Case Study: Lily AI achieves higher win rates, shorter sales cycles, and more accurate forecasts with People.ai

Lily AI Boosted Win Rates, Shortened Sales Cycles, and Achieved Forecast Accuracy in 180 Days with People.ai

Lily AI, an AI-driven organization that helps retailers connect shoppers with the right products, needed to scale its sales machine while standardizing a previously manual, inconsistent process. Before working with People.ai, the team relied on frequent pipeline reviews and seller updates, spent about 30 hours a week on them, and lacked a clear framework to qualify deals, improve pipeline hygiene, and forecast revenue accurately.

People.ai helped Lily AI implement standardized Opportunity Scorecards based on MEDDPICC, stage-gating, and Relationship Maps to improve deal qualification, multithreading, and sales visibility. As a result, Lily AI reduced its sales stages from 10 to 4, cut pipeline review time from 30 hours a week to a few hours, and saw improved forecast accuracy, shorter sales cycles, and higher win rates within just 120 days.

Lily AI

Julian Dimery

Sr. Director of Sales