Launching a SaaS product into a paid acquisition strategy requires different AI Max configuration at each phase. Running AI Max the same way for a beta launch as for a scaled product misses the opportunity to use each phase's unique signals. This guide covers the 90-day arc from pre-launch to early scale.
Phase 1: Pre-Launch (Days 1-30)
Before your product is publicly available, paid advertising builds the waitlist and email list that become your launch day customer list.
Pre-launch AI Max goal: Email capture and early access signups. Not paid trials — the product isn't ready. Set conversion tracking on your waitlist form submission.
Campaign configuration:
- Conversion: Waitlist/early access form submission
- Bidding: Maximize Conversions (no CPA target — you're optimizing for volume to build list size)
- Budget: Conservative (15-25% of planned launch budget) — this is list-building, not revenue
- Asset groups:
- "Problem" group: Headlines focused on the problem you solve, not your solution
- "Solution" group: What your product will do, framed as a benefit claim
- "Insider access" group: Urgency + exclusivity of being an early adopter
Audience signals for pre-launch:
- Custom intent: Search terms your target users use when experiencing the problem
- Competitor in-market: Users researching alternatives to the category
- Job title intent: Industry professionals who would have this problem
Landing page requirement: A simple waitlist page. No pricing, no trial. Just the value prop, an email field, and social proof (founding team credentials, advisor logos, press mention if available).
What you'll get from this phase:
- An email list (your primary launch asset)
- Initial quality data on which audience signals produce signups
- CTR data on your messaging hypotheses
- Early conversion tracking verification
Phase 2: Beta/Limited Access (Days 31-60)
Selective invitations from your waitlist become paying beta users (or free-trial beta users). AI Max now has a new job: find more users like your beta cohort.
Beta phase AI Max goal: Trial starts for high-fit users, not all users.
Configuration change:
- Conversion: Trial start (not waitlist) + secondary conversion: Completed onboarding milestone (if you have one)
- Bidding: Maximize Conversions, then transition to Target CPA once you have 30+ trial starts
- Budget: Increase to 50% of planned launch budget
- Add customer match: Upload your beta user emails as audience signals. These are your highest-fit early adopters; find more like them.
New asset groups for beta phase:
- "Beta access" group: "Join [X] users already in early access," "See what's different"
- "Social proof" group: If you have early testimonials or case study data, this is the moment to deploy them
- Maintain "Problem" and "Solution" groups from Phase 1 with updated performance data
What signals to watch:
- Which waitlist subscribers converted to beta users (segment your waitlist by engagement and map against Google Ads GCLID data if possible)
- Which search term categories produce trial users who activate (complete onboarding vs. those who don't)
Phase 3: Full Launch (Days 61-90)
Public availability. Trial starts open to anyone. The goal shifts from careful selection to efficient scale.
Launch phase AI Max goal: Paid trial acquisition at or below target CPA.
Configuration at launch:
- Conversion: Trial start (primary) + paid conversion (when trial converts, import as offline conversion)
- Bidding: Target CPA (set at 20-30% above your current average CPA to give the algorithm room to scale without immediately hitting its ceiling)
- Budget: Full launch budget
- Update customer match: Add all beta users + converted paying customers as seed audience
Launch week tactics:
Apply a seasonality adjustment starting 2 days before launch date:
- Pre-launch: +30% expected conversion rate (demand is highest near launch)
- Launch day: +50%
- Post-launch week 1: +20%
- Return to baseline by week 2
This prevents AI Max from treating launch week demand as anomaly and pulling back bids during the highest-opportunity window.
Asset groups at launch:
- "Early traction" group: Social proof at scale ("1,000 users in week 1," "[Company] named it...")
- "Direct comparison" group: If you have comparison data against alternatives
- "Free trial offer" group: If you offer a specific trial duration/offer at launch
- Maintain top-performing pre-launch groups with updated creative
Post-Launch Optimization (Days 90+)
After the launch wave settles, you're running a mature SaaS acquisition campaign. The July 2026 ToS (https://yositeup.com/blog/google-ads-tos-july-2026-ai-automation-what-changed) applies to all SaaS claims — user count claims, growth rate claims, and performance claims must be substantiated.
Post-launch ongoing management:
- Monthly: Review which trial cohorts convert to paid at highest rates and import these offline conversions to AI Max
- Quarterly: Refresh audience signals based on what your best paid customers actually look like (segment customer data from CRM)
- 6 months: Evaluate whether Target CPA is still appropriate or if Target ROAS (using LTV-weighted conversion values) would drive better customer quality
Campaign Isolation: Launch vs. Evergreen
After launch wave, create a clean separation:
- Archive launch-specific campaigns (with launch urgency assets, beta messaging)
- Create evergreen campaigns with durable positioning
- Don't commingle launch and evergreen campaigns — launch campaign's learning phase data includes anomalous demand patterns that don't represent normal acquisition dynamics
The June 2026 reporting deletion (https://yositeup.com/blog/google-ads-reporting-data-deleted-june-2026) is relevant if your product launched during that period. Launch-period attribution data may be incomplete; use product-side analytics (signups from your own database) as the authoritative source for launch performance, not Google Ads data.
The AI Max Shopping migration (https://yositeup.com/blog/google-ai-max-shopping-replacing-performance-max-2026) isn't directly relevant for pure-play SaaS without physical products, but the same AI Max bidding principles apply. The DSA to AI Max migration (https://yositeup.com/blog/google-ads-dsa-ai-max-migration-february-2027) is relevant for SaaS companies that used DSA to cover blog content — post-migration, configure URL expansion to restrict paid traffic to conversion-focused pages only.
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