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One of our clients is a leading ecommerce personalization platform that helps brands increase revenue through AI-powered merchandising, search, and customer experiences.
As the company grew, customer information became distributed across Salesforce, Intercom, BigQuery, and other business systems. While each platform contained valuable insights, teams lacked a unified view of customer health, making it difficult to identify risk before it affected renewals.
Like many growing SaaS companies, the company’s RevOps team spent significant time gathering customer information from multiple systems before they could answer even simple business questions.
Customer Success often investigated accounts only after problems had already surfaced, and different teams relied on different data sources to make decisions.
The team wanted to create a single trusted source of customer intelligence that would allow everyone—from RevOps to Customer Success—to work from the same view of the customer
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The company used Riley to connect customer information across Salesforce, Intercom, BigQuery, and other operational systems into a unified customer intelligence layer.
Rather than manually combining information from multiple platforms, teams could view a complete picture of every customer in one place.
Riley continuously monitored customer health and generated near real-time health scores, allowing Customer Success to quickly understand which accounts required attention and why.
One of the most valuable capabilities for the company was the ability to investigate customer health before churn occurred.
When customer health changed, Riley surfaced the supporting evidence behind the score, giving Customer Success immediate context about what had changed across customer interactions, CRM activity, and operational data.
Instead of spending time collecting information, teams could immediately focus on deciding the best next action.
For the company,, explainability was just as important as automation.
Rather than producing recommendations without context, Riley linked every analysis back to the underlying business evidence, allowing teams to understand exactly why an insight was generated.
Beyond customer health, Nicole saw opportunities to apply Riley across additional RevOps workflows, including revenue forecasting, pipeline reviews, opportunity analysis, and executive reporting.
As organizations continue adopting AI across revenue operations, she believes success depends on giving every team access to the same trusted business context.