- What is cohort analysis? (A jargon-free, straightforward description)
- How can ecommerce marketers use it?
- Eight exemplary (ecommerce marketing) questions it can answer
Coffee ready ☕ …? Let's begin.
Coffee ready ☕ …? Let's begin.
Two of the most common questions I get asked by online retailers I work with are:
“What customer metrics should I be tracking?”
“Which ones should I be looking to influence?”
Typically most ecommerce managers and digital marketing managers will be tracking top line metrics like revenue per marketing channel and conversion rate, but it is surprising that the ones who are tracking metrics such as repeat rate, new customer revenue and time to second purchase are still in a minority.
These are all crucial metrics to be looking at, and if you can optimise them the long term health of your business can be greatly enhanced.
So let’s break them down.
Dividing the total costs associated with acquisition by total new customers, within a specific time period
Do not get this metric confused with cost per action (CPA), as there is a strong distinction between the two. In ecommerce, cost per action is typically the amount you pay to convert a customer (i.e. to make a sale), but this relates to both new and returning customers.
CAC is all about acquiring new customers. See how even Google refers to CPA as ‘the cost you are willing to pay to make a conversion’ NOT to acquire a new customer.
We all stumble through life clutching onto the fuzzy memories of those pesky Pythagoras and algebraic theorems that haunted many a youth, and—with rare use cases in present day life—they normally end up getting filed and forgotten.
Enter customer lifetime value: the only equation you need to remember.
In ecommerce, CLV is the value a customer contributes to your business over their entire lifetime at your company.
The main methods of calculating CLV are split between historic and predictive CLV:
Historic CLV (Good indication of CLV)
Simply the sum of the gross profit from all historic purchases for an individual customer.
Predictive CLV (Great indication of CLV)
A predictive analysis of previous transaction history and various behavioural indicators which forecasts the lifetime value of an individual. As long as the equation is accurate, this value will become more accurate with every purchase and interaction.
This blog post accompanies our latest ebook: 15 A/B testing ideas for ecommerce email marketers. Click here to download.
It’s 2017, and the days of low-quality, irrelevant marketing messages are well and truly over; if your email doesn’t seem interesting to a recipient, it will be deleted, unsubscribed from or - dare we say it - marked as spam (😧 ).
As a result, it’s critical that your email marketing is crafted in such a way that it actually resonates with your subscriber list on a personal level.
The only way to know how your email marketing is *really* performing right now is to look at the numbers. The numbers don’t lie. If they are good, that’s great, but if they’re not so good, changes are probably needed (for some context, the average open rate for ecommerce email is 16.75% and the average click rate is 2.32%).
Fortunately, A/B testing can help you go about making those changes.