Cohort Analysis

For an eCommerce store to thrive in 2018, it’s important that you as the merchant are able to understand your customers as much as you can.

It’s basic math: The more you know about your customers, the more you can give them exactly what they want.

Naturally, all customers are different. Just because 2 people shop with you, that doesn’t mean that they both have the exact same needs. This means that you need to segment your customers so that you can start to tailor the shopping experience to individuals based on their individual needs. This makes the individual customer happier and more loyal, boosting your conversions and sales.

Cohort analysis allows you to do this, and it can become a key part of your analytics that still many eCommerce store owners overlook. Cohort analysis can deepen your understanding of your customers, thus giving you an advantage that could see you edge out the competition.

But what is it exactly and how can you use it? Let’s take a look.

Defining a Cohort

A cohort is a group of people who share a binding characteristic.

For example, people who follow the same political leader are cohorts.

Or, in eCommerce terms, customers born between 1990 and 1995 can be described as a cohort.

However, that measurement is a bit broad and simplistic. Instead, you’ll want to define a cohort a bit more specifically. Here are some examples:

  • People who signed up for a trial over the past month
  • People who entered your sales funnel via social media
  • People who made a first-time purchase based on a promotion you ran

Defining a Cohort Analysis

When you analyze a cohort, you’re performing a cohort analysis. The means breaking customers down into groups in order to establish patterns that will allow you to improve your marketing campaign.

First, you take the data, then you analyze it, and then you take action on it.

For example, let’s say that I have an opt-in page on my store’s website. I decide to group customers who opt into my email list into a cohort. I can then compare and contrast their behavior with customers who neglect to opt-in. What my cohort analysis might reveal is that customers who are on my list are spending far more money in my store than customers who aren’t opting in.

Moreover, my cohort analysis might also reveal that most customers who don’t opt-in to my email list are never seen again.

The action I will then take is to create a more compelling opt-in page that boosts the number of subscribers I get.

This is just one way that cohort analysis can be used, but there are many more:

Cohort analysis helps you to assess changes to your website

It’s very unlikely that a merchant will create the perfect website straight off the bat. What’s likelier is that we’ll create an online store, before modifying and optimizing it as we go along.

But how do you know what effects the changes have had on specific cohorts? Has it improved your conversions or worsened them?

In other words, which cohorts have responded better to your changes than others?

Cohort analysis lets you see what changes have worked with specific cohorts and what changes haven’t.

Cohort analysis helps you to asses the different stages in the customer lifecycle

When you don’t perform a cohort analysis, you’re essentially grouping everyone who ever visits your store into the same – very large – group. As a consequence, all your marketing campaigns will be the same for each customer, regardless of whether they have only just discovered your brand, or if they’ve already made 20 purchases from you.

To capture people’s attention in this frenetic digital world of ours, you need to tailor your marketing campaigns according to where they are at in the customer journey. Once you do this, you will start to see better results because your relationship with each customer will improve.

Cohort analysis helps you to assess online and offline preferences

Are there differences between an online and offline shopper? There can be.

For example, in a physical store, a salesperson can be of assistance to a shopper who needs help. In your online store, unless you have a live chat installed, you might be missing out on this high level of service that can improve sales.

On the other hand, the tangibility of products can boost sales offline, while personalization can do the same online.

Customer engagement across different platforms, as well as online vs offline, then, is affected by a variety of factors. To get a better idea of how these factors are influencing your customers, you can add a point of sales card reader to your store and then create a cohort around customers who shop online and those who shop offline. This will help you to see how effective (or ineffective) your efforts at customer engagement are, and what needs to change.

Cohort analysis boosts your content marketing campaign

Content marketing is of increasing importance in the eCommerce world. Content is what helps you make that all-important connection with your customers. It helps to build relationships, trust and so on.

Content can also boost your exposure when it’s shared. But why is content shared and who shares it?

To get a better understanding of this, you can use your analytics to discoverer who shares your content the most. Then, create a cohort before launching a campaign that encourages them to share your content even more.

Cohort analysis helps you to determine how effective promotional campaigns are

Let’s say that I decide to run a promotional campaign in order to improve customer loyalty. Customer loyalty is important as it’s far cheaper to retain existing customers than it is to keep acquiring new ones.

So I run my promo campaign and I stick anyone who made the first purchase with me on the back of that campaign into a cohort.

After 6 months, I track how much this group – on average – spent with me over those 6 months. Let’s imagine that their spending is consistent; there are no spikes and it hasn’t tailed off. Looks like I’ve now got some loyal customers.

I then compare this cohort with a cohort of customers who signed up before the promo campaign. Since this promo campaign was exclusive to customers, anyone who signed up for it beforehand didn’t have access to it.

I check their revenue over the next 6 months and find that it’s way down on the revenue generated by the first cohort. What I’ve discovered is that the promo campaign was a great way to boost customer loyalty.

Takeaway

All in all, cohort analysis can be key to your success as an eCommerce store merchant. Customers should be at the heart of everything you do, and the more you understand them, the better you can serve them.