A large US Enterprise struggled with customer profile matching, unification, and segmentation. They partnered with Exavalu for expert consultation and implementation services.
01
Consultation
02
Implementation
The client was struggling to execute their operational workflows efficiently due to their outdated system which had its own set of limitations. They wanted to improve their customer matching beyond current MDM capabilities using advanced matchlogic and cut short the tedious manual effort spent on customer unification and correcting over-merge scenarios. Most importantly, they were keen to utilize history to predict and segment likely customers and generate timely and personalized Asks for episodic events.
We collaborated with our client to implement a Salesforce Data Cloud solution and address their system limitations. We conducted deep data profiling to tailor unification and predictive models, while standardizing and cleansing data to boost fuzzy match accuracy.
The next thing we did was generate predictive customer propensity scores to facilitate customer segmentation. We seamlessly integrated Data Cloud with Teradata and Salesforce CRM via MuleSoft and enabled real-time data flow across core fundraising systems.
We automated Salesforce Ask creation to update customer propensity scores.
