How much should I spend on Google Ads? (Real budget framework)

If you have to pick one number: start with 5-12% of your target revenue going into paid ads, split across Google and Meta. A $100k/month brand should test with $5-12k/month. A $1M/month brand often allocates $60-120k/month. Below this, you can't generate enough data to optimize. Related: cro.

The minimum viable budget

Google Adsneeds 15-30 conversions per month per campaign to optimize properly. If your CPA is $50, that means $750-1,500/month minimum per campaign. For a brand running 3-5 campaigns, that's $4-8k/month floor. Below that, Google's smart biddinglacks data to work.

Budget by growth stage

• →Pre-$500k ARR: $2-5k/month, focus on brand + best-converting keywords only.
• →$500k-$2M ARR: $5-15k/month, expand to category keywords and Performance Max.
• →$2M-$10M ARR: $15-50k/month, full-funnel including YouTube and Demand Gen.
• →$10M-$50M ARR: $50-200k/month, saturate branded + aggressive non-brand.
• →$50M+ ARR: $200k+/month, often with brand lift testing and MMM.

The margin test

If your gross margin is under 40%, Google Adscan work but you need laser focus on high-intent keywords and tight CPA targets. If your margin is over 60%, you can afford broader targeting and testing. Brands with under 25% margin should probably avoid Google Adsentirely until margins improve.

When to scale

Scale budget 15-25% per month when you're hitting target CPA consistently for 3+ weeks. Jumping 50-100% causes algorithm resets and inflated CPAs. Slow compounding beats aggressive doubling in Google Ads.

Frequently asked questions

Is this approach right for early-stage companies?

Most frameworks in this space assume a certain level of operational maturity, dedicated team members, established measurement infrastructure, some history of experimentation to build on. Pre-seed and seed-stage companies often lack these prerequisites and need a lighter-weight adaptation. For brands doing under $3M in annual revenue, focus on three or four of the principles that matter most for your specific business model rather than trying to implement the full framework at once. Rigor matters more than coverage at this stage.

How does this work for B2B versus B2C businesses?

The underlying principles around how much to spend on google adsapply across both contexts, but execution differs meaningfully. B2B paid ads typically has longer sales cycles, multiple stakeholders per deal, and consideration periods measured in months rather than minutes. Measurement frameworks need longer windows. Attributionbecomes more complex. The same core strategic logic applies, but the tactical implementation looks different. We've worked extensively in both contexts and can flex the approach accordingly.

What changes when we integrate this with existing systems?

Every implementation requires integration work, systems don't exist in isolation. Analytics platforms, CRM, email systems, ad accounts, BI tooling all need to talk to each other for this to work at scale. Plan for 2-4 weeks of integration work at the start of any implementation. Shortcutting this phase creates data quality issues that compound and undermine the entire program over 6-12 months. We've seen teams skip integration work to move faster, only to spend 6 months later reconciling measurement discrepancies that could have been prevented upfront.

When should we reconsider the approach?

Every 6 months, run a structured review against the principles outlined here. Ask whether the market has shifted meaningfully, whether your business model has evolved, whether competitive dynamics have changed. Frameworks should evolve with context. A rigid commitment to any specific approach, including ours, eventually becomes the problem rather than the solution. The teams that outperform long-term are the ones that update their operating model based on evidence, not the ones that defend past decisions.