Marketing Analytics Audit
Score funnel health from KPI data in metric: value form. Produces a
0-100 score, an A-F grade, and prioritized recommendations.
Prerequisites
pip install -r requirements.txt
(Or, if the repo is installed as a package: pip install -e .)
Procedure
Normalize the user's metrics into metric: value lines:
visitors: 10000
conversions: 300
spend: 2000
revenue: 12000
ltv: 120
clicks: 5000
impressions: 100000
Recognized metrics include: visitors, conversions (orders/sales/signups/
leads), spend, revenue, clicks, impressions, ltv, cac, cpa, cpc, ctr, churn,
subscribers.
Run the audit:
python -m marketing_kit.cli analytics --file metrics.txt --format json
Read the output. details includes computed conversion_rate_pct,
cac, ltv_cac_ratio, roas, and ctr_pct; findings flags problems.
Summarize for the user, ranked highest-severity first:
- Conversion rate and whether it is healthy (3-5%+ is strong).
- Unit economics: CAC, LTV:CAC (should be 3:1+), ROAS (2:1+ to be safe).
- CTR and what it says about the creative.
Recommend next actions tied to the numbers:
- Low CVR → run
marketing-cro on the page.
- Low CTR → refresh hooks and creative.
- Low ROAS/LTV:CAC → tighten targeting and retention.
Notes
- If no
metric: value lines are present the engine returns a score of 0 with
a clear error — ask the user for their numbers first.
- Dollar signs, commas and trailing
% are handled automatically.
1---2name: marketing-analytics3description: Audit marketing funnel health from KPI data — conversion rate, CAC, LTV:CAC, ROAS and CTR — producing a 0-100 score, A-F grade and prioritized recommendations. Use when the user shares campaign metrics or asks to analyze marketing performance, KPIs, a funnel, or ad results.4---56# Marketing Analytics Audit78Score funnel health from KPI data in `metric: value` form. Produces a9**0-100 score**, an **A-F grade**, and **prioritized recommendations**.1011## Prerequisites1213```bash14pip install -r requirements.txt15```1617(Or, if the repo is installed as a package: `pip install -e .`)1819## Procedure20211. **Normalize the user's metrics** into `metric: value` lines:2223 ```24 visitors: 1000025 conversions: 30026 spend: 200027 revenue: 1200028 ltv: 12029 clicks: 500030 impressions: 10000031 ```3233 Recognized metrics include: visitors, conversions (orders/sales/signups/34 leads), spend, revenue, clicks, impressions, ltv, cac, cpa, cpc, ctr, churn,35 subscribers.36372. **Run the audit:**3839 ```bash40 python -m marketing_kit.cli analytics --file metrics.txt --format json41 ```42433. **Read the output.** `details` includes computed `conversion_rate_pct`,44 `cac`, `ltv_cac_ratio`, `roas`, and `ctr_pct`; `findings` flags problems.45464. **Summarize for the user**, ranked highest-severity first:47 - Conversion rate and whether it is healthy (3-5%+ is strong).48 - Unit economics: CAC, LTV:CAC (should be 3:1+), ROAS (2:1+ to be safe).49 - CTR and what it says about the creative.50515. **Recommend next actions** tied to the numbers:52 - Low CVR → run `marketing-cro` on the page.53 - Low CTR → refresh hooks and creative.54 - Low ROAS/LTV:CAC → tighten targeting and retention.5556## Notes5758- If no `metric: value` lines are present the engine returns a score of 0 with59 a clear error — ask the user for their numbers first.60- Dollar signs, commas and trailing `%` are handled automatically.
FreeAutomation-Tech