Posthog Support Tickets Churn

Do support tickets predict churn?

Question: Which support ticket volumes/topics precede the most churned revenue? For: Support & CS · Difficulty: Intermediate · Shape: a three-way join Data sources: PostHog events (engagement) + Zendesk/Intercom (tickets & topics) + Stripe (churn)

What this produces

A saved PostHog insight ranking support issues by the revenue that churns after them, and showing how ticket volume relates to engagement and cancellation — so the user knows which support problems actually cost money.

Workflow

First read references/posthog-workflow.md for the shared setup: confirm the PostHog MCP is connected, ensure the Zendesk (or Intercom) and Stripe sources exist (secure connect-link flow for each if not), and learn the real schema. This question needs two external sources plus PostHog, so verify all three are present before querying. Then:

1. Identify the pieces in this project

• Tickets & topics. From Zendesk/Intercom: ticket rows with a customer identifier, created date, and a topic/tag/category field. Confirm which field carries the "topic".
• Churn. From Stripe: canceled subscriptions and the revenue lost (approximate from the last active stripe_invoice/subscription value — see the money gotchas in the shared reference).
• Engagement. A per-account PostHog engagement measure (event count or active days).
• Join key. Tickets → accounts by email or domain; accounts → Stripe by email/customer id. Domain joins (splitByChar('@', email)[2]) are common when tickets are logged per-company.

2. Build and validate the query

Adapt names/fields and validate with query-run. Core idea: per topic, sum the churned revenue of accounts that filed that topic.

-- Support topics ranked by the churned revenue of accounts that filed them.
-- Adapt: ticket table/fields, the topic field, the churn/revenue logic, and join keys.
WITH churned AS (
    SELECT lower(email) AS email, sum(amount) / 100.0 AS lost_revenue
    FROM stripe_invoice
    WHERE status = 'paid'
      AND lower(email) IN (
        SELECT lower(email) FROM stripe_subscription WHERE status = 'canceled'
      )
    GROUP BY lower(email)
),
tickets AS (
    SELECT lower(requester_email) AS email, subject_topic AS topic
    FROM zendesk_tickets
    WHERE created_at >= now() - INTERVAL 180 DAY
)
SELECT
    t.topic,
    count(DISTINCT t.email) AS accounts_with_topic,
    count() AS ticket_count,
    round(sum(c.lost_revenue), 2) AS churned_revenue_after_topic
FROM tickets AS t
INNER JOIN churned AS c ON t.email = c.email
GROUP BY t.topic
ORDER BY churned_revenue_after_topic DESC

Be honest in the writeup: this shows correlation between topics and churned revenue, not proof the tickets caused churn. A high-volume topic among healthy accounts can still be fine.

3. Save the insight

Save as a SQL/HogQL table insight named "Support topics ranked by churned revenue", with a note on the churn/revenue method. Return the URL and call out the top revenue-costing issues.

Self-driving development (offer this)

With issues ranked by the revenue they cost, the user can spot accounts hit by the worst ones. Offer to help build a cohort of accounts with those tickets and trigger proactive CS outreach or a fix experiment — protecting revenue automatically.