Hook Exhaustion

Hook exhaustion is Mission Control’s answer to “is my creative tired?” It’s a per-(client × hook_archetype) composite signal materialized hourly into the HookExhaustionSnapshot table. When an archetype crosses the exhaustion threshold for the first time, the creative.hook_exhausted automation trigger fires — wire it to a Slack alert, a Note, or a custom agent handoff.

The signal

For each archetype that the tenant has any creatives in over the last 28 days, four sub-signals are computed:

Sub-signal	Definition	Interpretation
`spend_share`	This archetype’s spend ÷ tenant’s total spend, in window.	How concentrated the bet is.
`roas_slope`	Linear regression of weekly average ROAS, signed.	Negative = declining.
`ctr_slope`	Same regression, on weekly average CTR.	Secondary fatigue indicator.
`net_new_ratio`	Fraction of in-window creatives whose nearest cosine-prior is ≥ 0.15 distance away.	High = library is iterating; low = repeating.

The composite:

neg_roas_slope_norm  = max(0, min(1, -1 × roas_slope or 0))
spend_share_clamped  = min(1, spend_share / 0.5)     # 0.5 saturates

composite = 0.4 × neg_roas_slope_norm
          + 0.3 × (1 − net_new_ratio)
          + 0.3 × spend_share_clamped

And the gate that decides exhausted vs. healthy:

is_exhausted = (composite       ≥ 0.6
              AND spend_share  ≥ 0.20
              AND roas_slope   < 0)

All three conditions must hold. An archetype with high spend share but flat ROAS isn’t exhausted — it’s just dominant. An archetype with declining ROAS but minor spend share isn’t exhausted — it’s just a small failing bet.

Refresh schedule

Celery beat: 'creative-refresh-hook-exhaustion'
Task:        marketing_resources.refresh_hook_exhaustion_cache
Schedule:    crontab(minute=30)   # every hour at :30
Queue:       automations_low

Each tick:

Find all client_ids that have at least one CreativeAnalysis row.
For each tenant, build the per-archetype signal map for the last 28 days.
update_or_create a HookExhaustionSnapshot per (client_id, archetype_slug, window_end=today).
Compare to the prior is_exhausted=True set; for any new exhausted archetype, fire creative.hook_exhausted.

Re-running on the same data overwrites the snapshot — there is no append. Re-firing the automation trigger only happens on a False→True transition.

The automation trigger

trigger:  creative.hook_exhausted
payload:  {
  "client_id":                "...",
  "archetype":                "<slug>",
  "spend_share":              0.27,
  "roas_slope":               -0.18,
  "net_new_ratio":            0.31,
  "exhaustion_score":         0.71,
  "recommended_alternatives": ["<slug>", "<slug>", "<slug>"]
}

recommended_alternatives is a derived helper — top 3 archetypes (excluding the exhausted one) ranked by average ROAS in the same window. Wire it through the Automations builder:

Pick the trigger

In the Automations editor, choose creative.hook_exhausted as the trigger.

Add a Slack action

Action: slack.send_message. Use the trigger payload as the body — for example:

:warning: Creative fatigue detected on *{{ archetype }}* ({{ exhaustion_score | round(2) }} score).
Spend share: {{ (spend_share * 100) | round(0) }}% — ROAS slope {{ roas_slope | round(2) }}.
Suggested next: {{ recommended_alternatives | join(', ') }}.

(Optional) Auto-create a Note

Action: notes.create. Pre-fill title with the archetype name and link to /ad-creative-analytics so the team can acknowledge / track the response.

The trigger only fires on the transition. Once an archetype is exhausted, subsequent ticks re-write the snapshot but do not re-fire — so your Slack channel doesn’t get spammed every hour.

Drilldown

Each snapshot carries:

top_underperformer_ids — the 3 lowest-ROAS creatives in this archetype.
recommended_alternatives — the 3 highest-avg-ROAS archetypes (excluding the current).

The analytics page Hook Exhaustion card uses these to render a click-through drawer: tap an archetype bar → see the bottom-3 creatives and the top-3 alternative archetypes side by side.

Endpoint

Latest snapshot per (client_id, archetype_slug). Tenant-scoped via shared.auth.get_accessible_client_ids.Query params:

client_id — optional; required for non-superusers.

Returns { "snapshots": [<HookExhaustionSnapshot>, ...] } ordered by (window_end desc, refreshed_at desc).

Bob tool

@tool
def analyze_hook_exhaustion(
    config, client_id: str = '', lookback_weeks: int = 4,
) -> str:
    """Return the latest hook-archetype exhaustion snapshots: which hooks are
    over-spent, declining, or recycling rather than netting new expressions."""

Returns a JSON list of snapshot objects. Bob uses it inline when a user asks “is my creative tired?” or “should I retire any archetypes?” The tool is read-only — it reads materialized snapshots, never recomputes.

Tenant scoping

The _net_new_ratio computation has a subtle correctness bug if you’re not careful: cosine kNN on CreativeEmbedding would naturally walk across tenant boundaries. v2 adds explicit client_id=str(client_id) and kind='analysis_text' filters on both the prior-embeddings query and the in-window query. Cross-tenant leakage is impossible.

Tunable knobs

Setting	Default	Purpose
`LOOKBACK_DAYS`	28	Rolling window for spend / slope / net-new computation.
`NET_NEW_DISTANCE_THRESHOLD`	0.15	Cosine distance below which an in-window creative is “near-prior” (not novel).
Composite weights	`0.4 / 0.3 / 0.3`	ROAS slope vs. recycling vs. spend concentration.
Threshold	`composite ≥ 0.6 AND spend_share ≥ 0.20 AND roas_slope < 0`	The gate.

The composite weights are baked in to _archetype_signals_for_client — adjusting them is a code change, not a settings flag, because changing the gate retroactively re-classifies historical snapshots. If you need a softer / harder gate per tenant, add a config row before changing the constants.

Worked example

A tenant running heavy on before_after for 8 weeks:

Week	Spend share	Avg ROAS	CTR	Net-new	is_exhausted?
Week 1	0.18	2.6	1.4%	0.45	False (composite 0.41)
Week 4	0.24	2.1	1.3%	0.32	False (composite 0.51)
Week 6	0.27	1.7	1.1%	0.18	True (composite 0.69, slope −0.18)

At Week 6, the (False → True) transition fires creative.hook_exhausted once. The user’s Slack rule posts the alert. Subsequent ticks (Week 6.x) re-write the snapshot but do not re-fire. If the tenant pivots and the next week’s signal recovers (is_exhausted=False), then later regresses, the trigger fires again on that next False→True transition.

Where the code lives

marketing_resources/tasks/refresh_hook_exhaustion.py — refresh_hook_exhaustion_cache, _archetype_signals_for_client, _perf_for_window, _weekly_slope, _net_new_ratio, _alternatives, _emit_exhaustion_trigger.
marketing_resources/models/hook_exhaustion.py — HookExhaustionSnapshot.
marketing_resources/views/creative_health.py — the read endpoint.
automations/triggers/__init__.py — creative.hook_exhausted registration.

Getting Started

Onboarding

Platform

Configuration

AI Agents

Agent Surface

Creative Analytics

Development

Lunar Interns

Performance Reports

Attribution & Reporting

Notes / PMT

The signal

Refresh schedule

The automation trigger

Drilldown

Endpoint

Bob tool

Tenant scoping

Tunable knobs

Worked example

Where the code lives

​The signal

​Refresh schedule

​The automation trigger

​Drilldown

​Endpoint

​Bob tool

​Tenant scoping

​Tunable knobs

​Worked example

​Where the code lives

The signal

Refresh schedule

The automation trigger

Drilldown

Endpoint

Bob tool

Tenant scoping

Tunable knobs

Worked example

Where the code lives