It can seem like there are a million and one e-commerce analytics tools available on the market, all vying for your time, money, and attention. While they all set out to do more or less the same thing, they do so in very different ways.
Rather than provide a list of reviews or affiliate marketing links to different pieces of software, we’ll describe the characteristics of e-commerce analytics tools that you’ll want to keep in mind when you’re making your decision. We’ll then talk about just a handful of the most popular options that are available today and for whom they’re most suitable.
E-commerce Analytics Characteristics
There are uncountable flavors of e-commerce analytics tools out there, and each one has a different set of characteristics. These are many of them.
Ideal Business Size
E-commerce businesses benefit from different analytics packages depending on their size. Small e-commerce businesses may choose to use the most simple features of Google Analytics. After all, there’s no up-front cost and the courses to learn the platform are free.
Medium-sized e-commerce firms may wish to employ reasonably priced third-party software that provides simplified or additional functionality over and above what Google Analytics offers. Software like Metrilo (discussed below) or Crazy Egg might be attractive for this sort of company.
Large e-commerce companies will often go with a full-featured e-commerce analytics suite, like Adobe Marketing Cloud or Google Analytics 360. These teams need the power and versatility of high-end software and have the money to hire people with the expertise to operate them.
Most e-commerce businesses will have multiple sources of data on which they rely. They could be pulling in information from their web host, their digital marketing platforms (like Facebook and Twitter), and offline sources (like phone numbers).
Good e-commerce analytics tools will aggregate this data and bring it all into a single, convenient location. Not only does having the data in one place make for easier data management, but it’s also usually the only way you can perform any meaningful analysis on that data.
E-commerce analytics tools perform varying amounts and types of data analysis. While most tools will provide at least some off-the-shelf KPIs and metrics, the best ones allow you to perform free-form data analysis.
Free-form data analysis allows for the dynamic combination of disparate forms of data to reveal unique insights, correlations, and effects. For example, a tool like Adobe Marketing Cloud would allow you to overlay your digital ads with regional monthly sales data in order to discover a correlation between ad spend and sale.
Another popular feature of modern e-commerce analytics tools is person- or customer-level analytics. Rather than aggregating all of your customers into a single pool for the purpose of high-level analyses, a customer-level analysis considers the chronological history of a particular person as they moved through (or didn’t move through) the customer journey.
Most modern e-commerce analytics will conduct this sort of analysis, and it’s extremely useful to help make marketing and operations decisions.
E-commerce analytics tools are only valuable if they can present their data in a way that makes sense to you. Also called data presentation, data visualization translates the numbers into graphs, charts, and graphics that you can easily understand.
Most people can’t look at a table full of metrics and immediately tease out the patterns and correlations that make data analysis meaningful. However, most people can take one look at a well-constructed bar chart and understand the story it tells.
It’s important not to confuse data visualization with data explanation (discussed below). Just because your e-commerce analytics platform sets out your data in a pretty chart or graph doesn’t mean that there’s necessarily a pattern to the numbers. In other words, the mere fact that you can create a table or chart for a specific set of data doesn’t mean that you’ll be able to glean valuable insight from that data.
As we mentioned in a previous article, e-commerce analytics are only helpful if you can put the information you get from them to good use. This requires you to have some knowledge of statistics and data. Correlations that seem obvious from a single bar chart might actually show nothing but statistical noise.
Good e-commerce analytics tools will assist and explain the conclusions you can safely draw from the data they illustrate. These tools will be careful to point out if your sample size is too small to draw reliable conclusions or if there are outlying data points with a significant impact on a data set’s statistical features.
Artificial Intelligence (AI)
Artificial intelligence is a nebulous term. Depending on who’s using it, and in what context, it can mean everything from predictive analytics to machine learning.
The implementation of AI by e-commerce analytics tools differs from product to product. Some incorporate predictive elements, like estimating your expected sales for the coming month. Others take a more prescriptive approach, suggesting that you buy a particular digital ad in a particular market in order to boost revenue.
AI doesn’t replace human analysis. Instead, well-placed AI can supplement and support people who analyze e-commerce analytics. It can make their jobs easier and reveal potential decisions that may have initially escaped their notice.
Some e-commerce analytics tools will go as far as actually integrating with your e-commerce stack and making decisions based on actionable data. For example, the software might monitor a Facebook Ad A/B test and, once it has enough information, prioritize the winning ad for a future buy.
Some people are uncomfortable with this level of automation. They prefer to pull the trigger on these sorts of decisions themselves. Unfortunately, the additional time that a human being takes to make a choice may militate in favor of having the software make the call.
Example #1: Google Analytics
While a fuller analysis of Google Analytics will appear in a future blog in just a few weeks’ time, no summary of e-commerce analytics tools would be complete without at least a mention of Google Analytics.
Google Analytics forms the core of most sites’ approach to analytics. It’s customization options range far and wide, allowing you to segment your audience by virtually any conceivable metric. You could, for example, find out how long Safari users from Belgium who access your site on a mobile device spend on your website. You could discover how many visits you get from South African desktop computers on Saturdays.
Of course, all this power and customizability comes at a cost. Like many analytics platforms, Google Analytics can be difficult to learn and even harder to master. While the interface is intuitive and user-friendly, the sheer number of dashboard options can be overwhelming to new users.
Google does everything in its power to make things easier though. It offers free online courses in its Analytics Academy for users of different skill levels, including absolute newbies. Thanks to the popularity of the platform, countless other online learning platforms offer courses in Google Analytics as well. So if you want to learn more, the resources are available wherever you might look.
Example #2: Metrilo
For small- to medium-sized e-commerce outfits that seek a user-friendly analytics solution, Metrilo might be a suitable option. In a design decision similar to the one made by other e-commerce analytics platforms (Crazy Egg, Hotjar, etc.), Metrilo leans toward simplicity rather than power.
Metrilo’s ideal user is one who is turned off by the panoply of options in the Google Analytics toolbox and wants a more manageable kit. For these users, less is more.
Of course, Metrilo offers all the usual bells-and-whistles of modern analytics software, including:
- Customer-level analytics
- Automated email marketing
- Web traffic and product performance reporting
There’s a significant cost involved if you wish to use Metrilo past the free trial, so be prepared to hand over your credit card number. But if the thought of Google Analytics has you quaking in your boots and you want something a little simpler, Metrilo (or similar software) might be for you.
E-commerce reporting tools don’t come in one-size-fits-all packages. What you need for your business will depend on its size, your data science knowledge and capabilities, as well as your budget. Your purpose in getting an analytics platform will matter as well.
Yes, it’s likely true that you want to grow sales and revenue, but you presumably have other intentions as well. Perhaps you wish to increase your average customer lifetime value. Or maybe you want to grow your business in a particular region.
Whatever the case may be for you, you’ll need e-commerce analytics tools that can capture, analyze, visualize, and explain data in ways that help you achieve your goals.