#The challenge
The self-serve funnel produced enormous volume and almost no qualification: no product-qualified-lead definition, no routing rules, and no reliable way to tell whether a signup represented a company at all, since most used personal email addresses. Sales had no principled basis for deciding which self-serve users deserved an account executive, and an earlier notification approach had flooded reps with alerts, which made the team justifiably wary of turning anything on. Contracting downstream was equally manual once a deal did reach a rep.
#The approach
Usage and spend signals into the CRM
Piped Snowflake spend and usage data into HubSpot so behavioral reality — spend run rate, usage pattern, activity trend — sat on the record where scoring and routing could actually use it.
A fit × behavioral PQL model
Built a sixth-iteration PQL model combining firmographic fit tiers with behavioral tiers, banding every contact into a fit × behavior grid rather than collapsing everything into a single score.
Controlled routing into sales
Gated AE-versus-SDR routing on the model and rolled net-new product-qualified leads to AEs on a delay with notifications throttled — an explicitly staged release designed around the earlier alert flood rather than pretending it had not happened.
Enrichment to unmask the base
Ran reverse-email and funding enrichment across the contact base to turn anonymous personal-email signups into identified companies and fill missing firmographic data, then proposed a criteria-based intake filter to stop paying enrichment credits on records that would never qualify.
Contracting and deal hygiene
Built PandaDoc contract templates with CRM sync, mapped qualification-framework fields into Gong, backfilled historical contracts, and opened a CPQ workstream off an analysis of executed agreements and 90 days of recorded pricing calls.
#Outcomes
~7,600 product-qualified contacts projected
The PQL model was built and staged on live spend and usage signals, banding every contact into a fit × behavioral grid; its projection is roughly 7,600 product-qualified contacts. Staged as a disabled draft for controlled rollout at the time of writing.
~112 net-new PQLs in the first controlled go-live
The first release sized roughly 112 product-qualified leads to route to AEs on a two-day delay with notifications throttled, deliberately sized small to avoid repeating an earlier alert flood.
~32% proposed enrichment-credit savings
A criteria-based funding-intake filter was modeled to cut monthly enrichment credit consumption by roughly a third while still retaining 93% of funding matches. Proposed, not yet executed at the time of writing.
Contracting templates live and a CPQ workstream opened
Contract templates synced to the CRM, qualification-framework fields mapped into the conversation-intelligence platform, historical contracts backfilled, and a CPQ build opened off an analysis of executed agreements and roughly 330 recorded pricing calls across 90 days.