Budget Allocation & Bidding Strategy

Process

1. Collect budget and performance data across all active platforms
2. Read ads/references/budget-allocation.md for allocation framework
3. Read ads/references/bidding-strategies.md for strategy decision trees
4. Read ads/references/benchmarks.md for CPC/CPA benchmarks
5. Read ads/references/scoring-system.md for health score algorithm
6. Evaluate budget allocation, bidding strategy, and scaling readiness
7. Generate recommendations with kill list and scale list

Budget Allocation Framework

70/20/10 Rule

• 70% on proven channels (consistent ROAS/CPA targets met)
• 20% on scaling channels (showing promise, need more data)
• 10% on testing channels (new platforms, audiences, creatives)

Platform Selection Matrix

Business Type	Primary	Secondary	Testing
SaaS B2B	Google Search, LinkedIn	Meta, YouTube	TikTok, Microsoft
E-commerce	Google Shopping, Meta	TikTok, YouTube	Microsoft, LinkedIn
Local Service	Google Search, Google LSA	Meta	Microsoft, YouTube
B2B Enterprise	LinkedIn, Google Search	Meta	Microsoft, TikTok
Info Products	Meta, YouTube	Google Search	TikTok
Mobile App	Meta, Google UAC	TikTok	Apple Search Ads
Real Estate	Google Search, Meta	YouTube	Microsoft
Healthcare	Google Search	Meta	Microsoft, YouTube
Finance	Google Search, Meta	LinkedIn	Microsoft
Agency (clients)	Varies by client	—	—

Budget Sufficiency Rules

Platform	Minimum Daily	Learning Phase Budget
Google Search	$20/day	Sufficient for 15+ conv/month
Google PMax	$50/day	Sufficient for algorithm optimization
Meta	$20/day per ad set	≥5x target CPA per ad set
LinkedIn	$50/day Sponsored Content	15+ conversions/month
TikTok	$50/day campaign, $20/day ad group	≥50x target CPA per ad group
Microsoft	No strict minimum	Sufficient for stable delivery

Bidding Strategy Evaluation

Google Ads Bidding Decision Tree

Start
├─ <30 conversions/month?
│  └─ Use Maximize Clicks (cap CPC at benchmark)
│     └─ When >30 conv/month → Maximize Conversions
├─ 30-50 conversions/month?
│  └─ Use Maximize Conversions
│     └─ When stable CPA → Target CPA
├─ >50 conversions/month?
│  └─ Use Target CPA
│     └─ When revenue tracking → Target ROAS
└─ Revenue tracking active + >50 conv/month?
   └─ Use Target ROAS

Meta Ads Bidding

• Lowest Cost (default): best for volume, may have CPA variance
• Cost Cap: sets CPA ceiling, may reduce volume
• Bid Cap: maximum bid per auction, most control
• ROAS Goal: target return on ad spend
• CBO vs ABO: CBO for proven campaigns, ABO for testing

LinkedIn Bidding

• Cost Per Send (CPS): for Message Ads
• Maximum Delivery: for Sponsored Content (recommended)
• Manual CPC: for tight budget control
• Target Cost: for predictable CPA

TikTok Bidding

• Lowest Cost: maximize conversions within budget (volume)
• Cost Cap: set maximum CPA (efficiency)
• Bid Cap: maximum bid per impression
• Budget ≥50x CPA per ad group for learning phase exit

Microsoft Bidding

• Mirror Google strategy but bid 20-35% lower
• Enhanced CPC for manual campaigns
• Target CPA / Target ROAS for automated

Scaling Assessment

Ready to Scale (Green Light)

• CPA consistently below target for 2+ weeks
• ≥50 conversions per week (learning phase exited)
• CTR stable or improving
• ROAS above target
• No creative fatigue signals

20% Rule

Never increase budget by more than 20% at a time:

• Week 1: $100/day → $120/day
• Week 2: $120/day → $144/day
• Week 3: $144/day → $173/day
• Monitor 3-5 days after each increase for performance stability

Scaling Methods

1. Vertical: increase budget on winning campaigns (20% rule)
2. Horizontal: duplicate winning campaigns to new audiences
3. Platform expansion: add budget on new platforms
4. Geographic expansion: test new markets/regions
5. Format expansion: test new ad formats on same platform

Kill List Assessment

3x Kill Rule

• Any campaign/ad group with CPA >3x target → flag for pause
• Review spend in last 14 days with no conversions → flag for pause
• Creative with CTR >50% below platform benchmark → flag for creative kill

Kill Decision Framework

Scenario	Data Required	Action
CPA >3x target	≥7 days data, ≥20 clicks	Pause immediately
No conversions	≥$100 spend or ≥50 clicks	Pause and diagnose
CTR <50% of benchmark	≥1,000 impressions	Kill creative, test new
ROAS <50% of target	≥14 days data	Reduce budget 50% or pause

MER (Marketing Efficiency Ratio)

MER = Total Revenue / Total Marketing Spend

• Assess blended efficiency across all platforms
• Target MER varies by business: 3x-10x depending on margins
• Use MER to evaluate overall health, not just per-platform ROAS
• Incrementality testing recommended for MER accuracy

Output

Budget & Bidding Assessment

Budget Allocation Health

Allocation Strategy:  ████████░░  XX/100
Bidding Strategies:   ██████████  XX/100
Scaling Readiness:    ███████░░░  XX/100
Budget Sufficiency:   █████░░░░░  XX/100

Deliverables

• BUDGET-STRATEGY-REPORT.md — Full allocation and bidding analysis
• Current vs recommended budget split (pie chart data)
• Bidding strategy recommendations per platform/campaign
• Scale list: campaigns ready for more budget
• Kill list: campaigns/ad groups to pause immediately
• MER analysis and trend
• Quick Wins for immediate budget optimization

HYROS-Adjusted Budget Decisions (Optional)

When output/hyros_data.json is available, use HYROS true attribution for budget decisions:

True ROAS for Kill/Scale

• Use HYROS true ROAS instead of platform-reported ROAS for kill/scale decisions
• A campaign showing 3x ROAS in-platform may only be 1.5x ROAS in HYROS (over-reported)
• Conversely, some campaigns under-reported by platforms may show strong HYROS ROAS

Adjusted 3x Kill Rule

• Use HYROS CPA instead of platform CPA for more accurate kill decisions
• Platform CPA may understate true CPA due to modeled/view-through conversions
• Flag campaigns where HYROS CPA is >3x target even if platform CPA looks healthy

True MER Calculation

• Recalculate MER using HYROS-verified revenue: True MER = HYROS Revenue / Total Spend
• Compare True MER against platform-reported MER to quantify over-reporting impact

True Budget Allocation

• Recommend budget reallocation based on HYROS attribution data
• Shift spend from platforms with high over-reporting to platforms with accurate or under-reported ROAS
• Flag campaigns where HYROS and platform disagree significantly (>30% variance)

Platform	Platform ROAS	HYROS True ROAS	Variance	Recommendation
Google	X.Xx	Y.Yx	Z%	Scale/Maintain/Kill
Meta	X.Xx	Y.Yx	Z%	Scale/Maintain/Kill
TikTok	X.Xx	Y.Yx	Z%	Scale/Maintain/Kill
LinkedIn	X.Xx	Y.Yx	Z%	Scale/Maintain/Kill

If HYROS data is NOT available, skip this section entirely.