Ad Campaign Analyzer

Usage

Use when reviewing a running campaign to decide what to kill, keep, or scale. Works for daily 15-minute ad reviews, weekly creative refresh planning, and monthly performance trend reviews.

Process

Step 1: Gather Inputs

Ask the user for:

• Campaign data — one of:

• CSV or table with columns: ad/ad set name, impressions, clicks, conversions, spend, CPA

• Pasted text from ads manager

• Structured list of metrics per ad

• Target CPA — the maximum they're willing to pay per acquisition

• AOV (Average Order Value) — what they earn per conversion on the front end

• Product/pricing info — what they sell, offer details, known conversion benchmarks

• Daily budget per ad set (optional) — for scaling calculations

• Days running (optional) — for statistical significance judgment

• Historical data (optional) — from previous review for trend comparison

Step 2: Parse Campaign Data

Normalize the input into a consistent table structure:

Ad / Ad Set Impressions Clicks CTR Conversions Spend CPA Days Running

Calculate any missing derived metrics:

• CTR = clicks / impressions × 100

• CPA = spend / conversions (∞ if 0 conversions)

• Conversion rate = conversions / clicks × 100

Step 3: Grade Each Ad — Red / Yellow / Green

🔴 RED = STOP

Kill this ad. It's burning money.

Criteria (any one triggers Red):

• Spent 1.5–2x target CPA with zero conversions

• CPA is 2x+ target CPA with statistically significant spend

• Consistently worsening metrics over multiple days with no improvement signs

• CTR below 0.5% after 1,000+ impressions (the creative isn't connecting)

Action: Turn off immediately. Redirect budget to greens.

🟡 YELLOW = LEAVE ALONE

Don't touch it. It needs more data or is borderline.

Criteria:

• CPA is close to target (within 0.5–1.5x) but not enough data to be confident

• Fewer than 1,000 impressions or fewer than 20 clicks — too early to judge

• Spend is under 1x target CPA — hasn't had a fair chance yet

• Metrics are mixed (good CTR but low conversion, or vice versa)

Action: Do nothing. Check again tomorrow. Resist the urge to tweak.

🟢 GREEN = SCALE

This ad is working. Give it more budget.

Criteria:

• CPA is consistently at or below target CPA

• Has statistically significant data (generally 10+ conversions)

• Metrics are stable or improving over time

• CTR is healthy for the targeting type

Action: Scale using the 20% Rule — increase daily budget by 20% every 48 hours.

Step 4: Benchmark Comparison

Compare each ad's metrics against industry benchmarks:

CTR Benchmarks (by targeting type):

Targeting Expected CTR

Broad / run-of-network 1–3%

Interest-based targeting 2–4%

Lookalike / community-targeted 3–5%

CPA Targets by Offer Price:

Offer Price Range Expected CPA Range

$7–27 (low ticket) $20–40

$37–97 (mid ticket) $40–120

$97+ (high ticket) Varies — must model LTV

Step 4b: Funnel Debugging — Find the Leak

Before changing creative, check whether the ad is actually the problem. Work from the surface inward:

• Creative — Is the CTR acceptable? Low CTR = the ad isn't connecting. Test new hooks, visuals, or headlines.

• Landing page — CTR is fine but conversions are flat? The LP is the problem.

• Messaging — LP structure looks okay but still no conversions? The fundamental message may not be resonating.

• Product and pricing — Different angles all fail? The offer itself may be the issue.

• Market — Everything above looks solid but the right people still aren't converting? The segment may be wrong.

Work from #1 → #5 in order. Most founders jump to #3 or #4 when the actual problem is #1 or #2.

Data thresholds — don't debug on noise:

• < 1,000 impressions per ad variant: Too early to judge CTR.

• < 100 LP visitors: Too early to judge landing page conversion.

• < 10 conversions on a green ad: Scale cautiously — the trend may not hold.

Step 5: Flag Creative Fatigue

Check for fatigue signals across the data:

• Declining CTR over time (even if still "okay" in absolute terms)

• Rising CPA despite no changes to targeting or budget

• Dropping conversion rate with stable traffic quality

• Frequency above 3 (same people seeing the ad too many times)

If fatigue is detected, flag which ads are affected and recommend:

• New creative variation (different angle, format, or style)

• Audience refresh (new targeting or exclusions)

• Copy refresh (same visual, new headline)

Step 6: Profitability Check

The North Star: Is AOV > CPA?

For each green ad, calculate:

• Profit per conversion = AOV − CPA

• ROAS = AOV / CPA (must be > 1.0 to be profitable)

• Break-even CPA = AOV (you make $0 at this point)

• Margin at current CPA = (AOV − CPA) / AOV × 100

Step 6b: LTV:CAC Health Check

If LTV data is available, assess the pricing-level health of the campaign:

LTV:CAC Ratio Benchmarks:

Pricing Function Average LTV:CAC

No pricing function 1.68

Yearly pricing review 3.23

Continuous optimization 11.09

Interpret the ratio:

• < 1:1 — Losing money on every customer. Stop spending until unit economics are fixed.

• 1:1 – 3:1 — Marginal. Campaigns may appear profitable on front-end ROAS but are destroying value over time.

• 3:1 – 5:1 — Healthy. Scale greens confidently.

• 5:1 — Excellent. May be under-investing in acquisition.

Monetization impact reminder: A 1% improvement in monetization yields a 12.7% increase in bottom-line revenue — roughly 4x the impact of acquisition and 2x the impact of retention. If LTV:CAC is weak, the fix may be pricing, not ads.

Step 6c: Attribution Notes

When analyzing multi-channel campaigns, note attribution limitations:

• Single-channel campaigns: last-click is sufficient.

• Multi-channel campaigns: flag that attribution is approximate.

• Don't over-complicate analytics. The goal is action (red/yellow/green), not perfect measurement.

Step 7: Generate Scaling Recommendations

For each green ad, provide specific scaling numbers:

The 20% Rule:

• Current daily budget → recommended new budget (current × 1.2)

• When to apply: 48 hours after last budget change

• Next check-in date

For the overall campaign:

• Total daily spend recommendation

• Budget reallocation from reds to greens

• When to add new creatives to the mix

Output Format

Campaign Analysis

Date: [current date] Campaign: [campaign name or description] Period: [date range of data] Target CPA: $[amount] AOV: $[amount]

Traffic Light Summary

Campaign Health: [Healthy / Needs Attention / Critical] — [one sentence summary]

Ad-Level Grades

Benchmark Comparison

Creative Fatigue Alerts

[List any ads showing fatigue signals, or "No fatigue signals detected."]

Profitability

Overall ROAS: X.Xx Overall Profit/Conversion: $X

Action Items

Immediate (Today)

• Stop: [list red ads]
• Scale: [list green ads with specific new budgets]

This Week

• [Creative refresh, new tests, etc.]

Review Cadence

• Next daily check: [tomorrow]
• Next weekly review: [date]
• Next monthly review: [date]

Scaling Plan

Total daily spend: $X → $X (recommended)

Rules

• The grading method is deliberately binary. Red means stop, not "let's give it one more day." Kill losers fast and feed winners.

• Yellow is the discipline zone. Don't "optimize" yellows. Either there's enough data to judge or there isn't.

• The 20% rule exists because ad platforms optimize delivery around your budget. Jumping budgets overnight resets the algorithm's learning.

• CPA is the North Star, not CTR. A high-CTR ad that doesn't convert is worse than a low-CTR ad with great CPA.

• These benchmarks are starting points. After 2-4 weeks, your own data becomes the benchmark.

• If everything is red, the problem isn't the ads — it's the offer or the funnel.

• Creative fatigue is inevitable. Plan for it. Have your next batch of creatives ready before the current ones die.