Becoming Data-driven

4 vital steps to becoming a data-driven company

Step 1- Remove emotion from the equation.

Your data will always tell you a story; it just sometimes tells a story that you don’t want to hear. Often we find that people stop listening to their data when it gets hard, or right when the details are becoming the most important; but those are the times when you need to listen to the story that it’s telling you even more.

You need to take emotion out of your decision making process if you really want to become a data-driven company. Often the climate of the business has a huge impact on our lives, so it’s often difficult to separate your emotions from the decisions that you make, especially during the hard times. When the times are the toughest are generally when you need to be the most data-driven, and those are the hardest times to take emotion out of the equation; but if you do, it will help you to trust your decision-making process much more.

How do you remove emotion from the equation? The simplest way to remove emotion from the equation is to just let the numbers speak for themselves. No matter how hard things get, they will always get harder if you make the wrong decision.

It’s one thing to make the wrong decision because you went with a knee-jerk reaction; it’s a whole other beast to make the wrong decision because you had bad data. That’s why our next step is:

Step 2- Get your tracking in order.

You can’t make good decisions off of bad data. If your tracking is off, all of the insights that you get from that data are tainted.

One of the top 5 mistakes that businesses make is assuming that everything is tracking properly. Google Analytics is a very powerful, robust tool that helps businesses gain insights into their customers and their behaviors. It is also the number one most underutilized and error-prone tool used by small and medium businesses.

Analytics tools are notoriously difficult to set up properly, and unless you have an expert come in to set it up for you, or you invest the time to truly understand how to set it up properly, it can quickly turn from a bucket full of data to a bucket full of holes.

Many businesses know that their tracking is not correct, but they don’t know how to fix it; so they take the incomplete or inaccurate data that they have and they do their best with what they have.

The end goal of this step is to get you to the point where you have:

  • Organized UTM’s
  • Advanced Pixels
  • Custom Conversions
  • Event Tracking

We’ll go through each of these goals individually:

Organized UTM’s:

UTM’s are one of the most powerful tools that you have in your analytics arsenal, but they can also be very daunting to get started with. That is why we have written several blog posts on the subject matter, which you can find here: How to increase revenue with one simple tweak, Why UTM’s are so important, and we even set up a course that will teach you from start to finish how to create UTM’s and even has a spreadsheet that will automatically create them for you here: https://datarich.thinkific.com/

Advanced Pixels:

Tracking pixels generally have a similar functionalities to cookies. However, as more and more users are blocking cookies using browser functions, cookies provide incomplete data, and are often blocked completely.

Tracking pixels area good alternative to cookies as they cannot be blocked by a normal browser currently. Pixels gather a vast array of user data and pass it along to analytics tools. Some of the most popular advertising platforms use pixels to track user behavior and conversions. In addition to the basic tracking functions, pixels can also track custom events, such as video plays, button clicks, or time spent on a page.

Custom Conversions/ Event Tracking:

As we discussed in advanced pixel tracking, you can track so much more than simply page views and conversions. There is no end to the number of behaviors that you can track on a page. We recommend setting up custom goals, conversions and events within your analytics properties and assigning values to each of these items. While someone may not have purchased through your site, they may have filled out a contact form, or given their email address. If you know the average conversion rate for clients on your email list, and the average order value for them, you can assign a value to each email signup.

It’s just like we always say, your output is only as good as your input. If you can get your tracking in order, you are more than halfway through the journey to become a data driven company.

Step 3- Automate your reporting

Once you have your tracking in order, and you know that you have accurate data; you can move on to the next step: automation

You’ll know you’re ready for this step if you have all the complex tracking in place, but you or your team spends a ton of time gathering valuable insights from different systems and compiling them together into google sheets or into excel and pivot tables.

What compound interest is to your money, automation is to your time.

Businesses that we work with get most excited by this step, because it’s where we begin to focus on scaling the business. Automation leads to a reduction in overhead, increase in productivity, and allows you and your team to focus on the analysis of the information, rather than the collection of data. Automation eliminates the human error component of reporting, further allowing you to have complete confidence in the data that you receive.

To scale your business and progress even more, the focus shifts to integrating your systems together so that they automatically transform the raw data into the insights you need to take action. This allows your team to focus on valuable actions rather than mundane data entry. In technical terms, this is called ETL (automatically extracting, transforming and loading your data into one place). For more information on this process, and how we use it with the companies that we work with, be sure to check out our post on data-driven mistakes even good ecommerce business owners make (and how to avoid them).

Step 4- Democratize the data

The final step that you need to take is to share this information with all the people on your team. You wouldn’t believe the value that democratizing your data can have on your organization. Sharing data allows people to bring their diverse backgrounds and viewpoints to the data to help interpret it.

By allowing your team to access the data, they can bring valuable insights to the table and different perspectives that you might not have seen. We call this the lift effect, and we have seen it happen many times across multiple companies and industries. We recently talked to one of our clients about the value that democratizing data has had for them. Be sure to check out our full interview with Organifi here.

Everyone has their own ideas about what it means to have a data-driven culture. We don’t believe that this list is exhaustive by any stretch of the imagination; but we do believe that if you follow these steps, your business will transform into a data-driven organization. If you follow the steps that we outlined here, we guarantee that you will see a change in your business.

If you have questions on any of these steps, or need help with implementation; we are here to help. We provide comprehensive analytics audits to help see where you may have issues with your data. If you struggle with automation, we have a series of pre-built dashboards that can automate your data for you. If none of those interest you, we can also build out custom dashboards to measure unique metrics for your business.

The importance of knowing the lifetime value of your customers

Data-Driven Conversations: The Importance of Knowing The Lifetime Value of Your Customers

What is the lifetime value of a customer? How does that affect the way that you market your products and scale your business?

These are some of the questions that we had in mind when we went into our conversation with Jeremy Reeves on the Data Rich Podcast. Below is the video of the entire conversation, as well as a transcript of the highlights:

What does it mean to be data driven as it relates to customer LTV?

Being data driven boils down to being aware of the choices that you are making, and making the right choices by utilizing data.

An example of this would be if you are looking to roll out a new product, you need to know exactly how much you can spend to acquire a new customer. If you don’t have data to tell you that information, you are essentially guessing, and that can cause you to be limiting yourself in terms of growth if you’re not paying enough for new customers, or it can be driving you out of business if you’re spending too much to acquire those customers.

If you don’t know the metrics, you don’t know what decisions to make.

How soon in a business should you worry about LTV?

This varies from business to business, but comes down to how quickly you want to scale your business. If you are looking for explosive growth, then LTV is THE metric that you need to worry about. This will help you determine the cost per acquisition that you are willing to pay. In the example above, they realized that if they set their break-even point per customer at 3 months rather than immediate, they were able to pay 30% more per acquisition, which allowed them to jump from making 15 sales per day to making 300-400 sales per day.

By drilling into the numbers and truly understanding the value of their customers over time, their sales were able to increase by 2500%! When you view the true value of a customer over time, you can make decisions like this that help you to experience explosive growth as a company.

How do you maximize returns based off customer LTV?

The best way to maximize your returns is to get extremely granular with your data. Go beyond just looking at the generic LTV of all customers, and see the LTV of customers based off of their referral source, or check to see what other products they purchase after the initial purchase. The more that you can break down the data and individualize your targeting, the more you can glean insights into your consumers, and in turn maximize your returns.

What is the best way to track LTV?

This is the question that you really need to answer for your business. You need to determine how you want to define and track the value of your customers over time. This will be contingent on the systems that you are using, the types of products that you sell, and how you want to think about your products.

Going back to the previous point about getting as granular as possible, you can break down the LTV of your clients based off what their initial purchase was, by referrer,

When should you make changes to your budget based off the LTV calculation?

Unfortunately, just like the last question, this depends on your business. If your company has a long buying cycle, you should probably wait to increase your budget until you see the results from your efforts. If you are able to make back your budget based off the initial purchase, you can increase your budget immediately. By understanding when people are able to hit that break-even point in your business, you can know exactly when you should increase your spend.

How can I set up tracking to make sure that I am getting good data?

You need to make sure that your attributions are set up properly in Google Analytics, so that you can break out customer behavior by traffic source in order to see exactly what your spend should be for each source. Past that, it is highly recommended that you break them out into funnels or campaigns that you are using so that you can properly attribute the LTV to each of the campaigns that you run, as well as the sources.

This requires a great deal of work up front, but once you lay the foundation of good data it is much easier to continue down that path, and you know that you can trust your data.

What is the number one thing that all marketers should know about the LTV of their customers?

The obvious first thing that you need is to know the number. If you are not conscious of the LTV of your customers, you need to find out what that is. After you are aware of the average LTV across the company, you need to get more granular with it, and drill down into the LTV per product.

Once you have those numbers, you need to determine your business goals. If you are in a growth stage of your business, where you are trying to scale, don’t be afraid to break even up front. Be aware of how long it will take for you to start profiting, and make sure that you are comfortable with waiting for that; but once you have determined that, you need to move forward. The business that can afford to spend the most to acquire the customer wins every time.

If you have any questions about dashboards, tracking, analytics, or if you want custom dashboards built for your business then talk to one of our data experts.

Data Analysis

Data-driven mistakes even good ecommerce business owners make (and how to avoid them).

Have you struggled with data discrepancies? Had a hard time figuring out what metrics you should actually track? Tried to use a dashboard service and hated it?

If any of those things apply to you, we feel your pain. This video helps to break down some of the most common mistakes that we have run into across the board with multiple ecommerce businesses, and how to avoid and fix them. If you don’t have the time to sit through the video, or don’t have headphones handy, never fear: we have provided a breakdown of the video below.

Mistake #1: Not automating data extraction

  • Most companies have a HUGE issue with this; they have someone assigned to extract data from multiple data aggregates and put it all together in one place.
  • This causes several problems for businesses, the first being the human error side of things; humans make mistakes constantly, and with a task like data aggregation it’s very easy to misplace a decimal point or to switch two numbers around, which may not seem like a huge deal, but if you take action on the insights gleaned from that data it can lead to catastrophe.
  • The second problem is that humans are expensive. Generally the person in charge of this kind of task is a marketer, and their time is much better spent analyzing data rather than aggregating it; marketers find actionable insights from the data, but very rarely do they have the necessary training to clean data and ensure its accuracy.

Mistake #2: Believing that a dashboard is the solution to your data problems

  • Dashboards are excellent tools for data visualization and data aggregation, but they will not solve any issues that you have with the underlying data.
  • The second issue that people often run into with dashboards is actually connecting the data from the various sources to the dashboard. Many of these data visualization companies talk about how easy their technology is to implement, but going back to the first point, you need to understand how to take all of the different data formats and naming conventions and standardize them across the board so that you can actually get actionable data that you can trust.

Mistake #3: Not making your data actionable

  • According to a Google survey 97% of websites collect data from their customers, but less than 30% actually use that data to make decisions in their business.
  • Many companies get so bogged down with metrics and get lost in the weeds of everything that is measured that they lose sight of their actual goals. It is best to narrow the view down to 7 or 8 actionable metrics  to focus on in the near term, i.e. increasing revenue or decreasing costs, and then once you have those under control, you can begin to add new metrics that you want to measure to further optimize the business.
  • The last part of making sure that your data is actionable is making sure that there is someone assigned to each of the core metrics that you decide to measure. That allows the person to focus on that metric, so they know exactly why that metric went up, down, or sideways, and can explain to the team exactly what happened so that you can replicate that behavior again or avoid it in the future.

Mistake #4: Not democratizing data

  • Many organizations have one nerd who analyzes all of the data and then transmits that data to the team, but that nerd doesn’t know what they don’t know. This flows back to the first mistake that many businesses make, by trusting too much in humans who are extremely prone to errors.
  • Everyone has different backgrounds and experience, so when they look at a metric they will see one thing and come up with an action item based off their experience; but if you bring in another set of eyes, that person may see something totally different and come to a different conclusion. Democratizing data and making it accessible to more people will lead to greater insights and more options for ways to proceed.

Mistake #5: Not focusing on the bottom line

  • This is very similar to not making data actionable, but it is very important to cover as well.
  • Determining the right metrics to measure for your business starts with your big goal: driving more revenue. You need to ask yourself, “what are the primary drivers of revenue for my company?”.
  • After you have determined what the primary revenue drivers are for your company, you need to ask the logical questions as to how you can get more from those customers; that may be, “how do I keep them subscribed to my service for longer?” or “How can I increase repeat purchases?” or even “How do I increase the average order size on my site?”.
  • For each of those questions, you can find one metric that will help you to measure the effectiveness of your efforts. By then focusing on that single metric to measure your results, you can experiment to find what works for your customers.

Mistake #6: Worrying about the chicken vs the egg

  • Many business owners think that they don’t need to start truly tracking these key metrics until they already have success to replicate; this could not be further from the truth.
  • Cleaning and tracking data, especially in the early stages, helps you avoid costly mistakes and also helps you expand rapidly. Businesses that track their data early on can outspend and outmaneuver their competition because they know exactly the type of returns to expect from their investment, allowing them to aggressively expand and claim market share.

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