Adapt The Solution & Play With Your Own Data
The flow can be easily adapted with on-demand customization services to allow you to upload your own transactional data and rebuild the flow based on your goals.
Explore !The goal of this adapt and apply solution is to show retail organizations how Dataiku can be used to predict the customer lifetime value (CLV) of customers in order to optimize marketing spending and customer acquisition costs with a variety of predictive approaches. More details on the specifics of the solution can be found on the knowledge base. This solution is available on installed instances and Dataiku Online.
Business Overview
Efficiently managing an existing customer base is critical: acquiring new clients costs 5x more than retaining existing ones, and well designed customer lifetime value (CLV) supported strategies enable to deliver up to +30% life in sales. It is thus essential for retail brands to well understand their customer base across different dimensions and potential so as to answer the following strategic question: which customers should I invest into?
To do so, brands need to identify who their most valuable customers are, what their potential future spendings amount to, and how to engage with them. In other words, the ability to estimate current and future customer value is a huge opportunity to optimize marketing spendings and build long-lasting relationships with valuable customers. Combining different approaches and leveraging RFM analysis gives new opportunities to brands to make refined strategic choices in their sales and marketing programs.
Highlights
- Input transactional data to analyze your customer base distribution through a RFM* analysis.
- Build an RFM-based customer segmentation.
- Compute RFM-enriched Customer Lifetime Value for your customers and tier them accordingly: high, medium and low
- Predict the future lifetime value of your customers across different dimensions
- Identify products attracting the highest predicted CLV customers
- Visualize outputs and embed RFM-enhanced CLV in your marketing and sales processes
*RFM: stands for “Recency, Frequency, Monetary value” is a marketing metric used to identify the value customers are worth to a company.
Solution available on Dataiku Online
Data Driven Insights
A ready-made project with clear flow zones turns transactional data into actionable insights about the current and future value of your individual customers so that you can optimize your customer engagement strategy.
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Understand your CLV and RFM distribution
Get a quick and shareable view of your existing customer lifetime value as well as the RFM distribution.
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Predict the future CLV and better spend your marketing budgets
Predict the future customer lifetime value by using several different approaches that can be chosen between to best fit customer data and needs.
Analyze the CLV of your top ranked customers and compare it to other quartiles.
Go further: enrich with product data
Input product data (id, description) and run product analytics to get additional insights regarding product preferences of your highest value customers.
Explore !