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[VIDEO]- Master Cohort Analysis For Ecommerce with This Dashboard! - Data-Driven Decisions Made Easy

[Video Transcript]

What's up y'all! Today we're talking cohort analysis for your e-commerce company. Let's dive in!

I'm Jack Tompkins with Pineapple Consulting Firm and we are always trying to help the small business world become more data-driven. Today, the way we're doing that is with cohort analysis for small business e-commerce companies. So, knowing your customers better is always a good thing and helps your customers spend more with you, which is even better. It's a win-win! Not in a used car salesman sort of way, it's just giving them what they want when they want it. They buy more from you. They're happy with their purchase; win-win.

So one of the ways to do that is with cohort analysis. What the heck is that right? A cohort is just a group of customers and we group them together by something fixed. For example, their first purchase month, the first thing they bought, things like that, certain demographics about them, etc. It's something that's fixed about them that we can group customers together and see the classic, "you might also like" when you're shopping online. That is an example of cohort analysis because that type of person or type of shopper that buys that thing, might also buy something complimentary to it. That is a cohort.

How do we analyze them? Well, the analysis is just "how do they perform over time?" There are a bunch of different cuts of that but here are some examples of specific cohorts that you might want to analyze.

  1. If you're selling anything in the fitness or exercise world, January is probably going to be a big month. Maybe Black Friday is a big month too. People preparing for the new year, but a lot of people might give up in February. It's a classic New Year's resolution. So maybe you want to sell them a "stick with it" package in February or something like that.

  2. If you're doing a free trial for food or pet supplies or anything like that, how many people actually purchase the full price? The people that buy in January or June or whenever, do they act any differently? Does the type of food that they're buying matter? Do they buy something else?

Those are different cohorts. We start with the fixed thing; the first thing they bought or the first month they bought for example and then we analyze "what did they do after that". If we group those customers together, we get some really good insights into how our customer base is performing. Back to the original goal, we can sell them more of the stuff that they want and they spend more with us.

Okay, let's do a quick dashboard just so you can see a little bit of this visually. All right, here is our Google Looker Studio dashboard. Per usual, we love Google Looker Studio. It's totally free to use as long as you can get the data in here. There's a lot of good ways to do that. This example is with Shopify data but you could do this with Big Commerce, Amazon, a lot of different ones. That sort of engine is what's running this fake data that we've got here. I'm just going to get into presentation mode real quick.

So let's say that this is a company that is offering different food products. Let's say healthy food products and they're offering a free trial. You can see here we've got four options that are all in here. What we want them to do is purchase the free trial and then continue purchasing after that.

If we look at the top here, we see some overall metrics. It looks like about 20,000 or 21,000 people have purchased the free trial and we've still got 6,500 active people. So 31% have retained, which is probably pretty good. That's potentially 31% of people we wouldn't have gotten if we didn't offer a free trial. That could be verified with more analysis. Our goal here is to see who's performing best and which products are performing best.

For the who part, we're going to group them into months; their first purchase month. Are they still in the program and in the subscription today? That's what this graph shows. It looks like in July, there is a decent number of signups and most people stay for the month of July but it sort of dwindles over time naturally. But in this month four for example, we have the highest retention of anybody's month four. Then we really drop off in month five. So maybe something's happening there. There's some good Insight that we could probably draw from that. We could also see that at a product level and I'll go to the totals down here.

It looks like people start with vitamins more often than not and the retention is somewhat average, I would say, given the data that we're looking at here. Healthy snacks though; apparently people don't want to keep snacking, so retention is relatively low.

From all of this, you could filter and sort by any specific month or offering or anything along those lines and you could really dive into it. You could even go into a cohort of a cohort. So the specific vitamin, whether it's vitamin B versus vitamin C or something like that. You could go one layer deeper and see that extra level that might really help you hone in your analysis. Things like this really help for setting goals, setting expectations, actually measuring how everything's doing, and measuring the success of your offering.

I highly recommend putting it into a dashboard that is automated so you can see this at any time. The whole team will be on the same page, all that good stuff. Again Google Looker Studio is pretty easy to use and totally free to use as long as you can get the data in there as well.

There are a lot of benefits to it and it's the "you might also like" but not the used car salesman, "Hey please buy this", you know it's nothing like that. It's just giving them what they want when they want it by understanding them better.

There are vast benefits to being able to understand your customers better. Numbers-wise, you have a higher retention rate and people staying customers for longer. Whether it's a free trial or not, it is just people actually purchasing and repurchasing with you. Everybody loves that. It leads to a lower cost of acquisition, higher long-term value, and higher average order value. All of these things can be gained from a little bit of cohort analysis.

So do yourself a favor and grab a dashboard that automatically tracks this for you, helps you set goals for the team, and gets your customers to spend more with you. It'll be a win for you and it's a win for them as well. As long as you're tracking it, you can measure it.

Please reach out! We always love this stuff and we love the e-commerce space so we are more than happy to help with whatever you've got going on, especially in the cohort analysis sphere. Take care y'all!

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