Technology Company Improves Sales Forecasting by 500%

Challenge

A leading fintech company relied primarily on data from its CRM, Microsoft Dynamics, and Tableau dashboards to manage sales planning and forecasting.

Managers and salespeople maintained the quality of information in the CRM through the expansion of the company’s sales team and go-to-market engine from 2018, when the company created 20k opportunities, to 2020, when it created 175k.

In spite of this, they found that simply rolling up forecasts, activities, and opportunities into dashboards didn’t give management the intelligence it needed to plan and manage the business. In any given quarter, management’s forecast was off by 20% or more, which hurt the company’s ability to direct executive attention to the right accounts and to grow the sales team where required.

Solution

The company turned to C3 AI CRM to exchange spreadsheets and dashboards for a complete system of customer intelligence.

C3 AI CRM provides the company with a unified intelligence layer comprised of CRM and ERP data as well as data from external systems, including market data, financial filings, analyst reports, and news.

This data image gives salespeople complete context on all the internal and market factors influencing their accounts. It also feeds C3 AI CRM’s out-of-the-box feature store, which compiles millions of discrete data points into signals to be used in AI model training (e.g., an opportunity’s progression through sales stages over time, an account’s average email sentiment, or a customer’s rolling stock price).

Finally, AI insights help sales managers and professionals better manage the business. C3 AI CRM helps them produce a quarterly sales prediction, accurate to within 96% percent. The product also delivers advance notice on prime opportunities to be accelerated into the quarter and which should be pushed out.

Armed with these insights, the company is able effectively plan the business, spend more time on the right deals, and reliably grow revenue, quarter over quarter.

About

• $12B annual revenue
• 3,500 sellers
• 175K+ opportunities per year

Objectives

• Improve quarterly revenue forecasts
• Identify both at-risk deals and opportunities that can be accelerated into the current quarter
• Prove the viability of AI as a technology for helping sales managers and representatives to plan and execute more efficiently

Highlights

• 4 weeks to integrate data, tune ML models, configure UI
• AI evidence package accompanying every AI score to help sales professionals identify factors accelerating or hindering progress in their accounts
• Integrated internal & exogenous datasets (CRM, ERP, macroeconomic, firmographic, other exogenous)
• 6 years of deal history analyzed for model training
• 1,000+ out-of-the-box signals tested during AI training, with 230 prioritized for use in production AI model
• Comprehensive evidence package for every AI forecast & opportunity score