Late-stageFintech & Financial Services
Rebuilding an ICP from closed-won signal analysis, then sourcing look-alikes for a new vertical
A signal-ranked ICP rather than an opinion-ranked one
A signal-ranked ICP rather than an opinion-ranked one
Targeting was intuition dressed up as data. The account attributes that most strongly predicted deal size were the ones the CRM could not see: the field capturing a category-defining platform attribute was populated on under a fifth of records, the volume metric that best predicted deal size was missing on about two-thirds, and the competitor field was effectively unpopulated.
Rather than asking sales what mattered, we analysed roughly 400 closed-won deals and looked for account attributes that correlated with deal size.
For every high-value-but-empty field we wrote a named path rather than a generic 'enrich the account': job-posting scans for administrator titles tied to the platform in question, technographic detection on the prospect's web properties, press-release monitoring for adoption announcements, and a public filing for the volume metric.
The initial look-alike universe came from the publicly named customers and testimonial logos of five direct competitors.
We ran the tier definitions against a live list of companies drawn from the target vertical. The sweet-spot tier captured only about a quarter of them, which for a vertical-specific list is a failing grade.
About one record in ten carried a data defect that would have mis-tiered it: revenue values off by three orders of magnitude, blank sub-vertical labels, and employee-to-revenue ratios that were physically implausible.
A planned technology-footprint signal, detect whether a prospect was already running a competing product, returned nothing across two technographic providers for the entire competitor set. Those products simply do not leave a detectable footprint on a prospect's web properties.
A signal-ranked ICP rather than an opinion-ranked one
Account attributes ranked by their observed relationship to deal size, cross-referenced against CRM fill rates, producing an ordered enrichment backlog instead of a wish list.
