An Introduction to Cohort Analysis for Ecommerce Businesses

Data Analytics

Intro to Cohort Analysis

Don’t worry, the term “cohort analysis” sounds a lot more buzzwordy and intimidating than the concept itself. As a B2B enterprise, there’s a good chance you already perform all sorts of handy data analyses to drive your decision-making, from predictive analytics to prescriptive analytics. Cohort analysis is another type of behavioral analytics that you can leverage to help along the Ecommerce decision-making process — and once you get to know it, it’s a form of analytics that you’ll likely want to take full advantage of.

What Is Cohort Analysis?

Compared to other types of analytics, cohort analysis takes a broader view; interestingly, it achieves this by breaking down huge swathes of data into narrower, more digestible parts. Rather than looking at collected data in a singular unit from a specific and singular point in time, this type of behavioral analytics takes all sorts of data from a given subset across a period of time and divides it into related groups for analysis. Each group is referred to as a “cohort,” hence the name.

In B2B Ecommerce, those data groups are typically related to customer behavior, and often span the life cycle of each customer that interacts with your business.

Cohort Analysis and Customer Segmentation

Cohort analysis shares a lot in common with customer segmentation, another type of useful decision-making analytics. While cohorts divide customers with all sorts of different qualities into groups largely based on time (or other objective factors, like the size of their business or what they purchase), customer segmentation divides customers into groups — or segments — based on similar characteristics that the customers share.

Writing for Salespanel, Marveta co-founder Yash Chawlani says, “Segmentation is the simpler one of the two, but cohort analysis, though relatively harder to perform, provides in-depth insight into business activities. While segmentation aids in executing better marketing functions, cohort analysis helps understand the outcomes and effectiveness of every marketing activity.”

How It Works

Performing cohort analysis is essentially a four-step process. First, of course, you’ll need to pull the raw data, which usually ends up in tables of customer records in formats such as MySQL or Microsoft Excel spreadsheets. Once you’ve got your raw data, you use common identifiers to divide that data into cohorts, or groups, then identify the lifecycle stage at which each event happened for each customer (this is usually a software-assisted process). Finally, after calculating an aggregation — such as an average or a sum — from across your cohorts, it’s useful to visualize the data via formats such as charts or line graphs for easier analysis.

When grouping, it’s important to know that common types of cohorts include:

  • Time-based cohorts or acquisition cohorts are data groups concerning when customers signed up for services or made purchases (purchase frequency)
  • Segment-based cohorts break customer data down into groups based on the types of products or service they purchase
  • Size-based cohorts categorize customers by the size of their company (small businesses, mid-sized businesses, for example)

How To Leverage Cohorts

Because cohort analysis provides data that is less prone to short-term influence, Appcues points out that it can be an effective tool for diagnosing highly specific problems or pain points in your sales funnel, from start to finish. And this makes it particularly advantageous for retention hacking or encouraging customers to stick around

Advantages of Cohort Analysis for Ecommerce Stores

At the end of the day, cohort analysis heightens your understanding of your customers’ life cycles across any given period of time. The insight into trends and patterns gleaned from this type of behavioral analysis often comes with a bevy of benefits, including: 

  • Providing a data-driven gauge for how effective certain marketing techniques or campaigns have been
  • Identifying common lifecycle points in which customers stop purchasing products, which can help you in turn identify the most effective times to offer buying incentives
  • Offering essential insight into churn rates by identifying exactly when customers churn out
  • Letting you know exactly where most of your biggest purchases come from, with the most consistency
  • Benchmarking of ongoing user engagement
  • Identifying “sticky features” in your B2B pipeline, or the features that encourage retention, based on behavioral cohorts

At Medium, Humanlytics CEO Bill Su says, “While slow, cohort analysis provides a much more complete look at your buyer journey, and it is incredibly helpful to help you design a campaign that not only sees results immediately, but also is sticky and creates long-term value.” 

Let Zoey Help

On the road to that long-term value, you may find analyzing the huge volumes of data that cohort analysis relies on can be a monumental task. That’s where Zoey comes in. Not only does Zoey emphasize data accessibility, making it easy to import and export all the data you’ll need across various critical business systems, its built-in customer segmentation features also help to kickstart the cohort analysis process — and that might just be the best retention hack of them all.

Try the Zoey platform for yourself today – just contact us to get started:

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Dan is a freelance lifestyle writer and co-owner of two small businesses who splits his time between Dallas and LA. Throughout the last decade-plus, he’s been fortunate to collaborate with business brands such as Office Depot, The Motley Fool, Chron, Fortune and more.

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