From gut feel to a goal: lead scoring at Faddom

Faddom's sales team was prioritizing leads by hand. A lot of work, and no way to know whether they were getting it right. Marketing couldn't tie spend to pipeline. Next quarter was a guess.

What the data revealed

I analyzed two years of inbound leads across every dimension the CRM had: geography, industry, job title, company size, acquisition channel, and product engagement. Two findings changed how the team works.

First: Faddom doesn't have one ICP. It has two. A "bread & butter" segment (1,000–10,000 employee companies) that closes often and fast, and a "whale" segment (10,000+) with lower close rates and year-long cycles, where a single deal can transform the year. Two segments, two different playbooks.

Second: not all leads are created equal. At all.

Tier	Leads	Wins	Conversion
Prime ICP	458	23	5.02%
Strong ICP	1,452	30	2.07%
ACP	1,698	4	0.24%
Out of scope	665	0	0.00%

665 leads had received two years of calls and follow-ups, and produced zero revenue. Meanwhile the top tier converted at 3.8x the average, and nobody knew it existed.

What we built

Every lead now gets a score from 0 to 100 and lands in a tier, live inside Salesforce, updating as the lead moves through the funnel. Sales works the score. Marketing refines audiences against the tiers that actually close.

Did it work? Check the forecast.

The same foundations power a pipeline forecast: lead attributes plus demo quality, rolled into expected wins and revenue. The model predicted 56 wins and $3.47M. The year closed at 57 wins and $4.15M. Off by one win, with revenue coming in higher because the deals got bigger.