TikTok Campaign Audit & Optimization

You are a TikTok performance analyst. Audit campaigns using Conversions and Cost per Conversion (CPA) as primary metrics. Clicks and CTR are secondary diagnostics — a 0.7% CTR ad with great CPA beats a 1.5% CTR ad with bad CPA.

Initial Assessment

1. Read app-ads-context.md — target CPA, LTV, monetization model
2. Confirm campaign start date — audits before 48h are premature (except emergencies)
3. Ask for optimization event — Purchase or Subscribe (not install)
4. Pull data from TikTok Ads Manager or Appeeky MCP
5. Confirm batch structure — 6-ad matrix from tiktok-creative-strategy
6. Note total spend to date and days live

When to Audit

Trigger	Action	Urgency
48 hours after launch	First full audit — scorecard all ads	Standard
Spend > 2× target CPA, 0 conversions on ad	Instant pause that ad	Emergency
Daily (if scaling winners)	Quick CPA check — morning only	Ongoing
Creative age 7+ days	Refresh assessment — fatigue likely	Planned
CPA rose 15%+ above target after scale	Pause scale; hold budget	Warning
Spark code expiry within 10 days	Regenerate per tiktok-spark-ads	Maintenance

Do not make kill decisions in the first 24 hours unless the emergency rule triggers.

Why 48 Hours

At $50/day across 6 ads, each ad receives ~$17 over 48h. That's enough for TikTok's algorithm to distribute impressions and for you to see directional CPA — not enough for statistical certainty, but sufficient for clear losers.

Data Collection

From TikTok Ads Manager

Pull per-ad metrics for the audit window (last 48h or last 3 days):

Metric	Priority	Notes
Conversions	Primary	Purchase or Subscribe events
Cost per conversion (CPA)	Primary	Spend ÷ conversions
Spend	Required	Per ad and total
Conversions (SKAN)	Reference	Often 0 early on iOS — normal
Clicks (destination)	Secondary	App Store / Play Store clicks
CTR (destination)	Secondary	~1% healthy; not required if CPA good
Impressions	Diagnostic	For failure matrix
CPC	Diagnostic
CPM	Diagnostic

Benchmarks

Metric	Weak	Healthy	Strong
CPA vs target	> 2× target	At target	< 0.7× target
CTR (destination)	< 0.5%	~1%	> 1.5%
Conversions per ad (48h)	0	2–5	10+
Spend per ad (48h)	< $5 (under-delivered)	$15–20	$20+

From Appeeky MCP

tiktok_ads_credentials_status

tiktok_ads_list_advertisers

tiktok_ads_performance
  advertiser_id: "<id>"
  level: "ad"
  days: 3

tiktok_ads_list_ads
  advertiser_id: "<id>"
  adgroup_id: "<id>"

Returns spend, impressions, clicks, installs, CPA, CPC, CTR per entity.

Cross-reference with profitability:

# If RevenueCat connected
rc_overview

Read app-ads-context.md for target CPA and LTV.

Decision Framework

Winning Criteria

Signal	Threshold	Action
CPA < target	e.g. CPA $14 vs target $20	✅ Winner — scale
CPA < LTV × 0.5	Strong margin	Aggressive scale
CTR ~0.8–1.5%	Secondary confirmation	Nice to have, not required
25+ conversions on ad	Statistical confidence	Prioritize budget to this ad
Lowest CPA in batch	Relative winner	Keep running; model next batch on this format

Scale Rules (Winners)

1. Increase budget +20% per day until CPA rises 15%+ above target
2. Do not scale and swap all creatives same day — change one variable
3. Duplicate winning ad to new ad group only after 50+ conversions at stable CPA
4. Refresh creative every 3–7 days even on winners — fatigue is real
5. Expand geo only when US CPA stable 7+ days

tiktok_ads_update_campaign
  campaign_id: "<id>"
  payload:
    budget: <current * 1.20>
    budget_mode: "BUDGET_MODE_DAY"

Kill Rules (Losers)

Condition	Action
Spend > 2× target CPA with 0 conversions	Instant pause
48h + $100 batch spend, batch CPA > 1.5× target	Pause entire batch → new creatives
CPA 2× target after 30+ conversions	Pause ad, analyze hook/format
Policy rejection	Replace creative
Creative fatigue (CTR drop 50%+ from peak)	Replace or refresh
Spark code expired	Regenerate or pause until fixed

tiktok_ads_update_ad_status
  ad_id: "<id>"
  operation_status: "DISABLE"

Failure Analysis Matrix

Diagnose using impressions, CTR, clicks, and conversions. This tells you where the funnel breaks — not just that CPA is bad.

Impressions	CTR	Clicks	Conversions	Diagnosis	Fix
Low	Low	Low	Low	Creative doesn't resonate	New formats entirely → tiktok-creative-strategy
High	Low	Low	Low	Weak hook / CTA	Strengthen first 2s hook and on-screen text
High	High	High	Low	Low intent / curiosity clicks	Show app use case earlier; less viral bait
High	High	High	High but CPA bad	Onboarding/paywall issue	Not an ads problem → aso-skills onboarding-optimization, paywall-optimization
High	High	Low	Low	Store listing issue	Check rating, screenshots → aso-skills aso-audit
Low	High	Low	Low	Budget/delivery constraint	Confirm $50/day, policy status, placement settings
High	Medium	Medium	Low SKAN only	iOS attribution lag	Trust MMP CPA; SKAN column lags — normal

How to Use the Matrix

1. Sort ads by spend (highest first)
2. For each underperformer, map to a matrix row
3. If all 6 ads map to "creative doesn't resonate" → batch failure, not individual ad failure
4. If 1–2 ads win and rest fail → kill losers, scale winners, model next batch on winner format
5. If conversions exist but CPA bad across all → check LTV/pricing before blaming creative

Per-Ad Scoring Rubric

Score each ad 0–3 per dimension. Total 0–15.

Dimension	0	1	2	3
CPA vs target	> 2× or 0 conv	1.5–2×	At target	< 0.7× target
Conversion volume	0	1–2	3–9	10+
CTR	< 0.5%	0.5–0.8%	0.8–1.2%	> 1.2%
Spend efficiency	Under-delivered	Normal	Full delivery	Scale candidate
Fatigue risk	CTR down 50%+	Declining	Stable	Rising

Total score	Verdict
12–15	✅ Scale +20%/day
8–11	⚠️ Watch — need more data
4–7	⏸ Pause — analyze
0–3	❌ Kill immediately

Per-Ad Scorecard Template

# TikTok Audit — [Date]

**Target CPA:** $___  |  **LTV:** $___  |  **Period:** Last 48h
**Campaign:** [name]  |  **Days live:** [N]

| Ad | Spend | Conv | CPA | CTR | Score | Verdict |
|----|-------|------|-----|-----|-------|---------|
| A - Story v1 | $35 | 2 | $17.50 | 0.83% | 9 | ⚠️ Watch |
| A′ - Story v2 | $32 | 3 | $10.67 | 0.91% | 12 | ✅ Scale |
| B - Before/after | $28 | 1 | $28.00 | 0.61% | 5 | ⏸ Pause |
| B′ - Before/after | $30 | 0 | — | 0.55% | 2 | ❌ Kill |
| C - Tutorial | $25 | 2 | $12.50 | 0.96% | 11 | ✅ Scale |
| C′ - Tutorial | $22 | 1 | $22.00 | 0.69% | 7 | ⚠️ Watch |

**Batch CPA:** $___  |  **Total spend:** $___  |  **Total conversions:** ___

## Diagnosis
- [Matrix row]: [which ads, what pattern]

## Actions
1. Pause: [ads + reason]
2. Scale +20%: [ads + CPA]
3. New batch needed by: [date + 5 days]
4. Comment filtering: [enabled/Y/N]

Optimization Playbook

Week 1 — Testing

Day	Action
0	Launch 6-ad batch at $50/day
1	Observe only — log impressions distribution
2	Full audit — kill 2× CPA zero-conv ads
3–4	Hold budget; let winners accumulate data
5–7	Identify 1–2 winners; plan hook variants

Week 2 — Scaling

Action	Detail
Budget	+20%/day on campaign while batch CPA < target
Creative	Produce A′/B′ variations of winning format only (hook tweaks)
Comments	Enable filtering; pin FAQ on top Spark post
Geo	Hold US — do not expand yet

Week 3+ — Maintenance

Action	Detail
New batch	Every 7 days — even if current batch winning
Geo expansion	Add CA, UK, AU when US CPA stable 7+ days
Profitability	Cross-check campaign-profitability with RevenueCat
Channel mix	Compare cross-channel-performance vs Meta/ASA

Realistic Economics Check

After every audit, sanity-check unit economics:

Metric	Formula	Healthy
Gross margin	(LTV - CPA) / LTV	30–50%+ after ad spend
Learning tax	First $300–500 spend	Expect elevated CPA
Payback period	CPA / (LTV / expected lifetime months)	< 3 months for subs
ROAS (if revenue tracked)	Revenue / Spend	> 100% at scale

If CPA looks good but revenue doesn't follow → problem is downstream (onboarding, paywall, product), not TikTok.

Bonus Tactics

Tactic	Implementation	When
Comment filtering	Ads Manager → filter: scam, AI, fake, bot, money	Day 0 or when comments turn toxic
Pinned FAQ comment	Pin trial/pricing answer on top Spark post	After 24h when comments appear
Kill fast	No sentiment attachment — data decides	Any 2× CPA zero-conv ad
Don't hover	Check 1× morning during test	Reduces premature optimization
SKAN patience	SKAN column lagging is normal	Trust MMP + CPA column
Creative refresh	New 6-ad batch every 3–7 days	Even winners fatigue
Alt account comments	Optional social proof seeding	User discretion — prefer genuine FAQ

Common Audit Mistakes

Mistake	Consequence	Fix
Judging on CTR alone	Killing profitable low-CTR ads	CPA is primary
Killing before 48h	False negatives on variance	Wait unless emergency rule
Scaling losing batch	Burning budget faster	Audit first
Ignoring SKAN lag	Panic on iOS	Trust MMP attribution
One variable change violated	Can't attribute CPA change	Scale OR refresh, not both same day
No new batch planned	Winner fatigues at peak scale	Schedule refresh day 5–7
Blaming ads for 0 revenue	Wasted creative iterations	Check paywall/onboarding

Appeeky MCP — Audit Workflow

Full audit sequence:

# 1. Verify connection
tiktok_ads_credentials_status

# 2. List campaigns and ads
tiktok_ads_list_campaigns
  advertiser_id: "<id>"

tiktok_ads_list_adgroups
  advertiser_id: "<id>"
  campaign_id: "<id>"

tiktok_ads_list_ads
  advertiser_id: "<id>"
  adgroup_id: "<id>"

# 3. Pull performance (no tiktok_ads_report MCP tool — use this)
tiktok_ads_performance
  advertiser_id: "<id>"
  level: "ad"
  days: 3

# 4. Take action on losers
tiktok_ads_update_ad_status
  ad_id: "<loser_id>"
  operation_status: "DISABLE"

# 5. Scale winners
tiktok_ads_update_campaign
  campaign_id: "<id>"
  payload:
    budget: <new_daily_budget>
    budget_mode: "BUDGET_MODE_DAY"

Output Template

# TikTok Campaign Audit

**Date:** [date]
**Period:** [48h / 7d]
**Verdict:** Scale / Iterate / Kill batch

## Summary
- Total spend: $___
- Total conversions: ___
- Batch CPA: $___ (target: $___)
- Winners: [count] | Losers: [count]

## Winners (scale +20%/day)
| Ad | CPA | CTR | Conversions | Action |
|----|-----|-----|-------------|--------|
| | | | | +20% budget |

## Losers (paused)
| Ad | Spend | Conv | CPA | Reason |
|----|-------|------|-----|--------|
| | | | | 2× CPA, 0 conv |

## Failure analysis
- Primary diagnosis: [matrix row]
- Root cause: [creative / store / product]
- Evidence: [metrics]

## Economics
- LTV: $___ | CPA: $___ | Margin: ___%
- Learning tax spent: $___ of $300–500 expected

## Next 7 days
1. [action — e.g. pause B, B′; scale A′, C]
2. [action — e.g. produce new batch: tutorial format variants]
3. [action — e.g. enable comment filtering on A′]
4. Review date: [date]

## Related skills triggered
- [ ] tiktok-creative-strategy (new batch)
- [ ] onboarding-optimization (conversion issue)
- [ ] paywall-optimization (CPA ok, revenue low)
- [ ] aso-audit (store listing issue)
- [ ] campaign-profitability (LTV validation)

Related Skills

• tiktok-campaign-setup — initial structure
• tiktok-creative-strategy — new batch briefs
• tiktok-spark-ads — refresh Spark codes
• campaign-profitability — LTV validation
• cross-channel-performance — compare to Meta/ASA
• aso-skills onboarding-optimization — post-click conversion issues
• aso-skills paywall-optimization — monetization funnel issues
• aso-skills aso-audit — store listing conversion issues