concise-dashboards

What is Gross Sales?

Thu, 21 Dec 2023 22:36:20 GMT

If you're running a business, then you don't need me to tell you the importance of tracking your sales metrics. After all, the lifeblood of any business is your sales numbers. However, there are a few different ways that we can look at even the most basic sales metrics. Here, we'll discuss gross sales . What it means, it's general usefulness, it's specific utility, how it plays with other metrics, and some of it's limitations. This will be overkill. But sometimes that is good. Let's get into it.

So What Are Gross Sales?

Gross sales is a foundational metric in the health of your business. It provides you with an insight into the overall demand/market interest in your products or service.

Gross sales is the total amount of sales revenue before any deductions (discounts, returns, and allowances)

It's really that simple. How many units did you sell, and what was the average price? Knowing these two things will help us calculate the gross sales.

How Do I Calculate Gross Sales?

Super easy. As we said above, it's just the total revenue that's brought into the business. This is before you take out any deductions due to discounts, returns, or anything like that. So it's the most basic equation you'll see in an introductory economics or business course:

However, don't forget how we defined this above - before any deductions . This is the full price at which the item is valued in the market, regardless of whether it actually sold at this price. That means that our Price variable here needs to be the original listed price. In other words, if we listed our product for $100, then offered a $20 off coupon, making the price the customer pays $80, we would still be using $100 for the purposes of our gross sales calculation.

Luckily, the quantity part of this equation is straightforward. It's just the total number of units sold. Doesn't matter if they were sold with a discount applied, or if they were returned. If they were sold at all, for any amount, they're counted here in our calculation. If we wanted to, we could even get more direct with our equation and make it instead read as:

Why Don't We Subtract Discounts?

As of right now, you may still be wondering why we're not subtracting discounts from the price in our gross revenue calculation. That's because our gross revenue metric is addressing the total potential revenue, not the actual revenue that would be reported in your financials.

Once again, gross sales revenue helps you understand the total sales volume generated by the business. The insights here are definitely different than what you'd find in net sales revenue . Here, we are attempting to learn more about the total reach into the market, and the overall demand before we account for any of the concessions that led to the actual revenue for the business. Make some sense? Hopefully we're making progress. Let's use an example to round out this section.

An Example of Calculating Gross Sales Revenue

Let's consider that we're a bakery that only sells cakes. Each of our cakes is listed at $30. We know that we sold 100 cakes through the month of September. With this information, we can quickly calculate the gross sales revenue by taking that listed price of $30 and multiplying it by the total number of cakes we sold (100) within the month. That gives us a total gross sales revenue of:

This number gives you the total market activity of your cake business. Again, we're not considering here that you offered a "back to school discount" on cakes for the first week of September that was a buy one get one half-off deal. Again, our gross revenue doesn't care about the discount that was applied. We ignore any and all discounts, returns, or other allowances that could impact our net revenue.

Why is Gross Revenue Useful?

In broad strokes, gross sales provides a peak into your business's market engagement and the scale of operation. It has some standalone value, as we covered previously in looking at the potential within the market. However, it is also useful when combined with other metrics to create a clearer picture of the overall health of your business. As with most metrics, we have the cliche answer that it becomes more useful when viewed as part of a picture, rather than the whole thing.

Understanding Market Reception

One of the primary functions of gross sales is to serve as an initial indicator of how well your product or service is being received by your market. By using the total sales volume that we calculate with gross revenue, we can begin to gauge the overall interest or demand for our product or service. This can be particularly useful as you track this metric overtime, helping you identify if the interest is improving or waning.

If we see that gross revenue is increasing year-over-year, it may be an great sign that our business is continue to grow and gain market share. If, instead, it is decreasing, it may tell us that we need to take a deeper look. Maybe our message-to-market fit has become worse. Maybe there is a new competitor that is harming our sales. Maybe this is just a down year. The details of this decrease (or even increase of that matter) is not provided by gross revenue. Rather, it serves as an indicator that you may want to look more deeply at certain parts of your business.

Assessing Business Scale and Reach

By understanding your gross sales, you'll have an idea of the breadth of your business. Again, this isn't a metric that provides a lot of "deep" insight. But it does serve as a general benchmark for the health of the business. Again, allowing you to see how widespread your business is - capturing your marketing penetration and customer reach.

As with the market reception, the value of tracking gross revenue increases with time. With more data , you're able to identify trends in gross revenue, seeing if your business is expanding or contracting in terms of scale or reach.

However, this doesn't only have value in a year-over-year or month-over-month context. It can also be useful to identify how your gross revenue fluctuates seasonally. Seasonal trends may be something you are able to identify without explicitly tracking gross sales, but tracking it can't hurt. In fact, you may perform better in some months relative to others than you anticipated.

Marketing and Sales Effectiveness

In general, we know that sales are the lifeblood of any business. Understanding the performance of your marketing team, marketing campaigns, or sales team or sales campaigns, can be a daunting task. At first, it may seem easy and straightforward, but the more you dive into the details of statistical analysis and A/B testing, you may realize there is a lot more to it than you thought. But that's okay, because depth isn't the goal of understanding gross sales revenue.

If we consider gross sales again, we know that it doesn't take into account discounts. So, this can be particularly helpful in understand the reach of a marketing campaign. Are we selling more units due to this marketing campaign than we are relative to another one, or before we started it? That question may seem too basic on the surface. To be honest, there probably is more nuance that will help provide a much clearer picture. However, addressing that basic question in terms of gross revenue kickstarts the process of understanding the details of the marketing campaign performance and if we should invest more into the campaign, cut it short, or consider running another one.

Deeper Insights by Combining with Other Metrics

As we've mentioned multiple times in this section, gross revenue is a valuable first step toward understanding your sales numbers. It becomes more effective when viewed as a "pointer" or "roadmap" into where to look within your business. Increasing gross revenue - maybe you're all good and can evaluate if you should be doing more of what you've been doing recently. Or maybe your efforts are just continuing to pay off. Decreasing gross revenue - maybe you need to be looking at recent changes, new competitors, or what is potentially causing the decrease in units sold (assuming that you didn't decrease the list price for your products).

Again, that gives us the initial picture, but there is plenty more to dive into before we start taking action. Let's take a look at just a few of the other metrics we can use alongside gross revenue to make informed decisions within our business.

Comparing Gross and Net Sales

As mentioned before, net sales is the next step in evaluating your revenue. Gross sales gives us the idea of the overall potential within the marketplace, capturing the total sales regardless of discounts, returns, or other allowances. Net sales offers a more financial look at the sales. These take into account the discounts, returns, and other allowances. So net sales paints a clearer picture of the money actual brought in to the business. If we just think about the difference between gross sales and net sales, we'll be able to understand the impact of these concessions (discounts, returns, and allowances).

The action you take from evaluating the difference between gross and net sales will be different for each business. Your objective will largely tell you if the difference is unexpected relative to the goals you're trying to accomplish in that moment. Maybe you're trying to acquire a heavy list of new customers and to do so, you're offering steep discounts. This would result in a sharp difference between gross and net sales. But again, maybe that wouldn't be a problem.

Correlating Gross Sales with Marketing Spend

Another way to utilize gross sales with additional business metrics would be to compare it with your marketing spend. In theory, we would expect that our gross sales should increase as we increase our marketing spend. But we also want to be capturing the proportional increase, or the correlation between marketing spend in gross sales. Said plainly, for every $1 increase in marketing spend, how many dollars can I expect back in gross sales? This is also easily conceived as a "Return on Investment" of your marketing spend, or more directly Return on Marketing Spend .

Limitations of Gross Sales

We've discussed the limitations of gross sales throughout the article to this point. However, the limitations are quite significant, so they do warrant their own section. At it's most basic level, you're probably already on board with the fact that gross sales will overestimate the performance of your business. The reason for the overestimation, an incomplete picture of revenue, is a limitation itself. Finally, it doesn't provide any usefulness in terms of considering profitability. These three limitations are not entirely exhaustive, but the blind spots created from these make them the most important to understand from the start.

The risk of overestimation should be pretty self-explanatory given the definition we provided earlier. Recall that gross revenue ignores any discounts, returns, or other allowances. So by definition, if we've had any returns, applied any discounts, or offered any other concessions, our gross revenue will provide us an inflated view of the revenue within the business.

If we fail to account for this aspect, then we may consider our business to be in a much stronger position than it is in reality. Unfortunately, if you solely focus on gross revenue, you may not be aware of underlying financial concern, strain, or challenges until it's too late.

This risk of overestimation speaks to a larger issue of an incomplete (or improper) estimate of revenue. Again, this incompleteness means that you will be running the risk of thinking your business is in a stronger financial position than it actually is. Leading to you potentially overinvesting in your business.

Finally, it's important to remember that gross sales does not in any way equate to giving you an idea of profitability. This gross sales number provides some top line information in your financials. But don't forget that we're not including any information about costs. This should be evident because we aren't even considering discounts in gross revenue. However, it bears mentioning.

Unique Benefits of Gross Sales Analysis

Now that we've discussed gross sales generally and mentioned it's limitations, let's talk about some specifics of what we can do with this metric.

Market Pulse Indicator

As we've mentioned, gross revenue serves particular usefulness in evaluating the overall acceptance of your product/service within the market. Capturing the total sales volume. This can be exceptionally useful in the spotting of different trends. Gross revenue can serve as an early or leading indicator of market trends or shifts in consumer preferences. By keeping an eye on this metric, you'll be able to quickly identify emerging patterns that are relevant to your business. Early identification of surges in demand for specific products or services (or even variations of those products/services) can help you capture a larger share of the market if the trend continues.

A Tool for Short-Term Projections

Related to serving as an indicator of potential emerging trends, gross sales can also provide some insight in terms of sales forecasting. Since it serves as a pulse for current conditions, it can help you identify immediate increases or decreases in sales volume. This can be useful for inventory tracking, or even for helping you identify the ideal time for certain marketing campaigns. Combining this short-term insights into a longer-term view, you can begin to see trends that consistently occur. This can help you be more proactive in your planning, rather than exclusively being responsive to currently evolving changes - which may cause you to overreact to short-term fluctuations.

Let's add to this the capability of gross revenue to serve as an indicator for how well a new product or service is being received, or for immediately evaluating the impact of new marketing initiatives. This is worthy of a deep-dive itself, so we'll save a majority of this discussion for a later date.

Benchmarking

As we've mentioned in each of the sub-sections above - the benchmarking nature of gross sales is one of it's biggest advantages. As with most other metrics, tracking it over time will provide you with the most insight. Gross sales, however, has a unique benefit of being one of the easiest-to-understand and easiest-to-calculate leading indicators of your business. It can help you quickly identify what is normal in certain circumstances. Whether that's comparing a current marketing campaign to previous ones; comparing the seasonality over multiple years; or evaluating the continued success of certain products or services, gross sales can be one of the first indicators for a changing market or changing consumer behavior. Again, it doesn't tell you why these things are happening. And because it is a simple measurement, it won't even be easy to break it down further without a decent amount of additional work. However, it can point you in the right direction to start digging deeper to find more clear and comprehensive answers.

Conclusion

In this deep dive into gross sales, we've explored its fundamental role as a metric in the business landscape. It stands as a straightforward yet powerful tool, offering insights that are both broad in scope and immediate in application. As a business owner, gross sales are a quick and easy way to get a glimpse of your business's market activity, enabling you to grasp the extent of your reach and the market's response to your products or services.

By integrating gross sales with other financial metrics, you can paint a more complete picture of your business’s health and trajectory, guiding you towards informed, strategic actions.

Remember, in the world of business analytics, no single metric tells the entire story. Gross sales is a chapter in a larger book, one that includes various other financial and operational metrics. As we continue this series, we'll explore these other metrics, helping you develop a nuanced understanding of your business's performance and potential. Stay tuned as we delve further into the world of business analytics, where data becomes the language of growth and success.

Dimensions v. Metrics in Looker Studio

Thu, 27 Jul 2023 19:40:18 GMT

Anyone who's spent time with Looker Studio (formerly known as Data Studio) has likely encountered two primary data types: Dimension and Metric. For those of you that have more experience in data analytics, these probably seem intuitive on the surface. However, even some statistical experts may get tripped up with what Google means by each of these terms. In this guide, we’ll briefly cover the basics of each data type and highlight the differences between them. If you’ve faced issues in Looker Studio in making charts exactly as you want, this may help you solve your problems.

Data Types

Before we dive into the specifics about the dimension vs. metric conversation, it’s important to talk about what data types are in general. Whether you’re in Python, R, Tableau, or any other statistical platform or language you’ll notice there are similar distinctions. For instance, date variables are handled differently compared to variables like total revenue. You’ll also notice that if your data was not properly prepared, you’ll have your revenue numbers coming in as a “character” string, or in Looker Studio’s case, a character dimension. Understanding these different data types will help us lay the groundwork for the discussion.

Strings, Numbers, and Dates

For most people looking to analyze a data set, there will be three primary data types: Strings, Numbers, and Dates. Dates are more of a unique case, so we’ll start there. When we talk about dates, they’re generally formatted in one of a number of ways. For example, January 25th, 2023 can be written as 1/25/23, 2023-25-01, 25/1/2023, and so forth. These are treated as dates from the Unix datetime stamp. Generally, these are stored under the hood as the total time since January 1, 1970 - which is Unix time. But, the way it’s displayed doesn’t impact the actual storing of the data. Each platform will have its own default way of displaying these dates.

The reason this is important is because, when dealing with Characters (or strings) and Numbers, the way they are stored in your data set has a significant impact.. If you’ve worked with revenue data in the past, you may have come across issues where the program you’re using says it’s unable to do calculations on a string variable. Then you dig into your data and you see the revenue is stored as $1,000, for example. Well, the reason it’s not a number, is because it includes two different characters - the dollar sign ($) and a comma (,). The process to convert this into a numeric variable is beyond the scope of this article, but it’s important to be able to at least identify why this is happening.

Lastly, numbers are just as they sound, they’re numbers. This doesn’t require much beyond that, so we’ll leave this discussion here.

Dimensions in Looker Studio

Someone coming from a data analytics background may automatically assume that dimensions are string variables, and metrics are numeric variables. The names seem to suggest as much, at least. For the most part, you’d be right. But I would encourage you not to think of them this way. Rather, you need to consider if the numbers are already aggregated or not.

Looker Studio’s own documentation states that these dimensions are “a set of values by which you can group your data… categories of information”. That means that a character variable will always be a dimension. However, metrics can also be dimensions.

Using the same documentation as above, we see that “dimensions also include unaggregated numbers”. So this would include anything that isn’t already some calculated or aggregate measure. But what does this mean in practical terms?

In the image below, you’ll see that we have some fake data related to sales. We’re tracking the date, order number, category (online or in store), price, and discount. You’ll notice that we have two numeric variables - Price and DIscount. But what happens when we load this data set into Looker Studio?

These two numeric variables still come in as Dimensions . Why is that? It’s because those numbers are unaggregated. In other words, they are simply just another variable in your raw data set. Nothing has been done to them - they haven’t been transformed in any way - they’re just additional columns of information associated with a row in your data.

Let’s now take a look at the other side of the aisle - metrics.

Looker Studio Metrics

Metrics, as defined by Looker Studio , are aggregated variables that itself have no pre-defined values. No pre-defined values, what does that mean? It means that the variable only gets values once the aggregation is carried out. "For the aggregation to take place, some operation must be performed on one or more of the other variables. Let’s take, for example, the average of our price variable. The average of our price variable can depend on a few other things. For example, what if we filtered so that we only had Online sales? Our new average price filter would be recalculated so that it gives us the average price after the filter has been applied. This means that the metrics in your analysis calculate on the fly .

Why Does This Difference Matter?

This conversation may not seem super important to you, especially if you’re just starting out in Looker Studio. As you advance and start employing formulas, you'll likely encounter this error frequently.

Understanding the difference between metrics and dimensions will help you more confidently approach your Looker Studio dashboards, and find more success in creating new variables the first time.

Metrics as Separate Variables

There are two different ways you can utilize metrics within your Looker Studio Dashboard. First, you can have metrics as their own variables. This approach is preferred when you frequently reuse a number, or when the number has significant independent importance. The next way to do it is to create those metrics within formulas.

Creating it as it’s own variable makes it accessible in your data source. This can be done using the “Add a field” option under the Data tab, or you could do it directly within your data source by clicking on the “Add a field” button there.

However, if you want to only use the variable one time, it may be preferred to just create it within the formula it’s needed in. In that case, you can just aggregate the dimension directly within the formula by using one of the default aggregators, such as AVG(), SUM(), COUNT(), etc.

In Conclusion

We’ve covered a lot here. From different date types to the specifics of dimensions and metrics and what makes each of them unique. Understanding these differences can help you avoid unnecessary obstacles when building your dashboards.

There’s a lot more that goes into making efficient and expertly crafted Looker Studio dashboards. But this will help get you started.

Enjoy your dashboarding!

Mastering Client Dashboards for Local Businesses: A Comprehensive Guide for Marketing Agencies

Wed, 26 Jul 2023 17:24:00 GMT

As a marketing agency seeking to elevate the success of local businesses, utilizing the magic of data is non-negotiable. Data is not just a numerical record; it's a gold mine of insights that can revolutionize the operations of a local business. However, understanding data and extracting its value is a specialized skill. The next step in your marketing agency is to understand how to properly translate the raw, complex data into digestible, meaningful, and actionable insights. One crucial way of doing this is through an expertly crafted client dashboard . Let's dive into the principles and strategies that can transform your dashboards from being simple data interfaces to powerful business tools.

Understanding Your Clients Business

The first step to creating an impactful dashboard is to fully comprehend who will be using it. If you've been working with local businesses for any time, you'll know they are distinct entities, operating on different scales and principles compared to corporate giants or digital-only ventures. But that doesn't mean they don't deserve the same insights and data-forward thinking as those larger businesses.

Local businesses thrive on deep community connections and personalized customer relations. They don't merely seek global trends; they need localized insights, particular to their immediate environment. The challenge, however, is that local businesses are probably the least likely of business owners to have a deep understanding of SEO or digital marketing as whole. This can lead to challenges in communicating exactly what you’re doing to help their business grow, and make them question why they should continue to pay you every month while things are getting started. Communicating your value with a properly developed dashboard of your efforts (and even additional business insights) will make that the furthest question from their mind. You'll quickly become a trusted advisor to their business .

As a marketing agency, your role extends beyond service provision - you become the translator, converting intricate SEO metrics into a language of tangible results. The entire purpose of your client dashboard is to effectively communicate the progress and results of your efforts to your clients. This isn’t just about ranking. Most of the time, ranking is something they don’t even care about. Sure, it can be cool to see their business pop up, but even a novice in business knows that alone isn’t enough for their business to grow.

Using your data skills to create a dashboard that communicates the value of the ranking, now that starts to get into a better conversation. This won’t be something you’ll know immediately, or maybe it is - who am I to say - but it is something that can be learned and perfected . Most importantly, it can be learned on a client-by-client basis . That all starts in the line of questioning when onboarding the client, or when starting a new initiative. But we cover the planning in a different article, so I’ll refer you there for now and keep this squarely about the dashboard.

Designing a Dashboard that Resonates

With an understanding of the unique needs of local businesses in general and your clients specifically, you can create a dashboard that delivers real value . Creating an effective dashboard is a symphony of many different data points and approaches, but at its core it can be boiled down into just a few key elements:

Real-time data : Business environments are dynamic, requiring swift responses. Providing real-time data on elements like foot traffic or social media engagement allows businesses to make quick, informed decisions.

Localized data : Ensure your dashboard includes data pertinent to the business's geographical area. Local search performance or region-specific sales data can give invaluable insights to a business operating on a local scale. That’s right, sometimes including information outside of their immediate business can help cement your value to the client.

User-friendly visualizations : Data should be presented in a simple, digestible format. Use intuitive charts and maps that tell a clear story of progress and performance. We’ll touch on this more later in this article, but it may surprise you just how important the proper data visualization is to help the client feel comfortable using and understanding the dashboard you provide to them.

Customization : Each local business is unique and therefore requires a customized dashboard reflecting its specific needs. Some business owners will want depth, others will want only to see a few key metrics and only want to review the data deeply in monthly or quarterly meetings with you. Providing the latter type of client with a comprehensive dashboard may actually do more harm than good.

Now that we’ve covered some of the basics, I think it’s time to expand just a little bit on some more general points. While your dashboard is important, the dashboard is not the end goal . Making it pretty can be effective for some, but at the end of the day, an aesthetically pleasing dashboard is useless if it isn’t effective. Focus on the important parts of the data first. You can always adjust the layout later.

Bonus Thought:

Communication of your dashboard and data. While this is focused largely around dashboards, dashboards are not the only way to communicate insights to your clients. One thing we’ve found that has worked well with our agency clients is to set up automation sequences that provide their clients with key numbers every day, every week, or every month. These can go right into their inbox, be sent via text, or go into whatever project management tool they use with their team (think Slack, Hive, Asana, etc.).

These can be set up to only send them key numbers, or you could even embed a snapshot of the dashboard to be sent to them. That way they never need to go to another spot to see their insights. While you may want them to login to a specific platform, the truth is that it’ll matter much more to your clients that you’re giving them this information in a place they already spend a lot of time.

Effective Data Visualization

With the basics in mind, one of the things that matters the most in your dashboards are your data visualizations. A bad visualization can render your dashboard, and thus the data itself, completely useless. Data visualization is not just about turning data into graphics; it's about transforming raw figures into a compelling narrative that resonates with your audience. The key to effective data visualization is simplicity and clarity.

There are dozens of different data visualizations and variations on them. For most cases, you’ll only need a handful: Line charts, bar charts (and column charts), and maybe a map. But when should each be used?

Line Charts : Line graphs are best used when you have “time series” data. That is, something like sales over time, website visitors, or anything that you’re tracking on an hourly, daily, weekly, monthly, etc. basis. These charts allow you to identify any recent trends with just a quick glance.

Bar Charts : Bar charts are most often used for categorical data. For example, if you wanted to see the sales of each different service the business offered, that could be presented in a bar chart, where each bar represents the total sales. Bar charts can also be used in lieu of lines in a time series visualization. Sometimes, bars can be a lot cleaner.

Stacked Bar Charts : These are just a slight variation on the bar charts we discussed above. Using the same example (sales of different services), we could transform that bar chart into a stacked column chart by looking at the sales associate that closed the deal. For example, let’s use a really basic example of a roofing client that does roof replacements and roof repairs. Our bar chart would just show those two. But our stacked bar chart would be very similar, but there would be multiple colors for each of our employees that went out to do the work. The figures below will help communicate this more clearly than words can.

Maps : This can be particularly useful if you have clients that services larger areas, or are looking to get an idea of where their time is being spent. You can color the map to reflect the total number of jobs in that area, total sales, average job value, average job time, or anything else. This can be particularly useful in helping your client understand areas they should or could focus more resources on. Or, if they should expand their service area or make it smaller.

While these obviously don’t cover every type of visualization, these are certainly the most useful as you get started. One quick note here, you’re probably wondering “but what about pie charts.” Pie charts are horrible at communicating insights. Avoid them at all costs. Bar charts are just as easy to make and significantly easier to understand and see differences in. Do yourself and your clients a favor - avoid pie charts .

The Backbone of the Dashboard: Data Storage and ETL Tools

Behind every effective dashboard is a robust data storage system and efficient Extract, Transform, Load (ETL) tools. This may seem like something that you won’t need to worry about. I would encourage you to consider the counterpoint. Data storage is about ensuring that your data is secure, accessible, and ready for analysis at all times. By setting up a database, or even just using ETL tools that help you better control your data, you’ll be primed to answer questions that live below the surface.

While you may not be sure what a database even really is, much less how to create and manage one, don’t worry. Where you choose to go with us for your data management needs, someone else, or just try your hand at it yourself, it’s an important step to becoming a truly data-driven digital marketing agency. But the precursor to that is understanding how to properly organize your database, even if it’s just a spreadsheet , so that your data is as usable as possible.

That’s all we’ll say on the database setup side for now. Just realize you don’t need it to get started, so don’t let it hold you back. But, as you continue to build up your data muscles, a database will be one of the first places you’ll want to turn. For each individual client, and for all of them. The database will open up additional questions you’d be unable to even consider asking if you just stored all of your data in Excel spreadsheets.

Wrapping it Up

Creating powerful client dashboards can seem like a daunting task. It’s really only scary on the surface, and likely more scary because you don’t have the confidence that you can make the dashboard as pretty as it needs to be. Based on our experience of working with over 100 clients, only a handful of them have ever even cared about how it looked. And even those only came after they were able to see all of the data and insights they were hoping for.

Focus your efforts where it matters, improving the communication of your value to your clients. It will not only help retention, but it may even help you figure out how you can continue to improve your skills in serving your clients.

Dashboards have the power to tell a compelling story of progress and actionable data. As a marketing agency, your role is to help local businesses understand their narratives and use them to build stronger futures. In mastering this, you'll have a clear competitive edge, providing an unparalleled level of service to your clients.

How Can a Business Intelligence Dashboard Help a Business with Data Collection?

Tue, 06 Jun 2023 21:27:17 GMT

In the bustling digital marketplace, data isn't just a buzzword —it's the secret ingredient to business success. But harnessing the power of data? That's a whole different ball game. This is where a Business Intelligence Dashboard steps in, acting as the maestro conducting your data symphony.

What is a Business Intelligence Dashboard?

Think of a Business Intelligence Dashboard as your personal data concierge. It's a dynamic data visualization tool that serves up the most important metrics and key performance indicators (KPIs) on a silver platter.

These dashboards are as diverse as the businesses they serve. Whether you're a cozy bakery tracking daily sales or a global corporation monitoring operations across continents, there's a dashboard designed just for you. The magic of these dashboards lies in their adaptability—they can be tailored to focus on the KPIs that matter most to you, offering a snapshot of your business performance that's as unique as your fingerprint.

The Role of a Business Intelligence Dashboard in Data Collection

Now, let's talk about data collection. It's like the opening scene of your data story, where information from various sources is gathered to set the stage for informed decisions. While the actual collection might be a separate process, a Business Intelligence Dashboard plays a crucial role in directing and making sense of this data.

Imagine your Business Intelligence Dashboard as a control tower, providing a bird's eye view of your data landscape. It helps you identify where your data collection is hitting the mark and where it might be missing the target. It also shines a spotlight on gaps in your data, prompting you to consider other potential data sources. By offering a comprehensive view of your data, it forms an integral part of your larger data ecosystem.

Data Integration in BI Dashboards

Let's dive deeper into data integration. Picture it as a grand reunion of data from different sources into a single, unified view . This could mean pulling data from various departments within your organization or integrating data from external sources like social media platforms, customer feedback surveys, or industry reports.

The power of a good business intelligence tool, like a custom-built dashboard , lies in its ability to seamlessly integrate this data. It acts as a bridge, connecting disparate data sources and presenting them in a coherent, unified format. This not only ensures data accuracy but also provides a more holistic view of your business performance.

Real-Time Data Tracking

In the world of business, change is the only constant. That's why real-time data tracking is so crucial. Business Intelligence Dashboards provide real-time data tracking, allowing you to monitor your business performance metrics as they happen.

This real-time insight can be a game-changer, especially during critical business events like product launches or marketing campaigns. It allows you to spot trends as they emerge, identify potential issues before they escalate, and make timely decisions. However, the effectiveness of real-time tracking largely depends on the robustness of your data infrastructure.

Successful Data Visualization

Data visualization is the art of presenting data in a graphical format. It's about transforming raw, complex data into a visual story that's easy to understand and interpret. A good business intelligence dashboard will excel in this area, offering a range of data visualization options to suit your needs.

Whether it's a bar chart showing quarterly sales or a heat map highlighting customer demographics, the right visualization can bring your data to life ( just be weary of pie charts. ) It can help you spot patterns, identify trends, and uncover insights that might otherwise remain hidden. In essence, data visualization is about telling a story - a story that guides you through your data, offering insights along the way.

How Business Intelligence Tools Improve Data Collection

Properly built and optimized business intelligence tools are the unsung heroes of data collection. They're like the backstage crew in a theater production, working behind the scenes to ensure everything runs smoothly. They automate the process, reducing the risk of errors and ensuring data accuracy. These tools can also analyze and interpret data, providing valuable insights that can inform business strategy.

Data Analysis - Without it Your Data are Just Numbers

Data analysis is akin to a detective's investigation, sifting through clues to uncover the truth. Business Intelligence Tools can automate this process, making it quicker and more efficient. They're like your personal data detectives, identifying patterns, spotting anomalies, and even predicting future trends, providing you with the insights you need to make informed decisions.

There's a lot that can go into data analysis, but if you're new it's important to know that keeping it simple is the way to go. To get the most out of your data , the work is done before you even start analyzing. The value of your analysis relies on the clarity of the question you're trying to answer.

Data Reporting Tools

Data reporting tools are another key feature of Business Intelligence Dashboards. They're like your data storytellers, translating complex data into clear, concise narratives. They allow you to generate detailed reports based on your data, providing a snapshot of your business performance.

These reports can be customized to focus on the metrics that matter most to you, whether it's sales revenue, customer satisfaction, or employee performance. They can be shared with stakeholders, informing decision-making and strategy. In essence, data reporting tools translate your data into actionable insights, empowering you to drive your business forward.

Where to go From Here

In the grand scheme of things, a Business Intelligence Dashboard is more than just a data visualization tool. It's a powerful ally in your data collection journey, offering a comprehensive view of your data landscape, integrating data from various sources, providing real-time tracking, and simplifying data visualization.

Coupled with the power of Business Intelligence Tools, it can transform your data collection process, making it more efficient, accurate, and insightful. So, whether you're a small business owner or a corporate leader, a Business Intelligence Dashboard can help you harness the power of data, driving your business towards success.

Airtable vs. Excel: Why It's Time to Make the Switch

Fri, 12 May 2023 20:00:00 GMT

Comparing Airtable vs. Excel

Data management has long been a nuisance for a majority of small business owners. The tools that have existed for decades are either complex, esoteric, or just overwhelming. The biggest offender for most has been the go-to for many years - Excel. But if you're not an Excel wizard, I'd imagine there's been at least a few times you've sat there wishing there was an easier way to stay organized without diving into the complexities of a full-fledged database. Well, that's where Airtable comes in. Today, we'll compare Airtable and Excel and explore why making the switch to Airtable can be a game-changer for your business.

Easy-to-Use Interface

First things first, let's talk about the user experience . Airtable's intuitive, visually appealing interface makes data management a breeze. Unlike Excel's often-overwhelming grid of cells, Airtable organizes information into customizable, easy-to-navigate tables. Plus, with its drag-and-drop functionality and user-friendly design, you'll spend less time wrestling with complicated formulas and more time focusing on what matters – your business.

The best part is that if you're already familiar with Excel, the core functionality of Airtable will feel like second nature. It operates on tables, much like Excel does with sheets, but presents the data in a much more visual way, making editing cleaner and providing easier options for adjustments. You'll be able to understand your data at a quick glance.

Enhanced Collaboration

One of the most significant advantages of Airtable is its collaboration capabilities. With real-time updates and the ability to add comments, attachments, and even emojis, your team can work together seamlessly . Say goodbye to the days of emailing Excel sheets back and forth and tracking down the most recent version. With Airtable, everyone stays in the loop, ensuring your data remains accurate and up-to-date .

Imagine a project with multiple steps, where different team members need to complete different parts to keep things moving forward. With Airtable, you can assign tasks within projects to specific people and use robust automation features to send notifications when a new task is assigned. And the best part? The results are stored in the same place, eliminating the need for separate tools to manage data and projects. Everything is consolidated in Airtable!

Flexible Data Views

If you're trying to figure out where Airtable shines relative to Excel, look no further than it's built-in flexibility. Instead of being confined to a single view, you can switch between grid, calendar, kanban, gallery, and even map views, depending on your needs. This flexibility allows you to visualize your data in ways that make sense for your business, streamlining processes and improving decision-making.

For example, your team members might prefer a spreadsheet view for quick data editing, while you, as the business owner, need a broad overview and want to easily move items from "Needs Review" to "Completed." Your view can be a Kanban board, allowing you to drag tasks into the next stage, while your team works with the same data in a grid view. Pretty cool, huh? And this can all happen right within Airtable, without the need for any additional dashboard software .

Powerful Integrations

Your business relies on multiple tools to get things done, and Airtable understands that. It offers powerful integrations with popular apps like Slack, Google Drive, Mailchimp, and many more, allowing you to effortlessly connect your data with other tools, automating tasks, and keeping your workflows running smoothly.

Not only do some integrations come native with your Airtable account, but Airtable can also easily connect with popular automation tools like Zapier or Make, giving you even more flexibility when it comes to creating automations and saving time within your business.

Customizable Fields in Airtable

Airtable takes data customization to a whole new level. Unlike Excel's limited cell types, Airtable offers a variety of field types, including single and multiple select options, checkboxes, and even rating scales. This versatility allows you to tailor your tables to your unique business needs, providing you with the most relevant and useful data.

One of the best parts of working in Airtable is the flexibility when it comes to linking to additional records. Remember the project management we talked about earlier? Those tasks belong to a project. So instead of setting it up each time, you can create a project with standardized tasks and then link that project and/or those tasks to different parts of your base. This allows you to easily create once and reuse as many times as you need.

Want Some Help Convert Your Excel Sheets to Airtable? We're Here to Help

Robust Templates and Blocks

Still not convinced? Airtable also offers a vast array of pre-built templates and blocks to help you hit the ground running. This helps Airtable solidify itself as the right choice for a number of use cases. From project management to customer relationship management (CRM), Airtable has you covered. Plus, with their growing library of blocks, you can add advanced features like charts, pivot tables, and more, all without writing a single line of code.

I'll extend this even further to talk briefly about the automation capabilities. When you hear "automation" it may be daunting, or just sound like the new flavor of the month in 2023. But with Airtable's robust automations, you're able to easily read the prompts and set up some recurring, or standardized changes to your bases so you can make sure things get done in the same way every time. The ability to write custom scripts extends that, but we'll save that discussion for a more technical blog post we'll release at some point in the future.

Is Airtable Affordable?

That's a bit of a challenging question. Compared to Excel, which is practically free for all intents and purposes, it carries with it a potential cost. You can certainly get very far with just the free version of Airtable. So with that being said, I would say Airtable gives most solopreneurs the opportunity to test out the tool without having to reach in their wallet. To be honest, I have worked with multiple projects for clients that never moved off the free plan, because their use case didn't require them too. That's great, but sometimes you do need more functionality - like the ability to trigger a webhook in Zapier or Make, or you want more visual cues to better understand your data at a quicker glance. For those things (and many, many more capabilities), you'll need to upgrade your plan. But if you have a small team, Airtable can still feel like a steal for their reasonable pricing. It does get a little more pricey as you add more members, so make sure to thoroughly think through who will be using it and if their use cases justify the cost per user.

Final Thoughts: Make the Switch from Excel to Airtable

So, my friend, it's time to make the switch from Excel to Airtable. With its user-friendly interface, enhanced collaboration features, flexible data views, powerful integrations, customizable fields, robust templates and blocks, and affordable pricing, Airtable is the smart choice for business owners looking to level up their data management game.

Don't let the complexities of traditional databases hold you back from moving away from Excel any longer. Give Airtable a try and experience the difference for yourself. You'll be amazed at how much more organized, efficient, and productive your business can be when you're armed with the right tools. You can get started quite quickly with Airtable's handy quick-start guide . And remember, I'm here to share my knowledge and help you make informed decisions for your business. So, if you have any questions or need further guidance, don't hesitate to reach out.

Here's to your business's success and happy data managing!

Embrace the Future of Web Analytics with GA4's Event-Based Tracking

Fri, 05 May 2023 17:15:00 GMT

Website Analytics: Revised

As the digital world continues to play a larger role in business, understanding user behavior is crucial for optimizing your online presence, enhancing user experience, and ultimately driving conversions. Google Analytics 4 (GA4) has brought about a paradigm shift in the world of web analytics by introducing event-based tracking, a powerful and versatile approach that captures various user interactions on your website or app. Let's dive deep into the world of event-based tracking with GA4 and learn how to harness its potential to transform your data-driven decision-making process.

The Shift from Pageview-Centric to Event-Based Tracking

Traditionally, web analytics have relied heavily on tracking page views as a primary measure of user engagement. While this approach has provided valuable insights, it has left businesses wanting for a more comprehensive understanding of user behavior. Google has responded to that feedback with an update to the data collection and modeling used in their revised version of web analytics, GA4. GA4's event-based tracking offers a more holistic view by capturing not only pageviews but also a wide range of user interactions, such as button clicks, form submissions, and even custom events defined by you. This gives more control to you as the business owner, but while that flexibility can be good in terms of allowing you to track exactly what you need, it can bring about quite the learning curve.

Along with this is the automatically collected events, and enhanced event measurements. We'll get into the enhanced events below, but with automatically collected events it's important not to fall into the pit of just turning it on and thinking everything will be good. There are events that you will need to modify depending on your goals, your website (yes, even your CMS can effect what is tracked automatically because of the way parameters are handled), and more. Form tracking and video tracking are two of the events that have commonly seen issues when it comes to the standard tracking. After you set it up, take a look yourself to see if it is tracking things properly. Though we do recommend custom setups, which we'll dive into below, and using Google Tag Manager to handle the implementation.

The Event-Parameter Model: Granularity and Consistency

GA4's event-based tracking is built on the "event-parameter" model, a simplified and consistent data structure that assigns a name to each event and allows for additional parameters to provide more context. For example, when tracking an 'add_to_cart' event, you can include parameters like 'product_id', 'product_name', and 'price'. This granularity in data allows you to analyze user behavior at a deeper level, making more informed decisions based on specific interactions.

Event-based tracking also enables advanced reporting features, such as segmenting users based on the events they've triggered, creating custom audiences for remarketing, and setting up conversion tracking for specific events.

To follow up on what we said earlier about implementing these events yourself, you can see with the flexibility - through parameters and control over audience and segments - that this can also breed a lot of complexity. This is why it's important to start with your goals in mind , and then build upon that tracking on what you'll need.

Implementing Event Tracking in GA4

To implement event tracking in GA4, you can use either Google Tag Manager or gtag.js, depending on your website's configuration. We implement all Google Analytics 4 tracking using GTM, and we recommend that you do the same even if you decide to do this yourself. Regardless of the tool you choose, it's essential to plan your event tracking strategy by listing the events and parameters you want to track, ensuring consistency and meaningful data.

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Here are some steps to help you create an effective event tracking strategy:

Identify key user interactions : Begin by listing the most important user interactions on your website or app that you believe contribute to user engagement, conversions, or other key performance indicators (KPIs).
Define event names and parameters: Assign a descriptive name to each event and determine the additional parameters you want to track. Keep the naming convention consistent across your events for ease of analysis. For example, we like to use GA4 Event - event_name for all of our events, where event_name is something like generate_lead. (Ex. GA4 Event - generate_lead)
Implement event tracking: Use Google Tag Manager to set up event tracking on your website or app, ensuring that events and parameters are accurately captured. This will provide you with additional flexibility to include tracking codes for things like a Facebook Pixel, Google Ads Conversion/Remarketing, and external tools like Hotjar right from inside of your GTM container.
Test and validate: Test your event tracking setup to ensure that data is being collected as expected. Make any necessary adjustments and retest until you're confident that the tracking is accurate and reliable. This is exceptionally easy when using Google Tag Manager's Preview Mode, as you can click around on your site and see what events are firing and when.
Monitor and analyze: Regularly monitor and analyze the event data collected by GA4 to gain insights into user behavior, identify trends, and make data-driven decisions to optimize your website or app. You're in it for the long-haul, by monitoring your set up and data, you'll be able to make sure your data can adapt to changes in your business, website, or user behavior.

We're Just Getting Started

GA4's event-based tracking is a game-changer in the world of web analytics, offering businesses a more comprehensive understanding of user behavior and enabling more informed decision-making. By shifting from a pageview-centric model to tracking a wide range of user interactions, you can gain valuable insights that help you optimize user experience, improve conversion rates, and ultimately drive growth.

Implementing event tracking in GA4 requires careful planning and execution, but the benefits it offers are well worth the effort. By embracing this new approach, you'll be better equipped to adapt to the ever-changing digital landscape and stay ahead of the competition.

So, get ready to dive into the world of event-based tracking with GA4 and unlock the full potential of your data. As you embark on this journey, remember to engage with your audience, share your experiences, and learn from others to continually refine your analytics strategy and drive better results for your business. The future of web analytics is here, and it's time to embrace it.

Unleash the Power of Data-Driven Decisions for Your Small Business

Wed, 03 May 2023 18:08:36 GMT

Is your small business leveraging the full potential of analytics to make informed decisions and drive growth? With the right approach, harnessing data can unlock valuable insights, optimize operations, and boost customer satisfaction. In this article, we'll reveal common analytics mistakes small businesses make and offer practical solutions to help you sidestep these pitfalls and elevate your business.

Mistake 1: Drowning in a Sea of Data

It may seem counterintuitive at first, but more is not always better when it comes to data. Collecting too much data can lead to information overload, making it challenging to uncover meaningful insights. Let's consider an example: an e-commerce company is experiencing a decline in sales . The obvious approach might be to track broad metrics such as overall website traffic, hoping that an increase in visitors would eventually result in higher sales.

However, this approach might not reveal the root cause of the problem. Instead, the e-commerce company should focus on gathering more targeted data that truly matters. By prioritizing metrics like conversion rates, cart abandonment rates, and average order value, the company can gain a deeper understanding of where customers might be dropping off in the sales funnel and identify areas for improvement. Website visitors will still matter, of course, but focusing your efforts on collecting data that is not directly related to the objective will leave you feeling like you don't know where to start.

For instance, if we're starting from the point of a low conversion rate, we have a few things we may want to consider. First, it may mean that the user experience as a whole needs to be optimized. This could be discovered by looking at a handful of metrics, from engagement rate, to session duration, to the percentage of returning viewers. Alternatively, if we find that we have a low purchase conversion rate, it may be that there are some issues in the checkout process that is causing visitors to stop before they've finished their purchase. For this, it would be wise to go through the checkout process yourself and see if there is anything that causes a bottleneck for you. Maybe there's higher-than-expected shipping costs, or maybe the appearance during checkout makes the site seem less trustworthy. Maybe it's as simple as slow loading times. Often, as we can see from that description above, the "data" you collect by going through the experience yourself can help you find a good starting point for your analysis.

Taking the time to set a clear objective for your analysis will help make sure you're not only not drowning in your data, but that you're also setting yourself up to reach the correct conclusions based on that data. Being specific can lead to more effective data analysis, and ultimately provide you with a better understanding of the path forward. By honing on in the most relevant data points, you and your business can confidently tackle challenges and make more informed decisions.

Mistake 2: Setting Sail Without a Compass

Embarking on your analytics journey without clear goals can leave you adrift. Establish specific, measurable, and time-bound objectives to guide your data collection and interpretation. For example, let's say we start with an overall goal of increasing monthly revenue by 10% within the next quarter. That's a good starting point, but we can break that down into more manageable and informative KPI's that will help us understand why we are or are not hitting that target as we progress toward our deadline.

Let's go through some of the first steps of this process for a landscaping company. With our goal in hand of increasing monthly revenue by 10% over the next quarter, we will want to track additional metrics that complement, or tell the story behind the story of our revenue data.

Breaking Objectives Down into Smaller KPI's

Here, we'll dive into a few objectives that should be tracked alongside the revenue goal. The percentages are just an example. For your company, you will want to get solid numbers for how much you would need to increase each component to individually increase your revenue by 10% - if that was the only thing to change . By setting those targets high, and assuming that only this one measurement will improve as desired, you may find yourself in a much better situation when evaluating your main objective.

Boost the Number of New Clients by 15% - Track the effectiveness of your marketing efforts by monitoring metrics such as the number of leads generated, conversion rates, and cost per lead on all of your marketing channels. This will help you understand which channels are most effective in generating you new leads, and will also give you more insight into which ones lead to more rapid conversions. Alongside this, you should also track your own performance as it relates to your marketing data. What is the average time from lead (form fill out, or click to call) to you contacting them? What are the types of leads you're getting from each platform? Are some better than others? All of these things matter and will help you get a better understanding of the client acquisition engine that can help you cement a new baseline for monthly revenue, 10% above what you are previously doing.

Increase Customer Retention by 10% - Measure your client satisfaction through targeted surveys for your own internal use. Alongside this, send out request for online reviews. This will help your presence on social media and search platforms, and will help others that find your business feel more confident about reaching out. In analyzing your survey results and online reviews, are their any common trends that you can find? Are there certain things that clients appear to be dissatisfied with, or wish could've gone better? When creating your surveys, make sure you ask targeted questions. You want to be able to drive action based on their responses, so don't leave too much to open responses (though those can be incredibly useful as an "anything else?" type of question at the end of the survey.

Expanding Service Offerings or Upselling Existing Clients - If you offer multiple, complementary services, make sure you're tracking the amount of repeat sales, cross-sells, and upsells that your clients or customers are purchasing. If you're tracking these numbers, it will be much easier to take a quick look into the data and identify services that clients/customers think pair well together. This can help you create new packages, that offer those services or products in a bundle, and potentially increase the average order value of your clients or customers.

Improving Operational Efficiency by 10% - Monitor the time spent on each project, labor costs, and the utilization of resources. It's almost a guarantee that you can find ways to streamline your business that can help you either be more efficient in the fulfillment of your services, or reduce costs to improve your profit margin or reinvest in other parts of your business.

By setting smaller, more focused objectives and tracking the associated KPI's, you'll have a much better picture of your progress toward your overall objective and what parts of your business may need some extra care in your journey toward your goal. At the end of the quarter, in our example, you can evaluate your performance in each area to see what worked and what didn't and adjust your strategies accordingly. This will not only help you understand if you hit your goal and why, but it will also give you additional ideas that will keep you continuously improving your business and driving growth.

There are obviously dozens of smaller objectives we can break each of the bolded goals above into. This is just the starting point. I would suggest that you try to continue to break down your goals, and what data you would need to make sure the goals are able to be properly measured and tracked. Even if you don't know what data you would need, write down what you think it would be and don't worry too much about the details of tracking each at this stage. You'll get there, and mapping it out to get you thinking in a data driven way will be helpful in your long-term goal of creating a data-driven business.

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Mistake 3: Navigating with an Outdated Map

Outdated or unreliable data can send you off course, leading to costly mistakes. With the world evolving seemingly more rapidly than ever, it can be challenging to keep up with shifting consumer preferences. However, imagine, as a restaurant owner, you introduce a new menu item based on old customer preferences, only to find that it fails to resonate with your patrons. You may be left feeling disappointed and wondering what went wrong. You might even be tempted to double down on promotions or advertising to boost sales, but that may not address the root cause of the problem.

While it can be hard to keep up with the trends, by setting up things that we've already talked about above in the article (for example surveys of customer feedback), you'll be able to see how your target audience may be shifting their desires.

So, how do we keep up with it then? To make sure you're using the most up-to-date data, not just about preferences, but within your business as a whole, it's crucial that you adopt a proactive approach. Starting with surveys to get customer feedback is a great start. Comment cards, online surveys, or feedback forms are easy to implement and can get you on the right track for this. But it's also important that you keep up to date on the best practices when it comes to your selling tactics, offers, data tracking, and security/privacy. For example, Google Analytics 4 is completely taking over Universal Analytics for Google Analytics in July of 2023. If you miss the news on this and don't migrate before the transition, you'll be left with no data as the summer gets into full swing.

In addition to gathering feedback, stay attuned to industry trends and emerging consumer preferences by following industry reports, attending conferences, and engaging with local business groups. By doing so, you'll be better equipped to adapt your services or products to meet the changing demands, rather than needing to react to a downturn in business because of it.

Finally, when it comes to tracking your own business, we already mentioned the changes to Google Analytics above. However, your customer preferences can also be discovered through analyzing your own data. For example, are certain pages on your website getting a lot more traffic now, relative to the same period last year? Also identify seasonal trends, either in your data or based on what you know about your industry. This will allow you to be better prepared for periods in the year where business may be a little slower, and get creative to potentially cover some of the lost revenue in these months. Regularly monitoring your internal business data will help you see insights that may be too hard to see in the day-to-day operations of your business.

By embracing this approach and even only some of these strategies, you'll be better equipped to navigate the challenges of an ever-evolving business environment.

Mistake 4: Chasing Mirages with Vanity Metrics

Relying solely on vanity metrics, or even giving them significant weight in your analysis can create a false sense of success and obscure the true performance of your marketing efforts. These vanity metrics are things like page views, social media followers/likes, and anything else that lacks actionable substance. These superficial metrics can make you feel good, and think that things will begin to improve. But they lack the depth required to drive decisions and often just serve to distract your business.

Instead, you need to dig a little deeper to get a more accurate understanding of your marketing performance and uncover valuable insights. These actionable insights are necessarily better-defined, and attached to something that provides guidance on steps to take. These actionable metrics are created with a business goal or objective in mind, and measured intentionally to get the most value for your specific purpose.

There is a lot of detail that will be left for another article. But by shifting your focus from vanity metrics to metrics that are tracked intentionally and backed by an objective, you'll begin taking the proper steps toward having a data-driven business. These insights will help you get a clearer understanding of the effectiveness of, for example, your marketing campaigns and help you refine them based on the proper data. To illustrate this point a little more deeply, it's easy to imagine running two ads. One of them is a really low CPM (cost per 1000 impressions), and another that is quite a bit higher. Let's suppose the conversion rate is the same for both, and your objective is to get them to sign up for your email list. Looking at the vanity metrics alone, you may keep the lower CPM ad running and turn off the high CPM. However, digging deeper into the data, and properly tracking these people with tags and UTM parameters, would show you that maybe the higher CPM ad was producing 10x the return based on 30-day purchases of your service. Without digging deeper, and being distracted by the vanity metrics, you would've been turning off a wildly successful ad campaign.

As you navigate the challenges of data-driven decision making, remember to focus on the most relevant data points, establish specific objectives, and keep your data up to date. By doing so, you'll be better equipped to evaluate your performance, learn from your mistakes, and implement data-driven solutions that lead to long-term success.

Putting it All Together

By sidestepping common analytics mistakes and adopting a data-driven mindset, your small business can unlock a treasure trove of insights to fuel growth. An effective analytics strategy can help you identify inefficiencies, uncover hidden opportunities, and streamline operations. In the long run, informed decision-making can lead to increased profitability and a competitive edge in the market.

Embark on your analytics journey with confidence, and watch your small business thrive by leveraging the power of data-driven decisions.

Google Analytics 4: What You Need to Know For Your Small Business

Fri, 28 Apr 2023 14:00:00 GMT

What to Expect

If you've been running a small business for any length of time, chances are you've heard the word "Google Analytics" before. Most likely, you set up a basic implementation of Google Analytics when you set up your site, but probably haven't thought much about it since then. Unfortunately, the version most websites have installed (Universal Analytics) is no longer going to be used starting in July of 2023. Instead, Google has released their new and updated version - Google Analytics 4 (GA4). In this article, we'll explore what GA4 is, how it differs from Universal Analytics, and why it's important that you start using GA4 right away within your business. Let's get started.

Why GA4 is Important for Small Businesses

As a small business owner, your days are filled with fulfillment of your goods or services, managing the day-to-day, bookkeeping, managing employees, and probably many other things. Unfortunately, looking at the data of your business is one of the things that is easy to push off to another day when you have less going on. We get it, and it's a problem we see with almost all of the business owners we work with, no matter how big they are, or how data-driven they appear to an outsider.

The good news is that setting your business up to begin tracking some user data is much easier than you may think. With just a few button clicks, you'll be able to set your GA4 property up with the standard implementation. It's important to note that we actually don't recommend that anyone do this to set up their GA4 property. Instead, we recommend using Google Tag Manager to manage the implementation of all of your tracking codes. This, thankfully, is also pretty straightforward for most businesses, especially those that run local, service-based businesses.

So now on to the meat of this section: why it matters. Properly setting up GA4 with your website helps you understand what's going on when visitors land on your website. Do they have a particular interest in one of your pages? Is there a type of content that they're drawn to? Are there any issues with your website? These are just a few of the common questions business owners can ask and answer with just a simple Google Analytics set up. But why, you may be thinking, do I need to know about the user behavior on my website? I'm so glad you asked.

If your website gets any amount of traffic, then it's largely doing a lot of the heavy-lifting in your prospecting process, whether you know it or not. Sometimes, the only impression people have about you before contacting you is your website. That can get you into an entire discussion about proper web design and conversion rate optimization, but that's not the point here. The point is that even if you've invested tens of thousands of dollars into those things, you cannot fully understand if they're effective, or where they're falling short if you aren't tracking how the users are behavior in reality . To be honest, the list of reasons why setting up Google Analytics could be a full article in itself. But I won't bore you with more, because at the end of the day, it's a simple and painless process and it's results can speak for itself down the road.

Don't want to do this yourself? Reach out and we'll get everything set up for you.

What is GA4 and How Does it Differ From Universal Analytics?

To start, they both aim to accomplish the same thing: tracking the behavior of visitors on your website. They differ, though, in a few key ways. Here, we'll just very briefly consider Universal Analytics (UA) before spending more time highlighting the behavior of Google Analytics 4.

At it's core, Universal Analytics and GA4 measure things on different levels. UA was session-based, whereas GA4 is event-based. If you're familiar with the category, action, and label in Universal Analytics, you can largely forget about that when it comes to setting everything up in the new version. In UA, sessions could include multiple page views, events, interactions, etc. These were basically "scoped" as being 30-minute windows of one user interacting with your website. After 30-minutes, a new session would be logged, tracking similar information but grouping it under a new session.

With their new model, Google is focused on the events that occur when a user visits your site. For example, a page view would count as an event, a form fill out would be another, and everything else that happens during a users session would be considered another event. These sessions, however, are now keyed with different information, including a session start event which is automatically collected, and a session duration which compares the time of the first event (potentially a session start) and the last event (think of something like a generate lead from a form fill out).

While that may be getting a little into the weeds, we've tried our best to take out a lot of the specifics of the language to just give you the basics: the way in which Google collects data now is different.

A New Dashboard

If you've taken Google's suggestion to set up a GA4 property, you've likely seen that there is a difference in the appearance of your dashboard. This is mostly a problem for those of you that haven't set up custom dashboards to track your website analytics data. If you want a custom-built dashboard so you don't have to worry about how Google changes their interface, check out some of our Looker Studio templates .

More Machine Learning with GA4

With the updated tracking system, we get a new and improved machine learning model that takes into account newer advancements in the field to help you get the most of out all the data you collect. To a data nerd like myself , this is one of the most exciting features. With GA4, there are a number of automated insights and trends that may have taken you hours of manual work under the old model. For example, GA4 can help you identify high-value customer segments, predict which users are most likely to make a purchase, and even suggest optimizations for your website based on user behavior. Now, for most of this functionality, it will be important to read up on the California Consumer Privacy Act (CCPA) , and the EU's General Data Protection Regulation (GDPR) to make sure that your website remains in compliance with the most recent advancements in the law about consumer data privacy. For this, we would recommend that all sites implement a cookie consent banner on their site, and hold off on firing any analytics events until those cookies are accepted.

Google Signals

Google Signals has with it a lengthy terms and conditions that you should consult an attorney about before turning on. By default, this tracking feature is turned off. Google Signals can provide even more information about your website visitors if they're logged in to a google account when visiting your website. Read through the documentation about Google Signals carefully before deciding to turn it on, and make sure you turn it off in regions where you do not comply with local privacy laws.

Best Practices for Setting Up GA4 for Small Business

To get the most out of your GA4 set up, you'll want to make sure you do a few things right from the start so you're not missing out on valuable insights.

1. Use Google Tag Manager

GTM allows you much more granular control over the events that you're tracking on your site. You can pass custom parameters to get even more information (such as what page did they come from before triggering another event), and easily define custom events that aren't in the standard Google Analytics 4 implementation. On top of this, it easily integrates with other tracking tools such as your Facebook Pixel and Google Ads, so you can have one source of truth to make sure that all of these things are properly set up on your site, and only firing when they're supposed to.

2. Set up Conversion Tracking

Conversion tracking allows you to track specific actions that users take on your site, and give them additional weight in your analytics. Things like making a purchase, filling out a form, or clicking a "Call Now" button are good examples of conversions that most sites have. Note that sometimes you'll want custom events to count as conversions. For this, make sure you leave GTM and go back into GA4 and turn on the switch to identify that event as a conversion event.

3. Use Custom Events

With GA4's event-based model, you can track user interactions in more detail than before. Using custom events, you can define what actions matter on your site, and what information should come along with that action. For example, let's say that you have a page on your site that has a button and a video. The video explains your service offering, and the button allows them to take the next step. You can set up a custom event for that button click, and pass in a parameter that lets you know how far along users were in the video before they decided to take the leap and click the button. If you notice any trends in this, you could drive more action by either moving that point closer to the start, or just understanding what was said around that time that could've been driving your users to take the action.

Embrace It, Even With All of It's Quirks

We get it, change sucks. Especially when it comes along with a lot of new difficulties such as quota limits and configuration limits . But this is simply the new reality for free website analytics tracking. Implementing Google Tag Manager can help you better understand your set up and why you may be running into these limits (or even avoid them before they happen), so it's worth figuring out how to use that, or reaching out to us to help you get everything set up properly inside of GA4.

I'm sure we'll be writing another article on the details of GTM and exporting data into BigQuery. Until then, make sure you get your basic set up squared away so you're not starting from scratch come July of 2023.

Maximizing Your Data Analytics Investment: How to Get the Most Out of Your Analytics Tools

Thu, 27 Apr 2023 15:00:03 GMT

What to Expect

If you're looking to unlock the potential of your business and gain a competitive edge over your competition? If so, then data analytics is the secret weapon you've been looking for. Don't worry if you're new to the data game - we're here to help. In this blog post, we'll walk you through some practical tips on selecting the best analytics tools for the job, how to set them up properly, and ultimately how to use your new data pipeline to make data-driven decisions that grow your business. Enough talking, let's dive right in.

Assessing Your Data Analytics Needs

Before diving into the details, let's figure out what you really need from data analytics. Think about your business goals, like boosting revenue, reducing costs, or enhancing customer satisfaction. Let's focus on one of these goals—increasing revenue—and break it down into manageable, actionable steps.

Imagine you own a small bakery. Your primary revenue streams are sales of baked goods, custom cake orders, and catering events. You set specific growth targets for each revenue stream, like increasing baked goods sales by 15% or growing catering orders by 25% over the next year. Then, break down these targets into smaller objectives, such as acquiring 5 new catering clients per month or raising the average custom cake order value by 10%. Finally, identify key performance indicators (KPIs) that align with these objectives and establish a tracking and reporting system to monitor your progress.

Notice how we didn't stop at the basic goal, like increasing revenue. Instead, you need to keep going deeper until going deeper doesn't provide you with any additional insights that you'd be able to track, and thus take action on. By breaking down your goal of increasing revenue into smaller objectives and determining the best ways to track progress, you'll have a clearer picture of your data analytics needs.

Tips and Best Practices: As you assess your data analytics needs, make sure to involve key stakeholders from various departments in your business. This will help you get a comprehensive understanding of the data required for informed decision-making. Additionally, prioritize your goals and start with the most pressing ones, as this will help you see the impact of data analytics more quickly and motivate you to continue investing in it.

Choosing the Right Analytics Tools

This might not seem like a crucial step in the process if you're not familiar with data collection, analysis, and visualization. But whatever tools you choose will come with their own benefits, and their own shortcomings. By properly laying out your objectives like we discussed above, you'll be able to figure out what benefits you need, and what shortcomings are deal breakers. Let's take a look at some of the more popular tools for different tasks that you'll likely be doing as you begin the analytics journey within your business.

Website Analytics

Google Analytics 4: GA4 is the new go-to for tracking website analytics, such as traffic acquisition, user behavior, and conversions. It's free, and for most businesses, it'll the the perfect place for you to start collecting some data that can help you make decisions down the road. This is installed on your site by just copying and pasting a small snippet of code.

Google Tag Manager: This is a little bit different than Google Analytics, but they go hand-in-hand. GTM, as it's often referred to, is the preferred method of setting up the events that will be tracked in your Google Analytics property. You can also easily install things like your Facebook Pixel using GTM. It really is a win-win, that allows you to customize your GA4 implementation without needing to know how to code, or even really understanding how the code on your website works. Like GA4, you install this with just some copy and pasting. This is where it's advantage really kicks in. As mentioned, you can install the Facebook Pixel through this. So rather than having multiple tags you need to put on your site, you just add it into your tag manager which is already there and it'll start tracking events as soon as you publish your new GTM container.

Data Visualization Platforms

This section covers some of the more popular data visualization tools. For more complicated analyses, you may need to "pre-process" your data to prepare it to go into these visualizations. I've left that section below this one, because you can start with some basic visualizations without needing to do any additional work.

Google Looker Studio: Formerly Data Studio, Looker Studio is a free visualization software that is provided by Google. This is definitely the most basic platform, but for most cases it can be an excellent way to get started without spending any money, or spending tens of hours figuring out how to make a basic table. It natively connects to all Google products (like GA4, Search Console, and BigQuery), so you don't need to worry about additional investment to visualize your website analytics. Note: There are issues with quota limits if you use a lot of visualizations. These occur on the GA4 side of things, so it's not a unique problem with Looker Studio. There are ways around this, and if you want to know more, feel free to contact us and we'll help you get it squared away.

Tableau: One of the most popular data visualization tools on the market, Tableau excels at creating professional dashboards and provides it's users with a lot of flexibility to make their dashboards look exactly as they want them to. I would throw this in the "moderate investment" category, as there is a cost associated with it. Unfortunately, the pricing structure can be a little confusing at first if you're looking to get multiple licenses for different stakeholders in your company.

PowerBI: A fantastic data visualization tool, particularly for the Microsoft enthusiasts out there. With an Excel-type of feel, the layout and customization options are robust and shouldn't have too steep of a learning curve if you're using Microsoft products on a daily basis. With seamless integration into the Microsoft suite of tools, there are a wealth of features for businesses of all sizes.

Fully Custom-Coded: This is the most expensive option we covered, but also the most flexible. With custom-coded dashboards, you're able to take any vision you have and bring it to life for a fully unique approach to analyzing your business data. We do all of our custom dashboards using R as the backend (using the Rhino framework within Shiny). If you're looking to go this route, let us know and we'll help you figure out if this is the right direction for your business.

Bonus

While they don't fall squarely into "visualization" tools, Automated Reporting tools can be an excellent way to get a quick snapshot at your business every day, week, month, or whenever you see fit. With the ability to be integrated into your existing project management software (Hive, Asana, Slack, etc.), you can make sure that you get all the insights you need in the place where you're already spending a lot of your time.

Statistical Programming Languages

The section heading sounds scary, I know. Part of that is intentional, as this is something that isn't required as you're just getting started in your analytics journey. Once you hit a wall and are unable to figure out how to structure or analyze your data to answer a particular question, then it's time to turn to the more powerful tools.

R: As an R developer myself, I am partial to R. A massively flexible language that allows for clean code, advanced statistical techniques, and is focused around helping you get the most around your data. As a statistical language first, it does that and it does it extremely well.

Python: A much more flexible language than R, Python has some wonderful capabilites, particularly when it comes to scaling advanced machine learning models.

Tips and Best Practices

When choosing your various analytics tools, consider starting with a free trial to test its functionality and compatibility with your business before committing yourself to a subscription. For most people, it could be wise to start with the free options, even if you think you'll ultimately end up transitioning to a paid tool. This will help you get an idea of why that free tool isn't able to meet all of your needs, and may even surprise you by showing you that it can. It will also help you get a better understanding of what really matters when measuring and analyzing the data within your business, and what you can live without.

When opting for a paid tool, try to take a look at their documentation before moving forward with any purchase. Make sure that there is extensive documentation, so if you come across something you don't know how to do, there will either be tutorials or a community that will help you troubleshoot as issues arise.

Setting Up Analytics Tools Properly

Now that you've picked your tools and are ready to get going, it's important to take a step back and make sure you set everything up properly. Accurate data tracking, implementing custom tracking parameters, and regularly monitoring performance will make sure that you can extract the most valuable insights to fuel the growth of your business. Each tool will have it's own instructions, and because of that, we won't dive too much into the details here. Instead, be sure to read through each of the tools instructions, watch tutorials, or reach out to us for a free consultation so we can help get you on the right path.

Tips and Best Practices: Set up test environments whenever possible. This will allow you to experiment with the analytics tool before putting it on your live site. If, for whatever reason, things weren't set up correctly and could break your site, you would want to make sure that happens in a test environment and not on your actual website. All along the way, make sure to document your processes, as this will make it easier to update or troubleshoot down the road, and enable you to ensure consistency across your organization.

Analyzing the Right Data

All of the magic of data analytics can only happen if you're analyzing the right data. Focus on relevant data sources and track KPIs that align with your business goals. As you're getting started, use the data as a tool to answer specific questions, not as a way for you to find new questions to answer. Data visualization tools are your friend here, as they can help you quickly and easily spot trends and patterns in your data.

Remember our bakery example from earlier? Keep your entire process centered around the goals you established, like acquiring new catering clients, or increasing custom cake order values. Don't get distracted tracking irrelevant metrics, hone in on your specific goals and master tracking those first. Once you have a deep understanding of those metrics, you'll be better equipped to expand your analytics portfolio to include additional data points and questions.

Tips and Best Practices: Regularly review and update your KPIs and goals to ensure they remain relevant to your business's evolving needs. Don't be afraid to discard metrics that no longer serve a purpose, or add new ones that better align with the goals of the future. To help with this, scheduling routine data check-ups and analysis sessions can help you maintain a consistent understanding of your businesses performance and make proactive, rather than reactive, data-driven decisions.

Putting it All Together

Maximizing your data analytics investment is essential for success in today's data-centric world. A few wrong investments, and you may think that the analytics side of business just isn't for you. You can avoid those pitfalls by assessing your needs, choosing the right tools, setting them up properly, and analyzing the right data. By doing this, you not only save yourself money by properly investing your analytics budget, but you'll also be able to unlock otherwise hidden insights that can drive your business's growth and profitability.

Looking for help with this? Schedule a Free Consultation Today!

Data Analysis 101: How to Interpret Your Marketing Metrics and Make Better Decisions

Wed, 26 Apr 2023 14:00:00 GMT

Introduction

Imagine running a marketing campaign without any data to guide your decisions - it would be like driving a car with a blindfold on! In today's data-driven world, understanding and interpreting marketing metrics is not only crucial but also indispensable for businesses that want to make better decisions, optimize their strategies, and drive growth. However, many businesses find it challenging to interpret the vast amounts of data generated by their marketing efforts, leading to missed opportunities and suboptimal decision-making.

With even just basic data analysis, you can turn raw numbers into actionable insights that pave the way to success. In this post, we will discuss the basic principles of data analysis and provide practical tips for interpreting your marketing metrics to make well-informed decisions that elevate your business.

The Basics of Data Analysis

Data analysis is the process of collecting, cleaning, analyzing, and visualizing data to extract valuable insights and make informed decisions. The basic principles of data analysis include:

Data Collection: Gathering information from various sources, such as website analytics, customer surveys, and social media platforms
Data Cleaning: Removing inconsistencies, duplicates, and errors from the collected data to ensure its accuracy and reliability
Data Analysis: Examining the cleaned data to identify patterns, trends, and relationships that can inform decision making
Data Visualization: Presenting the analyzed data in a visual format, such as charts and graphs, to quickly and easily understand what's going on and what decisions should be discussed

Covering the buzz-words is important, but these ideas are too abstract if not applied to an example. To see how basic data analysis can help you identify problems within your business, let's take a look at a fictional fashion retailer, StyleSavvy.

StyleSavvy was struggling to understand why their website's conversion rate had been declining over the past few months. They've made a few changes to their website including a new layout, a chat-bot, and a change in their pricing structure to put more of the pricing on shipping costs to entice people to add-to-cart with a lower listed price. They weren't sure what was contributing to this drop off in conversion rate, so they set out to take a look at their website data armed with one question: "Where in the journey are their website visitors falling off?" After collecting and cleaning their website data, they analyzed user behavior and discovered that their add-to-cart rate actually hadn't changed much. It appears their change in pricing structure and new layout didn't impact the add-to-cart user behavior. However, a high percentage of visitors were abandoning their shopping carts at the checkout stage. By taking even a quick look into their data, and starting with a clear question, the owner of StyleSavvy was able to quickly see that customers were deterred by high shipping costs. As a result, they tested offering free shipping on orders over a certain threshold, which led to a significant increase in their conversion rate.

This simple example is probably intuitive to those seasoned in business, or even just purchasing on eCommerce websites. However, stick with me and we'll dive deeper into the process you should be taking to better analyze and interpret your marketing metrics.

Concise Dashboards: Who Are We and Why Should You Keep Reading?

Howdy, I'm Dan. Owner here at Concise Dashboards. I just wanted to jump in here real quick to tell you a little bit about what we do. If you're not interested, feel free to skip this section (it'll only hurt my pride).

We are a dedicated team of analytics experts who have worked across a number of industries, and all business sizes. From local pet stores, to Amazon advertising agencies, and even Silicon Valley startups. As a full-service analytics company, we set up your data pipeline (fancy word for how you get your data out of platforms and into your hands), automated reporting, user-friendly dashboards, and custom analyses for those of you that are looking to get even deeper into your data.

Want to see what we would do for your business? Click the link below to schedule a free data audit and see how you could be better using your data to increase profits, improve retention, and feel more confident in your decision making.

How to Interpret Your Marketing Metrics

To make the most out of your marketing data, it's essential to know how to actually interpret your metrics. All of the data in the world is useless if you don't know what to do with it. Honestly, it's probably worse than that. Without knowing what to do with your data, you could be making ill-informed decisions that you think the data support. But don't worry, getting started with data analysis isn't as scary as all the jargon you'll see about it make it seem. Let's dive into the basics and see if we can help you get a better understanding.

Define and Track Key Performance Indicators (KPIs)

When beginning your data analysis journey, it's easy to get overwhelmed with all of the data at your finger tips. Take a step back and shift your frame of mind. Rather than looking at your data and saying "look at all this cool stuff I can do!", say "what important business questions do I need to answer right now?" In this step, don't even consider if the data you would need to answer the question are available. Right now, just focus on listing out one or two questions.

For example, common starting places for many small businesses would be to look at:

How many people are coming to my website and actually signing up, filling out a form, or purchasing?
We're thinking about re-structuring our pricing to be more in-line with our competitors, what are our actual customer acquisition costs?
We're struggling to get returning purchasers to the site, is there a way we could increase our average order value of that first purchase?

Starting from a framework of questions like this, you'll be able to find overlap. This overlap in your questions will begin to help you better figure out what question you listed is the most important, and may even help you create a new question that feeds into all of this.

Analyze Customer Behavior

With your questions now figured out, we can go on to the next step: analyzing customer behavior. For most businesses, this can be as simple as setting up Google Analytics properly on your site to make sure that you can understand the behavior of your website visitors. If you're getting traffic to your site, there is a mountain of information your visitors are sharing with you. If you're not tracking this properly, you're missing out on valuable insights about what your website visitors are looking for, and if you're meeting their expectations when they visit.

If you're active on social media, running ads, nurturing via an email newsletter, there is even more information for you to go through. This is where it's easy to get lost in your data. But don't forget what we said at the beginning of this, by keeping it simple we can begin to get insights. We don't need all the information right away. So all we'll do right now is consider the various customer persona's we want to target. We'll file this away for now and circle back to it later when we get into segmenting your data.

FoodieHeaven: A Case Study

I always find that this information is much more useful when used in an example. So let's take a look at another fictional case study, we'll call this business FoodieHeaven. FoodieHeaven is a restaurant looking to improve it's social media engagement and drive more customers to their online reservation system. They've been at it for a few months now, but haven't noticed any significant uptick in the number of online orders. So, they turn to the data to see if it can offer any additional insight.

Analyzing the information on their social media platforms, FoodieHeaven found that their posts with high-quality images of their signature dishes received the most engagement. Even better, reposting of images that were shared from diners did the best. Taking a deeper look, they found that the time they posted significantly impacted the number of clicks to their online reservation system. Posts that were shared during lunch time lead to nearly twice as many bookings as those shared at other points throughout the day. Armed with these insights, FoodieHeaven now has a clear direction for their social media content: post high quality images during lunch time, and watch those reservations flow in.

FoodieHeaven wouldn't want to stop there though. After doing this exercise one time, they would be wise to continue monitoring this information to see if there are any changes in behavior, or if there are any deeper insights they could gain from properly testing and tracking different approaches.

Identify Trends and Patterns

Now that we've thought through the questions that matter for our business, identified our KPI's, and made sure that we're collecting data smartly, we can use this information to go a step or two further. The first step we can take is by looking for trends and patterns within our data, and within our industry.

Sometimes, the data you collect can only tell you so much . If you're in a smaller market, or a relatively new business, you may not feel confident that your data is giving you an accurate picture of what's going on. A great way to overcome this is to look for other businesses in your industry and track their methods. This could be done by checking out their websites, their social media, and even subscribing to their newsletters to see what they're saying - and most importantly when they're saying it.

To help illustrate this point, let's consider a seasonal service-based business like power washing. You've been in business for a few years, and you always find that there is a huge increase in the number of visitors to your website and appointments starting around March. Then, it dies off around Halloween, and repeats again next year. This cycle is important to know, and is something you likely won't need robust data to figure out. However, you're noticing that your clientele is rather flat, and you don't have any confidence in the number of appointments you'll get in the next March. So, you decide to follow the content that a few very successful power washing companies a few states away are posting and you find out they have an early-booking incentive program they start immediately in November to book them out for the next year. Interesting, right?

By looking not only at your trends, but the trends of the businesses around you, you'll be able to get a lot of what we call "unstructured" data. In this sense, your unstructured data wouldn't necessarily be numbers on a spreadsheet. Rather, it would be knowledge that you're gaining from following these other companies and using their experience to move your business forward.

Segment Your Data

This section is a little bit more advanced, but it is something you should start doing as early as possible. But what does it mean? Segmenting your data is simply breaking your data down into smaller groups based on factors like demographics, behavior, or geography. Luckily, it's pretty easy to do this within a variety of tools, whether it's Google Analytics 4, or an email marketing system like MailChimp or Klaviyo.

This serves two purposes for your business: Targeting, and Better Analysis. We'll cover the targeting in an example below, so here I want to focus on what I mean by "Better Analysis." If you think about your data with segmentation in mind, you'll quickly be able to think about your business in a much different way. Rather than a large sea of potential clients or customers, you have a lot of little ponds that you can go fishing in. Some ponds are better than others, either with simply more fish, or better fish that are maybe a little harder to come by. Getting an early understanding of this within your business can help you be a lot more effective early.

Looking at the targeting side, segmentation is often discussed in the context of email campaigns. Let's again use a fictional company, MailMasters, to discuss how segmenting could be used to improve their clients open and click-through rates.

Case Study: Segmenting to Improve Email Campaign Performance

MailMasters set out with a simple goal in mind - improve open and click-through rates of the email campaigns they run. When they got started with this, they couldn't figure out a rhyme or reason that some campaigns performed better than others. They realized one big problem: they were treating all email subscribers the same, no matter what.

Solving this problem was relatively easy for them because they had a set of data about the purchasing behavior, and acquisition channel (ex. the ad they came from or if they found them on social media) for each of the emails. With this information in hand, they're able to better craft specific messaging to that particular group.

For example, if someone became an email subscriber because of an ad campaign that focused around baseball, it could be useful to use that information within an email campaign since they likely have an interest in baseball. Meanwhile, if they came in through Instagram, maybe they loved the visual aspect of the work that was being done, and it would be better to tailor the messaging around that. Hopefully with this simple example, it's clear to see how segmenting your data to create insights, and tailor messaging can lead to improvements within your business.

Test and Optimize

We mentioned this earlier when talking about FoodieHeaven's analysis of their social media, but the idea rings true for everything about your marketing efforts within your business. Proper testing is the key to figuring out what messaging works, and what maybe falls a little flat. Commonly, people start by testing and optimizing different ad copy, landing page designs, calls to action, and email subject lines. We recommend this as a great starting point. The important part here is the "proper" part of the testing. Blindly testing is effectively throwing money down the drain because you aren't able to pull out any valuable information from your tests.

What do we mean by this? I'm glad you asked. We used a few examples above, but let's just focus on one: landing page design . If you're running ads and you want to see if you can improve their performance by changing up the landing page or call to action, here's the approach we would take. Change one thing for each test . That is, if you're changing the landing page design, do one thing - for example change the header image from a group photo to a photo highlighting the product. That's one test. Run that and see how it performs. Then, once you see a winner, change the button color from it's usual color of blue to green. Run that test, and see how it performs. Are you starting to see a pattern here?

By changing one thing when you're getting started with this, and running simple testing, you'll be able to actually compare the performance of each to each other, because the only thing that changed was the one change you made . If everything else remains equal, it could be suggestive that the difference in the performance is due to the one thing you changed.

Putting it All Together

Navigating the world of data analysis can be challenging at first. There are a lot of new words, a lot of flashbacks to a statistics course you may or may not have taken, and a lot of people steering you in complicated directions that make you think that an "all or nothing" approach is required. By starting out with some basics, and laying the foundation to go along with that, you'll be well-equipped to begin unlocking the hidden potential within your marketing efforts.

Bonus Insight

We took the goal setting for granted here, and laid out only some basic objectives at the beginning of this. To make the most out of your dive into data-driven decision making, you'll want to be setting specific, measurable, achievable, relevant, and time-bound (SMART) goals. By doing this, you can better align your marketing strategies with your business objectives, track your progress, and evaluate the success of your campaigns.

Make sure that each of your goals are clear, quantifiable, realistic, and connected to the overall vision for your business. By setting a time-frame for these goals, you'll make sure that it doesn't get lost in the shuffle of things to do as a business owner. If you take one thing away from this long article, let it be this - data analysis is not a one time task, but an ongoing process that helps you stay ahead of the curve and make well-informed decisions .

The Role of Analytics in Data-Driven Marketing: How to Make Better Business Decisions

Fri, 07 Apr 2023 19:00:01 GMT

In today's digital age, businesses have access to an unprecedented amount of data about their customers, their marketing campaigns, and their overall business operations. Everywhere you look, you’re constantly told how data is everywhere, and if you’re not using it in your business… well, they’re sorry to say - you’re just not doing business right.

But that’s the difficulty that everyone seems to gloss over. Making sense of this data and using it to make informed business decisions can be a challenge. What data should you collect? How should you analyze it? Are you violating privacy laws? Is it “this data” or “these data”? The list of questions only seems to grow the more you learn.

But, before we can get into the nitty gritty, we have to set a foundation for what we’ll be talking about throughout this. So, let’s start with the big one: “Analytics.” Analytics is the process of collecting, analyzing, and interpreting data to gain insights and make better decisions. I’ll refer to this entire process as your analytics system. It’s not just the dashboards and reports, it’s everything from raw data collection, through automated emails that tell you your numbers from the day before.

In this blog post, we will explore the role of analytics in data-driven marketing and provide practical tips for businesses on how to make better business decisions using analytics.

Assessing Your Analytics Needs

This is a crucial step that is overlooked far too often. The conversation in your head becomes “well, I might as well get as much data as I can, right?” For the sake of a small business, I’m going to stand my ground and say that’s just flat out wrong .

You might be wondering why I would take such a strong stance on that. It’s because I’ve seen what happens when businesses take that approach. They’re tracking every little click on their website (even for things that don’t matter), the shirt they were wearing on the day they closed 5 new deals, and everything in between. The truth of the matter is, collecting too much data can lead to two major negatives:

Overwhelm . Let’s be honest. If you’re looking at dozens and dozens of spreadsheets, it’s hard to keep track of what’s happening, let alone draw conclusions from that data.
Incorrect Conclusions . With too much data, there’s a chance you’ll create spurious (think bogus) connections between your data that may cause you to shift your focus to channels that aren’t as successful as you think. “Muh data” I can hear echoing in the minds of some right now. Start with a little trust in me, and if you take this journey, you’ll be better off for it.

With that out of the way, we can talk about how we can actually assess your analytics needs. This is actually quite straightforward to do. For most businesses, there are really a few things that are necessary to track as early as possible.

To figure this out for your business, convene a council of the best business minds you know (your dog definitely counts) and just start talking about your overall goals. Do you have a growth rate target you want to hit? I personally, would opt for a question of - “How much did we make last year, and what number will we be disappointed if we don’t make this year?” The data you collect should be relevant to every question that you find yourself asking. Pay particular attention to the ones that keep you up at night.

Choosing the Right Analytics Tools

Once you have an idea of the questions you want to answer, we can now begin figuring out how we might start tracking data that can help us figure out the answers to our questions.

The biggest one to mention right from the start is Google Analytics 4 . GA4 is the new and “improved” version of analytics tracking provided by Google. If you’re like most people and prefer Universal Analytics, just make the switch. I put “improved” in quotes for a reason, but UA will be going offline in July of 2023. The longer you wait, the less data you’ll have when it’s all you can rely on for website data.

Now, tracking your website data can either be really important, or something that doesn’t matter a whole lot to your business. For an eCommerce store, your website data is pretty much everything. For a local service provider, it can be useful, but don’t spend weeks trying to get everything just right. Set it up, get a few custom events, and then make adjustments as they become necessary. Or, you can reach out to us about our Local Service GA4 set up and we’ll get it all squared away for you.

Other than that, the next step for most will just be trying to figure out how to get their data out of various platforms and into a system that they can manage. For example, for Facebook, Instagram, and whatever email system you use. Each of those platforms already track data and provide you with some level of a dashboard. You may be thinking - okay, I just need to figure out how to better use the reporting within the system. Maybe. But most likely, what you should be doing is trying to get the data out and stored in your own database, Airtable base, or even the dreaded Excel spreadsheet or Google Sheets.

You can choose a number of Connectors, as they’re called, to try to get your data out and stored in yo ur own system. These are just tools that companies have built to interact with the API of each platform. Rather than having to do the programming yourself, they do it for you and give you your data in a readable way. The one you choose will depend on a few things, mainly what they offer connections to and how much they cost per month. The details of this step will be reserved for another post in the future. Just keep this in mind as you’re thinking through your goals.

Setting Up Analytics Tools Correctly

Now that you have some idea of the numbers you want to be tracking, and some of the data sources you’ll be using, we need to dive one level deeper. In each of these tools, there’s a right way to set things up to get the most out of your data.

You may be thinking that I’ll tell you the best way to use the CSS selector to track button clicks in Google Tag Manager for GA4. Well… you’d be wrong. While that can be important, that’s way too far into the details to be valuable for most people just starting to take a deeper look into their analytics. As I said before, let’s start with some of the basics to lay a proper foundation. After we have that, then we can move into the more intermediate and advanced techniques to get the most out of your data.

So if not that, then what? Reasonable question. I want to highlight two things: the naming convention you use, and how to make adjustments and tests.

For naming convention, this is something that can easily be overlooked. We want names to be descriptive, yet not too detailed to where it’s 200 characters. Let’s take a Facebook Ad structure as an example. This will touch on the naming convention, but also the general structure that might make sense to set this up. I’m a data guy, not an ad guy, so don’t come at me for this illustrative example.

For this example, let’s just set up one specific goal for our campaign. Let’s say this goal is website clicks. So we’ll call our campaign something like “Campaign - Website Clicks - 001”. This will allow us to have room to make other campaigns (by changing out website clicks in the title) and also add more campaigns with the same goal, by changing the number to 002. Don’t forget, this is just one way of doing this.

Next, we go down into our ad group. In this ad group, we want to be using a specific type of ad. For example, carousel ads. Then, we can have another ad group that is using all video ads. We would name these “Ad Group - Carousel - 001” and “Ad Group - Video - 001”, respectively. You an see how we could easily add more detail if we had additional parameters that made these ad groups unique.

Finally, we go into the ads itself. Let’s say we have two ads inside of our carousel ad group. The first one uses bright colored pictures, the next one uses the exact same pictures, but with dark colors instead. We could name these “Ad - Dark Images - 001” and “Ad - Light Images - 001.”

Now, if we wanted to compare the data between our ads, we would have a few pieces of information we could use.

From our naming convention, we can easily understand what each ad, ad group, and campaign are because we descriptively named them. You may be thinking, “I just set them up, I won’t forget what they are!” Trust me, you will . Even if its only a few days from now, let alone a few months, you won’t remember and you’ll need to take some extra time to click into the specific ad or campaign to see the details.

But more importantly, in setting up the naming convention, I was also setting the stage for what everything was going to hold. All ad groups within the campaign used the same goal, and all ads within each ad group used the same ad type. This makes our life a lot easier when we go to compare results and see what’s working, and what’s not.

Take, for example, if we set up our ads differently. Recall that the only thing that changed was the shading of the image - bright and dark. If we instead used different images inside of the ads and changed the darkness, we wouldn’t know if it was the images themselves or the shade over the images that was more or less successful. Same thing goes for the text. If we had changed the text on one of the ads, we would now be making our life a lot more difficult when it comes to analyzing the performance of these ads.

That takes us into the next point, analyzing our data. But before we get there, I want to give a bonus tip here for how to best store the data you are storing yourself in some sort of spreadsheet .

In analyzing the data in the spreadsheet, it may make sense to put the different values (such as dates) as columns across the top of the spreadsheet. Then, you’d fill in the values in each cell. While it might make it easier to see in the spreadsheet, it basically makes your data unusable from an analysis perspective without first needing to “pivot” the data. You don’t want to be analyzing your data in Excel, so store it in a way that can be usable by more robust tools.

For the curious reader, the format I just described is “Wide” data, and should be avoided in almost all cases you’ll come across. What we want is “Long” data, which stores values at the intersection of a row and a column, and uses columns to categorize information (such as date).

Analyzing the Right Data

Asking the right questions, laying out the data we collect, and properly setting up our data systems to feed us with usable data has finally brought us to this point. Analysis.

I’m not sure why, but the word analysis seems to carry some fear along with it. If I told you to analyze your data, you may be intimidated and not sure that you could do it at a super high level. That may be true, you may not know how to run machine learning algorithms or neural networks, but the world is lying to you by saying that you need all of that within your business.

Remember the theme of everything I’ve talked about throughout this article, keep it simple and do the basics.

Rather than diving down the rabbit hole of predictive modeling, causal inference, and other big words that may make you feel overwhelmed, let’s use some really simple examples .

Let’s go back to our ad example from before. Because we set everything up properly, we’ve done 95% of the work. Analysis can be as simple as looking at the cost per click between the two ads we created, and seeing which one provided us with website clicks for a lower amount per click. Taking that one step further, we may be able to compare the behavior of users that came from each ad, depending on how we set up our website tracking.

Maybe the light colored ad was giving us clicks for, say $3. Not bad, you think as you look at it. Then you take a look at the dark colored ad and each click was only $1.

You might stop there and think to yourself “I can’t turn that light colored ad off fast enough.” But then you look at user behavior and find that none of the people from your dark colored ad gave you their email to download your free thing. Meanwhile, 10 people from the light colored ad did.

The goal of your ad was to get website clicks. But diving deeper into the data shows that even though the light colored ad clicks were more expensive, they were seemingly much higher-quality clicks.

Look at that, with only a few moments, we were able to do some basic analysis that led us to making a data-driven decision within our business. Because we set everything up correctly, the analysis portion was a breeze.

Now, obviously, analysis can get much more complicated. Even in our simple example, I’m sure there are dozens of ways that we could complicate the analysis to suggest that we weren’t looking deeply enough at our data. But remember, getting started with understanding the actions you’re taking, why you’re taking them, and how they help you better measure your objectives is the goal of using a data-driven approach to begin with.

You don’t need a Ph.D. to crunch the numbers on your business.

Conclusion

We covered a lot here, and if you’ve made it this far - kudos to you. You should now be on a much better path to understanding how to utilize a data-driven approach in your business. And as an added bonus for you that have made it this far, I want to share a piece of wisdom I learned when I was in graduate school.

As an economist, we would constantly talk about the “economic way of thinking.” It was a framework that helped you approach problems from a particular angle. Data analysis, and being more data-driven within your business is the same thing. It’s a mindset. It can surely be challenging, but once you start utilizing a data-driven mindset, the details of how to do it will begin to fall into place. And hopefully at the end of it, you can have a greater understanding of your business and grow to help more people with the services or product you offer.