CRM Hack: The Customer Churn Factor
Watch and learn how to use a simple, smart formula that could help you predict customer churn before it’s too late
The challenge of communicating with each customer at the right time is only getting harder. Your customers are constantly exposed to different messages from different brands and different products – all the time – and behavior quickly changes.
Marketers must find a way to break through that noise and leave customers with a message that they will actually act upon. That requires personalization – and perfect timing.
To find the most appropriate time to send a message to each customer and have that message be the most relevant one at that time – you need a robust yet simple and personalized way to engage with each customer in your database.
It’s especially true with customers who are at a higher risk of churn.
That’s why we created the Churn Factor formula. Watch the mini-workshop below, or read the transcript under it to learn more:
To start predicting churn, first, you must find the frequency of how much time elapses, on average, between two consecutive activities of a single customer using the following Optimove calculation:
There are many different methodologies to predict churn, but in many of them, we have to pay some price of personalization. The Churn Factor aims to solve that problem. Calculating customer’s individual Churn Factor can flag risk-of-churn customers based on their own personal activity frequency.
Two weeks have passed for both Customer A and Customer B since their last activity. However, Customer A purchases every month while Customer B purchases every week. The key difference between the two is their Churn Factor. Using Optimove’s calculation, you can see it is completely different:
From a churn perspective, it is clear that Customer B is more at risk of churn as they have missed their own purchasing cycle.
Though this is a fairly simple example, it illustrates nicely how simple it can be to predict and prevent churn by first figuring out who the customer is and then sending out the right campaign to prevent them from churning.
Using a customer’s personal frequency to understand when they are at risk of churn is a better methodology than setting a single, distinct threshold to the entire customer base.
Want to know more? Reach out to us:
Strategic Services Team: email@example.com
Sales Team: firstname.lastname@example.org
Don’t miss out on our previous CRM hacks from Optimove experts:
- Gmail’s Promotion Tab
- The “Power Measures” You Must Know
- How to Make Your Dashboard Insightful
- The Building Blocks of a CRM Strategy
- VIP Definition
- Campaign Prioritization
- Basic Segmentation to Personalization
- Going Beyond Personalization Tags
- Marketing Plan Objectives and Principles
- Using Realtime Marketing to Improve Conversion
- Monitoring the User’s Heartbeat
- The Hidden Data of Emails
- Customer Tier and RFM Segmentation
- Cross-Selling Between Platforms
- CRM Hack: Cross-Sell Principles
- Gamifying CRM Campaigns
- Measuring the Right KPIs
- Repurposing Content
- Marketing Campaign Optimization
- Lifecycle Based Campaigns
- Testing and Evaluating CRM Strategy