Homa LAB Paid Media → Monochrome

1. What you're taking over

Scope of this handoff: everything prefixed [HOMA-LAB] / [HOMA-WILDCAT] / [HOMA-EXT] on Meta and Google, the PostHog-fed automation that powers it, and the measurement conventions. NOT in scope (Monochrome already owns these): the MM_ Meta campaigns and the G_ "High-Intent Buyers"/"Asterisk" Google campaigns — those are already yours.

2. Access & accounts

Credential files (never in this doc — this is a public URL): Meta system-user token, Google Ads OAuth, PostHog keys, Data Manager OAuth all live on the ops machine. Hand these over securely, out of band. Do not paste secrets into any shared page.

3. Meta LAB campaign inventory

Prospecting

Retargeting

4. Google LAB campaign inventory

Google LAB = the metro Search campaigns (Tampa/Orlando/Jax/Miami + TX metros), RLSA Warm (best-CPA retargeting layer), Brand, Wildcat exploration, Display remarketing, Hero Video, Extension. Google is the down-funnel engine — it drives the majority of qualified/approved (see §10).

5. Audiences (top 30 by size)

All refreshed nightly by workers (§6) — do not treat as static uploads.

Google Customer Match lists

6. ⚙️ The automation fleet — MOST IMPORTANT

These Cloudflare Workers read PostHog nightly and push audiences / Customer Match / conversions into Meta & Google. They are the moat. Monochrome must either keep them running (recommended) or replace them before they're decommissioned.

Decommissioned / do not use: audience-sync (never deployed, dead code).

7. UTM conventions & attribution truth

How to tell LAB from Mono (critical)

"All Google = LAB" is WRONG. Mono runs Google too (the G_ "High-Intent Buyers"/"Asterisk" campaigns). Case-sensitive G_ vs lowercase g_lab is the discriminator.

Attribution reality — do not trust event-UTM

• Only ~8% of qualified_lead events carry a UTM (92% fire in a direct/untagged session). So a per-campaign "qualified by UTM" view under-counts massively and over-credits whatever channel drove the in-session qualify (usually retargeting).
• Person-level first/last/any-touch is the truth. Roughly: ~45% of qualified/approved are direct/untracked, ~40% single-touch, ~20% multi-touch (double-countable across channels).
• Role split: Meta LAB = top-of-funnel volume (drove ~0 approvals last week). Google + direct = the down-funnel closers. Mono Meta opens journeys; LAB Google closes them.
• PostHog is the source of truth. Ignore Google's own conversion column. gclid→click_view recovery + enhanced-conversions gclid backfill are used to reclaim UTM-severed Google.

8. Optimization events & value ladder

Primary optimization event = engaged_lead (2+ distinct property views in a day) — frequent enough to exit learning, unlike the rarer onboarding_completed. Google Smart Bidding is fed the offline value ladder (via Data Manager):

Recent change (8/6): 5 chronically learning-limited ad sets that optimized the rare onboarding_completed were rebuilt to optimize engaged_lead — currently in learning; let them stabilize before judging.

9. Hard-won gotchas

• DPA creative link limit: can't be a macro or >~1,000 chars → use the homa-metro-go redirect worker.
• Catalog ad sets must use the raw pixel-event form in promoted_object ({pixel_id, custom_event_str}), NOT custom_conversion_id — the latter is accepted, shows no error, and silently never serves.
• New catalog needs its pixel connected (external_event_sources) or a conversion-optimized campaign serves 0 impressions with everything reading green.
• promoted_object is locked after publish — to change the optimization event you must build a new ad set (deep-copy then edit works while unpublished).
• Meta learning resets on: budget change >20%, placement change, audience/optimization change, creative content change. url_tags-only (UTM) changes do NOT reset learning (verified via last_sig_edit_ts).
• Customer Match does not serve on GDN display (search sizes populate, display ~0). Use rule-based/pixel lists for display.
• Placements / Reels: 22 Meta ad sets are Feed-only; 9 remain on Advantage+ (incl Reels) — intentionally left to avoid learning resets. Build any NEW ad set Feed-only at creation to avoid the reset entirely.
• OnSpot open-house audiences are partner-provided/shared and not targetable ("custom audience not available / missing perms"), and can't seed lookalikes. Unblock = get the raw address file and upload as first-party. Currently NOT running.
• Housing special-ad-category blocks lookalike audiences; the metro-carousel commerce catalog is deliberately non-housing to keep LALs + Advantage+ available.
• Reddit is fully paused (foreign/low-quality traffic).

10. Current performance baseline

Watch the right metric. CPL has crashed to $2-3 but that's volume dilution — leads grew +240% while qualified grew ~17%, so the lead→qualified rate fell from 7.7% to 2.6%. Optimize toward cost-per-qualified / cost-per-approved, not CPL. Down-funnel is carried by Google + direct; Meta LAB is cheap reach + retargeting-pool fuel.

11. Open items & handoff checklist

In-flight (mid-change)

• 5 ad sets switched onboarding→engaged_lead on 8/6 — in learning, let stabilize.
• Cold v2 (Price-Engaged) launched 8/7 — new, on Advantage+ placements.
• Fleet budgets glided -20% on 8/6 (LAB only; Mono reverted). Revert values on the ops machine.
• OnSpot open-house audiences loaded but blocked (see §9).

Monochrome onboarding checklist

1. Get partner access: Meta act_9501970176547289 + Google MCC 2225490048.
2. Get PostHog project 141181 access (measurement) + review the attribution truth in §7.
3. Decide on the automation fleet (§6): keep the PostHog→audience/CM/CAPI workers running (recommended — receive the repos + credentials) or plan a replacement before decommission, or audiences go stale.
4. Adopt the UTM conventions (§7) so LAB stays distinguishable from your MM_/G_ work in reporting.
5. Re-baseline against §10 and optimize toward cost-per-qualified/approved.

12. How we run it — operating principles

• Leads are the headline; qualified/approved are the scoreboard. CPL is a vanity metric at scale (it crashes as you buy cheap reach). Optimize to cost-per-qualified and cost-per-approved, and track median viewed price & break-even close rate weekly.
• Signal-first, spend-second. The moat is fresh first-party audiences (the worker fleet), not any bought list. Keep spend capped behind campaigns that target those signals. Data thesis: first-party conversion signal fed to the algorithm beats any static list, and the flywheel is more converters → better lookalike seeds.
• Division of labor is real — fund the closers. Meta = cheap top-of-funnel reach + fuel for the retargeting pool (shallow: ~18% engaged, ~0 direct approvals). Google Search + retargeting = the down-funnel closers (Google runs ~2.5× better CAC). Don't over-fund shallow Meta prospecting because CPL looks great.
• Value-based bidding. Feed the platforms the dollar value ladder (Meta CAPI values + Google Data Manager offline conversions) so Smart Bidding optimizes toward $, not raw event counts.
• Respect the learning phase. Budget steps ≤20% every 2-3 days. Avoid placement / audience / optimization-event / creative-content edits on live ad sets — they reset learning. UTM (url_tags-only) changes are safe. Build every NEW ad set with its final placements + optimization event from birth so you never owe a reset.
• Attribution humility. PostHog is the source of truth — ignore Google's own conversion column. ~45% of qualified/approved are direct/untracked. Judge channels person-level (first/last/any touch), never by event-UTM (only ~8% coverage). Keep LAB (homa-lab) vs Mono (MM_/G_) UTM discipline so reporting stays honest.
• Brand posture is non-negotiable. Buyer-trust over any single close — never anti-realtor, always "up to 2% / $10K-$25K+" framing, ads always show tryhoma.com. Homa will tell a buyer not to buy when that's right; the paid program must never undercut that.
• Reversible & gated. Ship reversible changes freely; gate large spend and anything irreversible. Log outcomes and fail loud (Slack alerts on worker failures) — a silently-broken audience feed is the worst failure mode.

13. Tools & stack to maintain

Skills the operator needs: HogQL, Meta & Google Ads APIs, Cloudflare Workers/wrangler, the value-ladder + person-level attribution model, and the DPA catalog + redirect-worker pattern. Credentials (Meta token, Google/Data-Manager OAuth, PostHog keys, Cloudflare) are handed over out of band — never in this page.

14. Roadmap — how to improve the system

Ranked, highest-leverage first:

1. Fix measurement. Move the dashboards off event-UTM (8% coverage) to person-level journey attribution, and put CPQ / CPA next to CPL so the vanity metric stops being the headline.
2. Populate suppression. Fill the empty Closed + In-Escrow and Qualified exclusion lists (source from Attio) — you're currently paying to re-serve people who already transacted.
3. Unblock OnSpot via Google Customer Match. Get the raw open-house address file from OnSpot and upload it as a first-party address CM list (targetable + lookalike-able) — sidesteps the Meta partner-permission block entirely.
4. Close the reg→qualified gap. Registered users browse deep (median 5 homes) but stall before the tour request; Meta-sourced regs qualify at ~13% vs 26-33% for direct/Google. Add a mid-funnel nudge and tighten Meta registration quality.
5. Scale the closers. Google metro Search + RLSA Warm drive the down-funnel; TX metros have been spend-gated/dark. Push budget toward the best-CAC surfaces (Google), not the cheapest-CPL ones (Meta prospecting).
6. Mature value bidding. As approved volume grows, graduate optimization toward the approved event / higher-value targets; keep feeding accurate ladder values.
7. Creative velocity. Systematic angle testing; DPA dynamic for retargeting, static/carousel for cold audiences; scheduled catalog + creative refresh.
8. Harden automation. Failure alerting on every worker (a stale audience feed reads "green" while degrading), and automate the catalog/product-set refresh cadence.