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

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 data mistakes that we run into with 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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