The Quantitative Persona™️ scoring service enables marketers to harness the full power of their assets: data, behavioral predictive models, and orchestration / delivery tools across consumer touchpoints. Rosemark’s approach leverages its proprietary AI/ML data modeling to convert a client’s strategic segmentation into a targeting algorithm, which is integrated via an API into the marketing automation stack. Rosemark’s QP™️ helps marketers target and personalize their brand marketing to drive materially higher penetration and share of requirements among the brand’s most valuable consumers.

Implementing QP™️ insights into the marketing process and the corresponding QP™️ machine learning based algorithms into the technology stack enables marketers to develop and execute a personalized customer management strategy based on the drivers of brand choice and category usage, which when tuned and optimized through testing over time, drive material improvements in loyalty and thereby Customer Lifetime Value (cLTV).

The QP™️ Personalization Method integrates and enhances the most common consumer insight frameworks such as customer journey and predictive behavioral modeling in service to making the marketing treatments more personally relevant.

The following diagram illustrates how combining QP™️ Clusters with customer journey and behavioral models provides more effective personal and relevant marketing treatments.