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Smart CRM Basics: Customer Behavior Modeling

Watch: 4 steps to approaching customer behavior modeling

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Many would agree with us when we say that it’s actually quite challenging to build a good customer behavior model. The mathematical techniques required are complex and risky. And the smart and experienced customer analytics expert – who will know how to do it – is expensive and hard to find.  

Even once your customer behavior model has been built, it’s not easy to manipulate it for the purpose of the marketer. Most customer behavior models ignore many pertinent factors so that the predictions they generate are not very reliable, too. 

As a CRM marketer, that means it’s hard to determine exactly what marketing actions to take for each customer or group of customers. 

So, what do you do? Watch the 5-minute video or read the transcript below it:

Download this free eBook guide to building your customer model

4-Step Approach to Customer Behavior Modeling 

  1. Daily single customer view 

First of all, you need to start with a single customer view to derive accurate and actionable customer intelligence from your company’s data. Therefore, you need to take all your customer data and aggregate, clean, and synchronize it into one flat table. 

  1. Lifecycle stage-based segmentation 

The next step is to segment customers into small groups and address individual customers based on actual behaviors. This allows you to define the different lifecycle stages of your customers and understand their relationship with your brand. 

  1. Cluster analysis-based segmentation  

Then you move forward to a more granular level of segmentation and further split and divide the lifecycle stages into micro-segments to discover distinct customer personas with the cluster analysis. In this step, you can track customer segments and how they move over time instead of just determining what segment a customer is in right now. 

  1. Predictive customer analysis 

The final step involves accurately predicting conversion, churn, and reactivation rates. Based on objective metrics, the predictive customer model allows you to know exactly what marketing actions to take for each customer at any given time to maximize their long-term value. 

By now, you surely understand why it is crucial for you to have a good customer behavior model in place for your brand to make correct future predictions.  

If you want to learn more about customer behavior modeling, feel free to Reach Out or visit the Optimove Learning Center.  

Don’t miss out on previous Smart CRM Basics:  

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Megane Morais

Megane Morais is a Data Scientist at Optimove. She holds a BSc in Economis and Statistics from France and a MSc in Organizational Behavior and Development (from Israel)