Loyalty has been disrupted
- Defection rates now exceed loyalty rates for most brands. In 2022, defection outran loyalty at 13 of 18 volume brands and 12 of 14 luxury brands.
- Inventory constraints, long order-to-delivery times and new in-vehicle technology are all driving brand switching.
- Traditional loyalty predictions are based on past purchase history, not on predictive customer behavior, and offer no qualitative insight to shape what you say to customers.
A prediction built on why customers stay
Strategic Vision applied machine learning to 2.6 million historical NVES surveys to find the answers that predict future loyalty or defection. Applied across the NVES population, the correlation between predicted loyalty and actual retention is .92.
That combines the deep qualitative understanding of what drives loyalty with the scale of large data sets. The projections carry relevant, differentiated messaging, and scale across your entire CRM database.
Four steps
- Identify the customers in your CRM database who are within 12 months of returning to market.
- Re-survey them with a custom qualitative survey built on the predictors of loyalty, at the corporate, make, model or trim level. We deliver it to the customer email addresses in your CRM.
- Score each customer Red (likely to defect), Yellow (on the bubble) or Green (loyal). AI modeling projects the scores across every customer returning to market, and prescribes the message for each group.
- Activate and optimize. Your marketing partners deliver the right message to the customers most at risk.
Lift is typically 10 to 20 percent of total retention spend.