The challenge
Of 24,000 monthly leads, only 2,700 started an application and 400 finished. The sales team could work roughly 3,000 leads a month, not 10,000, and had no way to prioritize. Customer data sat unused across a risk engine, a servicing platform, and Salesforce.
What we did
- A dual-tier lead grade (fit) and lead score (progress) so reps work the highest-value candidates first
- A Data Cloud architecture and roadmap to unify 10 terabytes of data from the risk, servicing, and CRM systems
- Agentforce AI SDR agents to follow up, request missing information, and qualify leads before a human touch
- Financial-services best practices from a team that does the majority of its work in the industry
The results
The lender received a complete Data Cloud architecture and phased plan, a working lead-prioritization framework, and a scalable foundation to ground AI models in full customer context across finance, underwriting, collections, and sales.
We definitely see the potential, the benefit and… scalability is all we need and what we’re looking for here.
Client, Financial Services — Lending