Template
E-Commerce Business Overview
Combine your Shopify, GA4, Google Ads, and Facebook data for insights across your business.
.svg)
Find out how cohort analysis can allow you to ascertain the real difference-makers in your business — be it a specific customer touchpoint or a timely marketing campaign.
Business growth can be summarized into two quintessential principles: understanding your target audience and playing by your strengths.
It's no secret that no two customers are alike, but they all share similarities indicative of their buying patterns. And when it comes to strategy, a lot of businesses make the mistake of constantly trying new things without doubling down on what already works.
Cohort analysis can help with both scenarios. It allows you to ascertain the real difference-makers in your business — be it a specific customer touchpoint or a timely marketing campaign.
Without further ado, let's talk about cohort analysis.
To understand cohort analysis, you must first know what the word "cohort" actually means.
In simple terms, a cohort is a group of users or customers that share similar characteristics.
For example, you can have a cohort of customers who signed up for your service during a promotion or a specific month. Or, it can be a group of customers who only bought once and never returned.
Now, in customer cohort analysis, you're basically looking into data collected for customer groups over time. You're also able to compare metrics between different cohorts and identify trends that may not be noticeable at first glance.
Tracking customer segments always sounds like a good idea. But why should you bother with cohort analysis exactly?
Here are some of the main reasons why it's important:
To help you understand how cohort analysis works, let's take a look at some examples:
Businesses can split their customer base into cohorts in line with their initial purchase size. This allows you to test parameters, like the likelihood of repeat purchases, based on previous transactions.
Size-based cohort analysis can also be used to identify trends or unveil underlying factors that contribute to purchase behavior.
For example:
Let's say your SaaS company offers two subscription plans: a "starter" plan and a "business" plan.
You noticed that customers on the starter plan have a much higher churn rate than your enterprise plan.
With this information, you can prioritize business plan subscribers — where the big money is — in your marketing. You may also look at other factors, like alternative plans from competitors and excessive feature limitations, that might influence your starter plan subscribers to stop doing business with you.
You can build cohorts based on customer interactions and behavior, like engaging on social media or downloading free resources.
Doing so should give you a clearer profile of who your most valuable customers truly are. Of course, it also allows you to make informed decisions on how and where to allocate your marketing efforts.
For example:
You may find that customers who shop for more expensive items in your online store also follow you on Instagram. As such, you can experiment with the following adjustments to your strategy:
Believe it or not, the time when customers transact with your business can affect their purchase behavior in the future. Time-based cohort analysis will help you determine whether this dynamic applies to your customers.
Time-based cohort analysis often uses months as the criteria for groups. Put simply, you'll have cohorts for customers who purchase in January, February, March, and so on.
For example:
Suppose your customers who bought in July have a much higher lifetime value than your customers from January.
Then, you remember that you revamped your online store interface in Q2.
Unfortunately, the customers who purchased prior never got to see your redesigned storefront. There are also probably a few things in the customers' previous experience that didn't gel with them, be it the high shipping costs or delayed deliveries.
Cohorts can also be grouped based on the type of product or service they purchased.
Naturally, these customers have different needs, objectives, and pain points. It shouldn't be surprising if these cohorts don't exhibit the same behavior and contribute the same business results down the stretch.
Performing segment-based cohort analysis will help you understand these nuances — leading to useful data-driven decisions in your marketing (and remarketing), product R&D, and customer service.
For example:
If your product has multiple versions at different price points, you can group your cohorts based on the version they bought. From there, you can start tracking and comparing metrics like Monthly Recurring Revenue (MRR), CLV, and Average Revenue Per User (ARPU).
Breaking down cohorts by segment also opens up the doors to further research, like customer profitability, customer retention analysis, and marketing mix modeling.
Ready to get your hands dirty with cohort analysis?
Cohort analysis is one of the most important data analysis techniques you should learn if you're looking for growth opportunities. But in order to do it properly, you'll need to use the right tools.
Below are some of the best cohort analysis tools in the market:
Polymer is a modern, all-in-one Business Intelligence (BI) solution that enables you to turn heaps of data into interactive visualizations — no technical data science skills required.
With the help of built-in data connectors, you can easily consolidate all your data from third-party tools and services like Shopify, Google Analytics, Facebook Ads, Zendesk, and more. This lets you see the whole picture regardless of wherever customers interact with your business.
Another note-worthy Polymer feature you should know about is the drag-and-drop dashboard builder. Just pick from the available data visualization types or use AI tools to instantly generate actionable insights.
Click here to try Polymer for free.
Google Analytics is a free, comprehensive website analytics tool with cohort analysis baked into the system.
Here's how it works: once you set up your Google Analytics dashboard, connect your website, and wait for the reports to be ready. The best part is, some reports already come with cohort analysis right out of the box.
Cohort analysis charts are also available in the user retention report. This allows you to analyze and compare retention or engagement patterns between customer cohorts.
Looker Studio is Google's entry into the self-service BI and data dashboarding niche.
Its biggest strength is the massive library of third-party data integrations, including Google products, advertising platforms, payment processors, and analytics tools. This gives you the advantage of being able to track customer behavior, churn, and retention across all channels without relying on code.
Just be mindful that it can be tricky to create cohort analysis charts with just the bare Looker Studio features. You can, however, acquire third-party templates that handle the configuration and structuring side of cohort analysis.
You can learn more about Looker Studio by looking at our feature comparison post: Looker Studio vs Polymer.
Tableau is among the top data visualization tools for businesses, and it's also equipped with everything you need to conduct cohort analysis.
The platform connects with plenty of third-party data sources like Google Analytics, Salesforce, Dropbox, and Amazon Redshift. Tableau also features flexible data visualization tools along with convenience features, like assistant workbook optimization and ready-to-use templates.
However, you do need a little bit of work to use Tableau for cohort analysis. More specifically, you need to manually define cohorts by setting calculations, like the number of customers within an acquisition period.
Userpilot is a product growth platform built around creating, tracking, and improving user experiences. If you're a SaaS company, it will help you analyze user behavior, track churn rate, and spot opportunities to increase retention through various analytics tools.
The cohort analysis tool, for example, allows you to define customer groups and build data visualizations through a user-friendly interface. You can also run A/B testing campaigns targeted at specific cohorts, which will allow you to turn user behavior insights into actionable plans faster.
Just remember that Userpilot's toolkit is designed specifically for SaaS companies. If you're in any other industry, like retail or home services, you're way better off using a more versatile data visualization platform like Polymer to jumpstart your cohort analysis.
Setting up a cohort analysis dashboard on Polymer requires some creativity.
There are plenty of ways to organize customer data based on acquisition time, size, behavior, and so on. You can use filters, create a pivot table, or slice your data through a spreadsheet tool and connect it to Polymer as a data source.
Another strategy is to create a heatmap, which color-codes data based on up to two parameters within a timeline.
Let's say you want to conduct a segment-based cohort analysis, which splits your customers according to the price points of their subscriptions.
Using a heatmap tool, your Y-Axis should reflect the price points, whereas the X-Axis can be the date.
Finally, choose a metric that you'd like to compare throughout your analysis. This can be behavior-based like churn rate, or revenue-focused, like sales.
Before we wrap up this post, remember that not all cohort analysis objectives can be accomplished using the same data visualization and analysis techniques.
The good news is Polymer allows you to combine multiple data sources and build multiple visualizations in the same dashboard. This, along with global filters and custom metrics, allow you breeze through the entire setup stage.
Don't forget Polymer's AI tools, which can instantly turn your data-related questions into readable visualizations in mere seconds.
There's so much more to learn from your data other than the nuances between your customer groups.
With Polymer, all you need to do is create an account (paid or free trial), connect your data source, and create a brand-new dashboard.
As soon as you land, you'll find AI-generated visualization suggestions that allow you to make sense of customer data — regardless of your data science background.
Of course, you can also build your own visualizations from scratch and learn as you go. With Polymer's AI features, drag-and-drop editor, and real-time previews, you're pretty much guaranteed to create an awesome cohort analysis board that will unlock your company's growth.
See for yourself how fast and easy it is to uncover profitable insights hidden in your data. Get started today, free for 7 days.
Try Polymer For Free
.svg)
.webp)
