Cohort analysis in ecommerce may not be the first thing you think about in the morning, but it may very well be the key to providing premium customer experience.
In this article you’ll discover:
A quick refresher
Cohort analysis is looking at the behavior of a customer group, sharing a common trait, over time – how often the shop from your store, what they buy and so on
This analysis shows how people who became your customers at the same time, buying the same product, or using the same coupon, engage with your ecommerce store until they no longer do.
It’s a solid ground for comparing different customer groups because different stimuli attract various kinds of shoppers and you see how differently they interact with your store over time.
For example, maybe your deep discount coupons don’t attract loyal customer but only one-timers.
Or you get lots and lots of holiday shoppers who never come back.
Those are just two of the opportunities for engagement and extra sales you discover when doing cohort analysis.
I know it’s not the friendliest of reports, but it’s not that bad, I promise.
Usually, it puts together a timeline and the cohort behavior to show how this behavior goes on over time.
In the example below you see in which week after the first order people from that cohort place their second, third and so on order. Week 13 is great for 4th orders!
For a business with healthy retention, every cohort can look like the one above – returning customers coming to buy again and again.
When a cohort is not a good fit, though, those people don’t come back for many repeat orders.
In this case, you should work harder on engaging and keeping your customers after the first sale. Use customer feedback to find out why they don’t like your store.
Because it helps you get profitable after spending to acquire a customer. If you get a few orders from them, it offsets the CAC.
The higher your LTV, the more stable your business is because you’ll still be in the game tomorrow if you don’t get new customers. Returning customers keep things going.
Related: Retention marketing in ecommerce
Let’s dive in!
Here are some real-life ecommerce cases when cohort analysis uncovers potential for more sales.
You know email is the best for driving engagement and repeat orders. It’s a free form of marketing, it’s very much personal (not public communication), customizable and can be automated.
But when is the best time to send those emails so you’re not spamming and annoying your contacts while getting the maximum ROI?
With cohort analysis, you’ll see what’s the average time between orders for your business. It’s surprising how what we expect that period to be for a certain product and what it really is.
We have a client selling roasted coffee who was very thrilled to discover with Metrilo’s retention analysis that his time between orders is 23 days instead of 45 as he thought!
So, how do you use that info?
When you know people usually buy every 23 days, you can make them buy more often, sending offers every 21 days, for example.
They’re about to be ready to buy again anyway so your offer is well-timed and welcome. At the same time, it speeds up the buying cycle by 2 days, which means more orders every month!
On the other hand, if some people don’t place an order by the 23rd-day mark, you can proactively win them back and avoid losing them with another engaging email.
Time between orders is an eye-opening metric in the cohort analysis – without it, you’d be waiting passively for customers to come back or spamming them at times when they don’t need your product.
You may be wondering if it’s worth it keeping all your products or you can get away with some of them.
True, there are products that you just don’t need. Cohort analysis shows you if some items get you only one-time buyers, which causes more harm than good.
Why? Most ecom business lose money on the first order so only returning buyers actually make you money.
More on revenue vs profit in ecommerce
Other products create loyalty in customers (see above).
For some reason (that you can uncover by asking directly), those products hook people on your brand and shop. The cohort whose first purchase is this product would be strong, regularly shopping, with high LTV.
These are the products you need to push hard – on your home page, featured in ads, in your emails – to get more and more people to fall in love with them and become your regulars.
We explain the Superstar Product Technique in detail here.
When doing your cohort analysis by first product ordered, you might find that one category consistently outperforms the others, e.g. your men’s T-shirts get much more loyal crowd (cohort) than your women’s.
You can act on this insight in two ways:
It looks like everybody is doing some sort of a loyalty program these days. However, you can be doing well without one.
A cohort analysis shows how spending and AOV change over time.
If you get the same size orders regularly and AOV doesn’t go down, you’re fine. It means repeat sales are stable, you’re not losing those customers and their interest.
If those numbers go bad, though, you can add an incentive to stimulate larger orders.
This means people test you with their first order and you gradually manage to earn their trust, which leads to larger orders.
Then, you can do something about the first order: set a free shipping threshold, present yourself and your brand better, add more details about your higher-priced items compared to the lower-priced ones, put more social proof (user-generated content) on your site.
This will put your shoppers more at ease from the start and your relationship will start off stronger.
First, of course, compare promotions and campaigns by conversions and revenue. Then – see if they got you loyal customers.
Again, as you expect – cohort analysis will help.
The different kinds of promo offers attract different people and some are a better fit for your business than others.
Percentage off, money value off, new in, special, personalized, win back, abandoned cart promo codes all work for different people and it’s important to find out what gets you repeat sales.
Look at the cohort of each coupon code to see if it works for you long-term (getting returning customers) or only short-term (didn’t get repeat orders).
You see them in your cohort report – seasonal customers, shopping only around the holidays, one time only.
So they liked you enough to get presents from you but not enough to come again? I know it sucks.
Well, I’d reach out to them for every holiday the following year to get them buy gifts again. I’ll offer products related to what they bought to give them fresh ideas.
I’ll also ask for their feedback – if they can’t do it, they can at least forward my request to the real user of the product and I might get new leads.
Convinced you need to do cohort analysis for your store?
Metrilo can help
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