Everything you wanted to understand and learn about customer lifecycle (and didn't dare asking).
In this current guide, we'll guide you step by step through the main concepts of customer lifecycle and how you can implement concrete and immediate actions to activate, engage and prevent from churning your customer database.
Marketing lifecycle is critical to get the highest ROI from your customer database and make sure you get a sound customer database: let's start!
What is an active customer?
Active customers are defined as customers who made a least x purchases over the past T months.
The time lenght is up to each industry: you might not purchase every year a sewing machine but you'll purchase at your local supermarket at least every week.
The supermarket can definie you has active customer if you made a purchase at least over the last 3 months, given the nature of the business, over this delay you might counted as a churned customer.
Why keeping track of active customers?
Active customers will tell you about the quality of your product and service. If you see less customer signing-up, less adopting and more and more churning, you'll know that you'll need to do something.
Active customers also help breaking even faster and get a better a better ROI of your plateform.
Wait, the customer signed-up but didn't activate?
The difference between a customer sign-up and a customer activation is the next step if you want to understand to grow your business.
Not all the customers who sign-up to your website will activate.
What is activation should be defined by every company.
Most of the time however, a customer would be "activated" when he/she makes her first successful transaction on your website. The first successful product or service purchase is generally a milestones in the customer relationship. It's the very first moment the customer will experience your product and the service which goes with it.
This definition of customer activation can change: if you implement a new social network, when would you consider a customer as activated? When the profile has been updated at 80% and more? Would a customer be activated after his / her first post?
Customer adoption: the journey to customer adoption
Once you have your customer activated, the next question will be: was it a one shot or is the customer starting to adopt your product or service?
Typically Facebook would define user adoption according to the following criterias: a customer must have added x friends, uploaded a picture profile, posted 2 messages or shared some links within the first 2 or 3 months.
This golden path to product or service adoption is the output of analysis: all the customers who in the future adopted the platform actually showed these characterics and behaviour after their activation.
In other words: adoption path can be defined with data and facts as soon as you have enough data to calculate it.
You would need to take a cohort of your most engaged customers and look back in the past to make the main behaviour which would be likely to have predicted this high engagement level.
Once customer adoption has been defined with data points and analysis, the product and UI teams will influence the wished behaviour to drive adoption.
Emails will be pushed encouraging you to complete your profile. Notifications will pop up making sure you'll add some of your friends. Small messages will appear explaining you how to use the platform features.
You can find more information about customer adoption here.
Defining the levels of customer engagement
Ok, great, your customer has been activated, adopted your product or service and now?
Well, if having an active customer is great, having a customer who is engaged with your brand is better. Repeat purchase will mechanically lower your average customer acquisition cost.
You'll seek to build products and solutions tailor made for the personas (or target group) so that their need will be statisfied by what you have to offer them.
Engagement can be defined in many ways and the best way to do it is to analyze your data and segmenting your customer base accordingly in the first step toward success. Data science and statistics can help you figuring out what would be the typical profiles.
When a customer will churn or is about to churn - and how to prevent churn?
This question about customer churn can actually be flipped : Is there a way to predict which are my customers most likely to purchase in the next few days or weeks? We have a small but useful feature to predict when a customer will be likely to make a purchase next.