Predictive & Segmentation Models
Find the customers most worth investing in
Use machine learning on transaction and engagement data to turn “who should we talk to first?” into a measurable number.
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Pain points
Limited resources, decisions based on gut feel
Sales resources are limited, yet key accounts are identified by gut feel.
Existing models run in legacy environments and are hard to update or extend with new metrics.
Analysis results stay in reports and never reach the sales team.
How we do it
From model to daily use
Customer value segmentation
RFM segmentation with industry-specific custom metrics, such as enterprise-size flags and engagement frequency.
Cloud migration & auto-retraining
Move models to the cloud with automated retraining and monitoring.
Results on the front line
Results feed into BI reports or the AI assistant, so sales teams can use them without understanding the model.
Use cases
Common applications
Customers
High-value customer identification & churn alerts
Spot customers worth growing and those at risk, early.
Marketing
Audience segmentation & budget allocation
Tailor messaging and budget to each segment.
Operations
Demand & sales forecasting
Use historical data to forecast next-period demand—87.77% accuracy in our food retail case.
FAQ
FAQ
What is RFM segmentation?
Segmenting customers by Recency, Frequency and Monetary value, optionally adding industry-specific metrics such as an enterprise-size flag.
How much data do we need for predictions?
It depends on the prediction goal—usually a period of transaction or engagement records. We first assess whether the data is sufficient, then choose the modeling approach.
How can sales teams use the model results?
Results can flow into BI reports or the AI assistant, so sales can view segment lists directly or query them in natural language.
Explore next
Let staff query data directly
AI Assistant
Query data and documents in natural language, with cited sources.
Numbers don’t match and data is scattered
Data Platform
Organize your data into a single source of truth for the whole company.
See real results first
Case Studies
Anonymized cases from aviation, automotive, a foundation and food retail.
Try a customer segmentation on your data
Book a consultation and we’ll check whether your data is sufficient.