Fintech & Banking

Customer Segmentation

Customer segmentation, or the process of dividing customers into groups of people with similar characteristics, is important for any organization that hopes to communicate with and sell to their customers effectively.

Merely knowing what your customers are purchasing is not enough for a robust segmentation. Needless to say, the more data you have on your customers, the better you can segment them into correct groupings. Data inputs for these estimations typically require your customers’ personal data, some financial information, transaction data, network data, an in-depth understanding of their communications with your organization (channels, messaging) and their social media connections and activity.

Accurate customer segmentation requires reliable customer demographic data and transaction data to estimate how much a particular customer will be worth for your business, not only based on their purchasing estimation but also their influence over purchase decisions made by others.

Adastra’s Customer Segmentation Solutions

Adastra’s experts employ different data-driven segmentation solutions based on your specific business model. Some of our solutions include:

Customer Lifetime Value (CLV)

A customer’s lifetime value is an estimation of the net profit an organization can expect over the entire course of their relationship with a customer.

Adastra’s solution to accurately quantify Customer Lifetime Value takes into account different techniques to estimate the churn probability of a customer or the expected length of the relationship, variables that affect the customer’s purchasing behavior and probabilities of behavior change, and predicted profits that can be contributed by a customer under various purchasing behaviors.

This information can be valuable for businesses in making decisions on the investment that should be made to market to and retain a particular customer.

Net Promoter Score (NPS)

The Net Promoter Score is an index based on a 10-point scale that measures a customer’s willingness or likelihood to recommend your product or company to others. Customers falling in the 0-6 range are unlikely to promote you and are classified as detractors, while those in the 9-10 range are generally promoters. Your organization’s Net Promoter Score is the percentage difference between promoters and detractors for your products and company.

Adastra can help you apply this analysis for customer micro-segmentation in order to determine the rewards that should be associated with the different NPS classifications. We can further segment your 

customer data into those with a higher churn risk and those who can potentially, with well-planned rewards and engagement, be converted into promoters.

This solution can also determine optimal categories of individuals for targeted promotions, helping you optimize your marketing initiatives and investing resources where they are likely to generate the most profits in the long-term.

Recency, Frequency and Monetary (RFM) Segmentation

RFM segmentation is a data driven method for identifying different homogenous groups that can be targeted with a personalized marketing strategy. In this strategy, Recency, Frequency, and Monetary Metrics are scored on a scale of 1-5 to give you a better picture of your customer’s relationship with your organization.

Recency refers to the last time a product or service was purchased by a customer, with a score of 5 implying a purchase within the last month, 4 implying a purchase in the last quarter, 3 for a purchase in the quarter before and so on.

Frequency refers to how frequently a customer makes transactions with you, or the number of transactions completed within a period of time, or even average monthly purchases. Monetary implies the average transactional amount of the product or service used, or a sum total of all transaction amounts divided by the number of transactions. The score metrics for the frequency and monetary parameters vary based on industry and service segment.

The aggregate RFM score can either be an average of the three parameters or based on custom weightage for each metric. This model can help categorize your customers into different segments based on their value and engagement or nurturing needs.

Benefits of Customer Segmentation

Accurate customer segmentation can help your organization improve customer engagement by creating messages, products and offers that resonate with them. The narrower and more targeted your customer segments get, the more your organization’s scope for personalization increases. By catering to your customers’ specific needs and wants, you leave them feeling more satisfied after each interaction and this improves your organization’s customer retention rate.

From a financial perspective, segmentation-based targeting of marketing campaigns can save your organization a lot of money that would otherwise have been wasted on a broad-based campaign. Moreover, targeted campaigns have much higher conversion rates and can greatly improve your marketing return on investment (ROI).

Interested in data-driven customer segmentation solutions? Book a free consultation with our experts to learn more.

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