Minimizing Risk During Onboarding with Enigma

Preflect is a leading AI-powered ad targeting and campaign management provider who regularly works with small ecommerce companies making between $0-1M a year in annual sales. In the past, Preflect used other data vendors like Clearbit and Storeleads to sort through inbound leads to minimize the risk of onboarding low-value clients.

Preflect's inbound leads come from a form on their website that companies can fill out to book a live demo of Preflect's product. While Preflect often works with small ecommerce businesses, they wanted to make sure that the small companies they worked with were established with sales. Stores that didn't, explained Preflect CEO and Founder Ian McCue, often "converted poorly, churned quickly, and posed chargeback and fraud risks."

Other data vendors weren't providing the timely and accurate data needed to establish if a company was a good long-term fit for Preflect. Instead, the company's sales team had to manually qualify leads via a time-consuming demo process, made even more costly by a 44% no-show rate from prospective leads who booked demos. Moreover, not all bad leads were stopped with this manual process, and these low-value customers chargebacked at a much higher rate. Losses had a material impact on Preflect's business: in the past one bad lead, for example, had cost Preflect up to $100,000.

Preflect wanted to see if Enigma's data could be used to qualify these leads before any sales touchpoint, in order to minimize the risk of losing time and money on bad customers.

By only pursuing inbound leads that had positive card revenue in Enigma data, Preflect's lead disqualification rate would increase from 18% to 60% with Enigma, or 3.3x more disqualified leads blocked.

Since implementing Enigma, Preflect has had much lower fraud rates among new customers and has had no large loss events like the $100,000 charge in the past. Moreover, the rise in sales efficiency led to a 30% increase in revenue for the company.