Customer story
The difference between $0
and $100k in revenue.
Preflect is an AI-powered ad targeting and campaign management provider working with small ecommerce companies making $0–1M a year. In that band, most data vendors can't tell an established business from a fraud risk. A single binary check against Enigma — any card revenue in the prior 12 months — raised Preflect's lead disqualification rate from 18% to 60%.
Enigma + Preflect — disqualifying bad leads before the first call
- Customer
- Preflect
- Industry
- AI ad targeting & campaign management
- Use case
- Inbound lead qualification & fraud screening
- Headline result
- 3.3x more bad leads blocked
3.3x
more bad leads disqualified — 18% to 60% disqualification rate
30%
increase in revenue from the rise in sales efficiency
$100,000
single-lead loss event, of a kind not repeated since
44%
no-show rate on booked demos before the change
Source: Minimizing Risk During Onboarding with Enigma, enigma.com
01
The challenge
Qualifying leads by running demos for people who don't show up.
Preflect's inbound leads come from a form on their website where companies book a live demo. Preflect often works with small ecommerce businesses, but wanted the ones it took on to have established sales. Stores that didn't, explained CEO and Founder Ian McCue, often “converted poorly and churned quickly.”
Vendors like Clearbit and Storeleads weren't providing data timely or accurate enough to establish whether an inbound lead was a good fit. So the sales team qualified leads manually, through demos — a slow process made more expensive by a 44% no-show rate among prospects who booked one.
Preflect wanted to know whether Enigma's data could disqualify more bad leads before any sales touchpoint, so the team could concentrate on the most valuable prospects.
02
The test
One binary question, asked of leads already judged by hand.
Preflect took a set of inbound leads it had already qualified or disqualified manually and ran them through a single binary check against Enigma's data: did Enigma track the company as having any revenue within the 12 months before their inbound date?
That is the whole intervention. Not a score, not a model — a yes or no on observed card revenue, applied before anyone from sales spent time on the lead.
The reason it works is coverage at the bottom of the market. The $0–1M annual sales band is where most business data thins out, and it is exactly the band Preflect sells into.
“Most data vendors struggle in the $0-1M/year annual sales bucket. The difference between $0 and $100k is the difference between a bad lead / fraud risk and a good lead. Enigma's data enables us to differentiate between these.”
Ian McCue
CEO and Founder, Preflect
03
The results
Three times the bad leads caught, and no repeat of the $100,000 charge.
By pursuing only inbound leads with positive card revenue in Enigma's data, Preflect's lead disqualification rate rose from 18% to 60% — 3.3x more bad leads blocked before a salesperson touched them.
Since implementing Enigma, Preflect has seen much lower fraud rates among new customers and has had no large loss events of the kind that previously cost it a $100,000 charge.
The efficiency gain fed straight through to the top line: the rise in sales efficiency led to a 30% increase in revenue for the company.
Bad leads disqualified, before
18%
Bad leads disqualified, with Enigma
60%
“Most data vendors struggle in the $0-1M/year annual sales bucket. The difference between $0 and $100k is the difference between a bad lead / fraud risk and a good lead. Enigma's data enables us to differentiate between these.”
Ian McCue
CEO and Founder, Preflect
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