Customer targeting through predictive models can boost the performance of your campaigns. Focusing effort and resources on customers with a higher propensity to buy can increase response rates and profits, but finding and reaching those customers is difficult.
Predictive models created with advanced statistical methods can identify customers with a higher propensity to buy (PtB). When applied to x-sell or up-sell campaigns these models can prioritize lead lists focusing company resources on the most valuable customers. By using the Net Lift (incremental response) approach we ensure customer targeting has a real impact and that the marketing budget is spent effectively.
- Increases response rates to both x-sell and up-sell campaigns
- Improves profitability of the of the organization and marketing actions
- Decreases customer fatigue and improves the customer experience by improving targeting and the offerings presented to the customer
- Frees channel capacity for more efficient use or for customer experience improvement
For statistical methods we follow the strong and proven CRISP-DM methodology. We focus on business goals, exploit available data sources, use advanced analytics, and bring deep industry and business knowledge to deliver comprehensive solutions suitable for your business.
48% increase in conversion rate Medium sized bank, CEE, 2014