Data strategy frameworks that you should be familiar with
Efficient and well-engineered customer segmentation makes it possible to better understand customer behavior and allows retailers to react quickly and more effectively
The challenge
Everyone knows that it is better for retailers to retain existing customers than to acquire new ones.
This is because repeat customers lead to a greater ROI and cost 5-25 times less, which means it is particularly important that retailers retain the right customers. This is why they closely monitor customer retention rates.
The problem is that this combines many different types of active customers into a single KPI. In order to effectively improve customer retention over the long term, companies need to understand active users as they flow through each phase of the customer lifecycle.
The solution
Automated processes allow merchants to segment those unique customers based on their purchase behavior. Through a variety of machine learning algorithms used for both online and offline payments, a variety of merchants are able to understand the entire consumer lifecycle. As a result, merchants can send relevant messages in the right place at the right time based on which stage the user is currently in.
Payment processing creates customer segments in a way that adapts to all types of merchants—from small to large companies. The definitions of the customer segments are not clear or fixed, as they are dependent on each retailer’s individual characteristics.
Active customers can be found in one of three different retention stages:
- New customers: Customers who have recently been acquired and have made at least one purchase from the stores.
- Loyal customers: Customers who have been consistently shopping at the stores for some time.
- Resurrected customers: Customers who once made active purchases from the stores, but then became inactive for a certain period of time and later became active again.
Inactive customers are segmented into churned customers and lost customers.Churned customers consist of two types:
- Churned customers consist of two types:
Quick-churn: Customers who were new customers and did not buy again.
Late-churn: Customers who were retained customers and did not make a purchase for a longer period of time - Lost customers: Customers who did not buy over a long period of time—and with a very low probability of buying again.
In addition to the number of customers in each segment, it is important to monitor transition trends. In this context, the following questions are extremely important:
- Was the company able to successfully resurrect quick-churn customers compared to the previous month?
- Have the most recent targeted marketing campaigns increased the company’s success in acquiring new customers?
The result
The targeted segmentation of financial data combines important information and data points in order to break down siloed data. As a result, merchants benefit from optimized customer identification across all their channels so that they can now focus on what is most important for their sustainable growth: the performance of their existing and resurrected customer base.
