Posthog Value Vs Engagement

Are our biggest accounts our happiest ones?

Question: Where does account ARR diverge from product engagement — which big accounts barely use us? For: CS & Leadership · Difficulty: Intermediate · Shape: one dashboard Data sources: PostHog groups (engagement per account) + Salesforce / HubSpot (ARR per account)

What this produces

A saved PostHog insight plotting ARR against an engagement score per account, with the high-ARR / low-engagement quadrant flagged — the accounts whose revenue is at risk, and the expansion targets.

Workflow

First read references/posthog-workflow.md for the shared setup: confirm the PostHog MCP is connected, ensure the CRM source (Salesforce or HubSpot) exists (secure connect-link flow if not), and learn the real schema. This question is account/group-centric, so pay special attention to PostHog group types. Then:

1. Identify the pieces in this project

• Account entity. This works best when the user tracks a PostHog group (e.g. organization). Confirm the group type and how accounts are identified. If they only have persons, aggregate to a company via email domain.
• ARR per account. From the CRM: salesforce_account / hubspot_companies ARR (or an annualized amount) per account. Confirm the field.
• Engagement score. Define a simple, transparent score per account — e.g. active days in the last 30, distinct active users, or count of key events. Keep it explainable.
• Join key. CRM account ↔ PostHog group by name or domain (see join gotchas in the shared reference; lowercase and trim).

2. Build and validate the query

Adapt names and validate with query-run. Produce one row per account with ARR and engagement so it can be plotted or flagged.

-- ARR vs engagement per account, flagging high-ARR / low-engagement.
-- Adapt: group type, CRM table/fields, engagement definition, and the account join key.
WITH engagement AS (
    SELECT
        e.person.properties.company_domain AS account,     -- or the group key
        count(DISTINCT toDate(e.timestamp)) AS active_days_30d,
        count(DISTINCT e.person.id) AS active_users_30d
    FROM events AS e
    WHERE e.timestamp >= now() - INTERVAL 30 DAY
    GROUP BY account
),
arr AS (
    SELECT lower(domain) AS account, sum(annual_recurring_revenue) AS arr
    FROM hubspot_companies
    GROUP BY lower(domain)
)
SELECT
    a.account,
    a.arr,
    coalesce(e.active_days_30d, 0) AS active_days_30d,
    coalesce(e.active_users_30d, 0) AS active_users_30d,
    if(a.arr >= quantile(0.75)(a.arr) OVER () AND coalesce(e.active_days_30d, 0) <= 5,
       'high ARR / low engagement', 'ok') AS flag
FROM arr AS a
LEFT JOIN engagement AS e ON a.account = e.account
ORDER BY a.arr DESC

Engagement scoring is a judgment call — keep it simple and tell the user exactly how you defined it so the flags are trustworthy.

3. Save the insight

Save as a SQL/HogQL insight named "ARR vs engagement by account" (a table works; a scatter is ideal if the user wants the quadrant visual). Offer to put it on a dashboard. Return the URL and name the specific high-ARR / low-engagement accounts.

Self-driving development (offer this)

With ARR mapped against real engagement, the user can protect at-risk revenue and find expansion targets. Offer to help build cohorts for the flagged quadrants and trigger tailored CS outreach or in-product nudges — catching big accounts before they wobble.