Why Data Driven Decisions are Essential for Ecommerce Success.
Airline pilots and ecommerce business owners have much in common, both should make data driven decisions to perform their jobs. In both cases relying on instinct alone will eventually lead to disaster.
So what are the similarities between ecommerce data analytics, data interpretation and the Airline pilots equivalent?
Imagine you are flying today from San Francisco to New York. You see the pilot walking down the ramp, greeting his team and getting settled in his seat to begin the flight.
Imagine that he does not check his dashboard with the recommended speeds, he doesn’t check the flaps, doesn’t properly request takeoff and he doesn’t even check the weather.
He just gets in and starts the engine and takes off. Would you want to be on board?
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He figures that he just has a good gut feeling that this flight will go off without a hitch. “I’ve flown this plane so many times, I can do it with my eyes closed”, he tells himself.
You would probably have a reaction like this:
How could a professional do his job in such an amateurish way? How can he put himself and so many others in danger?
Truth is: Our imaginary pilot and the average online store owner have a lot in common.
While the pilot obviously has the incomparable factor of human lives in his care, he and the business owner both ignore vital data that definitely endanger their futures.
A true professional pilot checks all of the key data (KPIs), confirms his route multiple times, regularly takes countermeasures and more.
If something is wrong, he digs deep into his data and is able to quickly find a solution. He knows how important accurate data as it can be the difference between a timely, safe landing and a tragedy.
E-commerce businesses should be run with the same diligence. In the following article, you’ll learn all about how to run your online business like a true professional and what to lean on to ensure continuous success. Let’s jump in!
How to be a professional pilot of your own “plane”?
When it comes to data, there are two main activities you should spend your time on.
Activity #1: Periodical KPI checks
This means having the right “dashboard” to see if everything is going as planned, or if there’s something off. Periodical KPI checks work best when there’s some sort of schedule when you check your KPIs. Whether you feel that’s weekly, bi-weekly, or monthly, it’s important to know the time to have these KPI “sweeps” for maintenance.
Activity #2: Deep Issue Analysis
If your periodical KPI inspections show you have an issue somewhere, this is where the deep issue analysis comes in. This is when you dive deep into the data, attacking the root of the problem, and then take action. The Deep issue Analysis is all about understanding the “why” behind the issues.
How much time should I spend with data analysis?
Most business owners don’t know how much time to spend on certain tasks, so they either:
Waste lots of time collecting and analyzing useless data, or worse
Spend no time at all doing data analysis.
There are no fixed rules on how much time you should spend on doing data analysis. But as a rule of thumb we recommend the following:
Periodical KPI checks should be quick and easy, taking no more than a few minutes a day, 15 minutes a week, and 60 minutes a month.
On the other hand, Deep Analysis should be – as its name suggests – deep and thorough. It usually takes several hours, but can even take up to several days.
Because most businesses do not know this information, they end up spending too much time on vanity metrics and too little time digging into metrics that will actually move the needle.
Spending only 1 hour a month with analyzing your data, and still being able to make data-driven decisions is only possible if you have the right data at the right moment available.
But usually, there are a few problems with analytics, which makes data-driven decision making a pain in the a** for business owners. Let’s have a look at these problems, and what to do with them.
Difficulties of data-driven decision making
There are 3 main problems that cause eCommerce businesses to fail in data-driven decision-making:
1) Data is complex
Sometimes looking at data feels like torture. Sometimes, there’s just too much going on. Too many numbers, too many graphs, too many options. You know you need data but if you don’t know what to do with it, what purpose does it serve?
Most business owners get overwhelmed by just looking at the menu structure of Google Analytics. They often come to the conclusion that they need to spend all their time untangling complex data or very little time on it. Both are very wrong and destructive decisions.
2) Data is fragmented
Even though Google Analytics is a great tool, it gives partial data concerning onsite behavior. There are no data in Google Analytics about what happens before and after the customer visits your store. Sure, you can get this information from other tools but finding a synergy between various tools can be equally frustrating and time-consuming.
3) Data is out of context
“Okay, here are a bunch of numbers and percentages. Now, what do I do with them?”
If you’ve thought that before when looking at your dashboards, you’re not alone.
Most data and numbers are worthless without context. Percentages and numbers are valuable but cannot be translated into actionable insights without context.
How to solve these problems?
So how can you solve this data dilemma? Before you get into the solution, I want to make it clear that it won’t be easy but it’s certainly worth the trouble. Your business needs this data to be competitive and to thrive.
Here are the 3 steps you should follow to create a data-driven decision-making framework for your Shopify store:
1) Focus on the most important KPIs
Less is more. You have to decrease complexity. You have to choose a finite (and manageable) number of metrics, and stick with them. Here is our recommendation for the most important eCommerce metrics.
2) Make the important KPIs easily accessible
Have these metrics not only readily available on a whim but have them aggregated in a single – preferably visually pleasing – interface. Or even better: have them proactively delivered to you, in just the right rhythm. You should also make sure that your store uses tools that are aligned with your data approach like Gorgias Shopify live chat app that puts a heavy focus on data for your customer support team.
3) Put your numbers into context
There are so many ways to contextualize and understand data but most analytics tools don’t even have the option to do this. Most analytics tools are simply for reporting purposes and nothing more. While there’s nothing wrong with that, these tools exclude those who aren’t as numbers-savvy from properly using the power of data. Like I mentioned above, data is useless if you have no idea what to do with it.
Actionable Analytics for Shopify Stores
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Our goal at Conversific is to provide a central place to solve all these problems. Here’s the Conversific advantage:
Simplifying: We handpicked the most important metrics for an e-commerce store owner, and deliver them to you just when you need them.
Aggregating: We aggregate all your data sources into a simple platform, and make the necessary connections between these sources. We don’t collect more data, we feel you already have too much.
Contextualizing: Whenever we present a number to you, we ask: is it actionable? Is it clear what to do with them? If not, we don’t show it to you.
Want to see for yourself? Click here to try Conversific out, 100% free.