Operations & Development

Getting Started with E-commerce Data Analytics

Operations & Development
10 minutes

#1: Google Analytics

As a free service, Google Analytics should be the default for all internal web-based activity. GA allows you to track how many people are coming to your website, where they are coming from, and how long they are staying there. With a little digging, you can find out the demography of those coming to your site. Google Analytics has a simple integration with Shopify which I’ve allows you to quickly launch GA on your website.

Use case: Cross-reference Google Analytics page views data with Shopify units purchased data to understand the conversion ratio between page clicks and products purchased. You can get a nice quick ratio to let you understand what is converting and what is not (Product A sells 0.7 units for every page click but Product B only sells 0.12). Start by focusing on the best 5 conversion ratios (Why are they succeeding? Is it positioning on my site? Price point?). Next, take what you just learned and look at the 5 worst conversion ratios. What sticks out to you that may be the reason why those products aren’t being sold? Make calculated changes to the bottom 5 product ratios in order to increase their conversion.

I’ll do a step-by-step post explaining how to do this analysis in the future.

#2: Hotjar:

Hotjar is one of the most innovative technologies that I’ve seen come onto the scene in the last few years. Hotjar allows you to track how visitors interact on your site in both a macro and micro level (more on that later).

Personally, I use Hotjar consistently to see where customers are clicking on a website on a macro-level.

Use Case: One company I work with uses this information daily to rearrange the order of products on their website. Products that are “hot” stay near the top and products that are “cold” are shifted around or queued to be refreshed. Refreshing typically means that they are prioritized to have their product photos re-shot or the price of the product is discounted.

On a micro-level, Hotjar has a simple recording feature which allows you to watch actual sessions of customers interacting with your website (where the click, drag, pause, etc.). Although this data is a little more anecdotal than the click data, it can be useful to give another dimension to understanding how customers are interacting with your digital storefront.

#3 Luz:

Personal plug here, Luz is my company but I believe our data is revolutionary. The future is online and that fact has only been catalyzed by the pandemic. At Luz, we realized:

  1. All companies look forward in order to project product sales
  2. Most companies look backwards to understand how they’ve performed historically
  3. Almost no companies looks sideways (in a systematic fashion) to understand how they are doing in relation to others and what advantages they can gain from knowing the successes/failures of their competition


We view this as an oversight based on the thesis that E-commerce is interrelated, and, usually, a customer will either fulfill their need from Company A or Company B. The key component is understanding what customers are already buying and then you can make minor adjustments to tilt the scales in your favor.

Use case: A company we work with was monitoring a close competitor in the activewear industry. Out of nowhere, that competitor launched a brand new product line with 0 hype beforehand. They essentially were trying to pull the Taylor Swift album drop of activewear. Within a few days, it became clear that 2 of the styles were selling well and 3 were not.

Our client had been contemplating a new product style similar to one their competitor launched which flopped. As a result, they decided to scrap the new style and not invest the thousands it would have taken for design/production.

Next, our client bought the Ad space on Google Ads and Facebook for the names of the 2 top-selling products. These ads were relatively inexpensive due to the specificity of the terms. Almost immediately, we saw the sales of their competitor start to come down, after a week, they were down almost 75%. Through the use of data, our client won the day.

#4 SimilarWeb:

Just as Google Analytics is your de facto for internal website traffic, SimilarWeb should be your starting point for external website traffic and it’s relation to you. SimilarWeb allows you to benchmark your website performance, demography, and conversion to other sites similar to yours.


I’ve used SimilarWeb to understand how my Google Analytics data applies to others in my industry and find out who their algorithms think my competitors are. Often, the main visitors to my website are different than what I expected (Grandmas buying baby products for their grandchildren instead of strictly moms). This insight has been invaluable to market and structure my website accordingly.

Use Case: One company I worked with used SimilarWeb to realize that their average visitor was 10 years older than they thought. They made slight changes to the “feel” of their website to make it slightly more mature and increased sales by 16% and returning customers by 12%.

#5 Amazon’s Alexa Web Information Service (AWIS)

The most developer-friendly web data provider.

AWIS is great for those who are looking to automate their E-commerce data collection with APIs and at alow cost. AWIS’s most useful feature is their Alexa Ranking which is an estimate of website traffic to a website on any given day, and can even be broken apart by geography. They have a useful Chrome Extension too which gives you the Alexa ranking of every website for free (Note: my understanding is that’s how they get the estimate, they’ll track you through the chrome extension).

For example, the website in the world with the most Website traffic is Google so they are ranked #1. Allbirds.com at the time of writing has an Alexa ranking of #8,586. I’ve found a decent correlation between Alexa Ranking and online revenue. This gives you a quick insight into where you sit in relation to other companies. Check this statistic periodically to make sure you’re continuing to grow in relation to others.

If automation is your end all I’ll be doing a post here soon to explain how to make that happen using Python. I’ll be posting my code from a product we started working on to synthesize data from these sources but ultimately abandoned to fully embrace competitor data.


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