Posthog Lead Scoring

Which leads deserve the sales team's time?

Question: Which leads are most product-engaged — especially ones sales hasn't contacted yet? For: Sales & Growth · Difficulty: Intermediate · Shape: a scored query Data sources: PostHog events (key product actions) + HubSpot / Salesforce (lead records)

What this produces

A saved PostHog insight scoring CRM leads by recent product usage and highlighting the most engaged ones that sales hasn't yet reached — a product-qualified-lead list.

Workflow

First read references/posthog-workflow.md for the shared setup: confirm the PostHog MCP is connected, ensure the CRM source (HubSpot or Salesforce) exists (secure connect-link flow if not), and learn the real schema. Then:

1. Identify the pieces in this project

• Key product actions. With the user, define the handful of events that signal buying intent / real usage (event-definitions-list). Assign each a weight, or keep it simple (count of key events, recency + frequency).
• Lead records. From the CRM: lead/contact rows with email, owner, and a "contacted"/lifecycle field so you can tell who sales has already worked. Confirm the field that means "not yet contacted".
• Join key. CRM lead ↔ PostHog person by lower(email) (see join gotchas in the shared reference).

2. Build and validate the query

Adapt names and validate with query-run. Produce one scored row per lead, filtered/sorted to surface warm, uncontacted leads.

-- Score leads by recent product usage; surface the warmest uncontacted ones.
-- Adapt: key events + weights, the CRM table/fields, and the "contacted" flag.
WITH usage_score AS (
    SELECT
        lower(person.properties.email) AS email,
        sum(multiIf(event = 'created_project', 5,
                    event = 'invited_teammate', 4,
                    event = 'ran_query', 2, 1)) AS score,
        max(timestamp) AS last_seen
    FROM events
    WHERE timestamp >= now() - INTERVAL 30 DAY
      AND event IN ('created_project', 'invited_teammate', 'ran_query', 'viewed_pricing')
    GROUP BY lower(person.properties.email)
)
SELECT
    l.email,
    l.lead_owner,
    us.score,
    us.last_seen,
    l.lifecycle_stage
FROM hubspot_contacts AS l
INNER JOIN usage_score AS us ON lower(l.email) = us.email
WHERE l.lifecycle_stage NOT IN ('customer')          -- still a lead
  AND (l.last_contacted IS NULL OR l.last_contacted < now() - INTERVAL 30 DAY)  -- "not contacted yet"
ORDER BY us.score DESC
LIMIT 100

Keep the scoring transparent and let the user tune weights — a lead score sales doesn't understand won't get used. Note that this ranks by product signal only; a real PQL model may blend in firmographics.

3. Save the insight

Save as a SQL/HogQL table insight named "Product-qualified leads (uncontacted)", documenting the scoring weights and window. Return the URL and name the top few leads to call today.

Self-driving development (offer this)

With leads scored by real product usage, the user can catch the warmest ones as they heat up. Offer to help set up an alert or a cohort that flags a lead when its score crosses a threshold — filling the pipeline while they sleep. (Pushing the score back into the CRM is a separate reverse-ETL step; offer to explain it.)