Free PPC

Toolkit

Overview

Reads pasted Google Ads data and returns experiments triggered by patterns actually visible in the account, not generic best practices. Walks a priority cascade from alignment fixes to scaling winners, stopping waste, efficiency tweaks, expansion, and creative refreshes. Every recommendation cites the metric that triggered it and includes a confidence score tied to sample size.

What you give it

• Campaign-level performance data; device, geo, search-term, and impression-share breakdowns add depth
• Target CPA or target ROAS
• Time period (30 days default, 90 days for more reliable patterns)
• Business type (lead gen, ecommerce, SaaS, local services)

What you get back

• Experiments grouped by the priority cascade: alignment fixes -> scaling winners -> stopping waste -> efficiency -> expansion -> creative
• Each experiment cites the triggering metric with thresholds (e.g. CTR >6% + CVR <1%, mobile CVR <50% of desktop)
• Sample-size verdict per recommendation, flags anything below the minimum data bar
• Confidence score (0.0-1.0) tied to conversion volume and pattern consistency
• Plain-English description of impact in dollar terms (revenue at stake, savings available)
• High/medium/low priority labels based on signal strength, execution complexity, and risk

How to use it

1. Export campaign data plus any segmented breakdowns (device, geo, search terms).
2. Paste it with your targets and time period.
3. Start with anything in the alignment section, fixing alignment makes other tests cleaner.
4. Run scaling and waste-cut experiments next; they tend to be quick wins.
5. Save creative-fatigue tests for last, they need exposure volume to read clean.