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bid-optimization

Skill4 starsChanged 6 months agoMITView on GitHub

Recommends bid adjustments based on performance data. Use for CPC optimization, budget allocation, ROAS improvement, day-parting, device modifiers, and audience bid strategies.

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 2 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Never auto-applies bid changes

    line 14
  2. Very specific:

    Run scripts/analyze-bids.py with campaign export data:

    line 41
  3. Very specific:

    Run scripts/generate-script.py to create deployable JavaScript:

    line 60
  4. Distinctive:

    Create new script and paste code

    line 73

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Bid Optimization Skill

Analyzes Google Ads performance data and generates bid adjustment recommendations. Produces ready-to-use Google Ads Scripts based on Brainlabs patterns.

Safety Guardrails

Read-only by default. This skill:

  • Analyzes data and outputs recommendations only
  • Never auto-applies bid changes
  • Generates scripts that must be manually reviewed and pasted into Google Ads
  • Requires explicit user approval before any changes take effect

Optimization Strategies

Day-Parting (Hour-of-Day)

Adjusts bids based on hourly conversion performance. Identifies:

  • Peak conversion hours → increase bids
  • Low-performing hours → decrease bids
  • Uses 24/7 scheduling pattern from Brainlabs

Device Modifiers

Analyzes performance across Desktop, Mobile, Tablet:

  • Calculates CPA by device vs campaign average
  • Recommends bid modifiers within -90% to +300% range
  • Weights modifiers by conversion volume confidence

Audience Targeting

Optimizes bids for:

  • In-market audiences based on ROAS
  • Remarketing lists by conversion rate
  • Custom audiences by CPA performance

Workflow

1. Analyze Performance Data

Run scripts/analyze-bids.py with campaign export data:

python scripts/analyze-bids.py --input campaign_data.csv --output recommendations.json

Input formats supported:

  • Google Ads CSV export
  • Google Ads API JSON response
  • Google Sheets URL

2. Review Recommendations

The script outputs:

  • High CPA keywords to reduce bids (CPA > target × 1.3)
  • High ROAS keywords to increase bids (ROAS > target × 1.2)
  • Day/hour patterns with statistical significance
  • Device modifier recommendations
  • Estimated impact on spend and conversions

3. Generate Google Ads Script

Run scripts/generate-script.py to create deployable JavaScript:

python scripts/generate-script.py --recommendations recommendations.json --template day-parting

Templates available:

  • day-parting - Hour-of-day bid adjustments
  • device - Device bid modifiers
  • bid-adjustment - Keyword/ad group bid changes

4. Deploy (Manual)

  1. Copy generated script
  2. Open Google Ads → Tools → Scripts
  3. Create new script and paste code
  4. Preview before running
  5. Schedule for hourly execution

Templates

See templates/ folder for Google Ads Script templates:

  • bid-adjustment-template.js - Basic bid adjustment patterns
  • day-parting-template.js - 24/7 scheduling with hourly modifiers
  • device-bid-template.js - Device platform bid modifiers

Bid Modifier Bounds

Default safety limits:

  • Minimum: -90% (0.1x multiplier)
  • Maximum: +300% (4.0x multiplier)
  • Day-parting: -50% to +50% recommended
  • Device: -90% to +100% typical range

Data Requirements

For reliable recommendations:

  • Minimum 30 days of data
  • At least 30 conversions per segment
  • Statistical significance threshold: 95%

Low-data segments receive weighted modifiers to prevent over-optimization.

About this skill

Part of the Synter free skills collection — open-source agent skills for advertising, PPC, and marketing automation.

Want this skill (and 40+ more) running on autopilot against your live ad accounts? Try Synter — AI Agent Media Buyers that connect to Google, Meta, LinkedIn, TikTok, Reddit, Amazon, and 7+ more platforms.

Download now (ZIP)

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