Create meaningful customer groups for more relevant interactions
What a group of customers has in common isn’t always obvious. Certainly, there are better ways to find commonalities than simply grouping by age, gender, income and geography – or even recency, frequency and monetary value (RFM). Data science can help by digging deep into all your data to find hidden insights and patterns that create truly meaningful customer segments. Then you can align everything from marketing to product development to customer service to these segments, ensuring every interaction is relevant and engaging.
Know your customers and prospects
Understand what characteristics really matter when it comes to segmenting customers into meaningful groups. Get beyond mere demographics and RFM to find deeper insights.
Tailor each interaction
Use segmentation to ensure every communication, be it through sales, marketing, customer service, is structured to meet the unique needs of that customer’s segment.
Discover new opportunities
Get beyond a single view of your customer base to see the nuances between each individual segment, and the opportunities they represent – for new products or marketing strategies.
Design better products
Determine not just how to communicate to each segment, but what they each want out of your products. Use these insights to improve product design, and sales results.
Customer Segmentation Use Cases
“The seamless integration of RapidMiner’s lightning fast data science platform and QlikView’s strong visualization capabilities provides a Customer Segmentation solution to drive revenue optimization.”
