Performance Foundation: Master the New Era of Search with Google AI

Business-focused summary (Google AI search ads: AI Max + Performance Max)

Core message / strategy

Search is shifting from information to intelligence, with growth driven by:

• AI summaries
• AI mode
• Multimodal/voice search

For advertisers, competitive advantage depends on being visible and relevant inside Google’s AI results, which requires:

• Strong measurement foundations
• Adoption of AI-powered search ads products (AI Max / AIAX and Performance Max / PMax)
• Scalable creative and landing-page alignment

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Frameworks / playbooks mentioned

Recommended 3-step ROI action plan (implied playbook)

1. Build measurement bases

   • AI operates based on your measurement; AI tools won’t perform without reliable, “foolproof” measurement.

2. Boost ROI with AI-powered solutions

   • Use AIAX / AI Max and Performance Max
   • Improve ROI with creative content, including the AI Brief

3. Optimize execution

   • Landing pages
   • Bidding/budget approach
   • Simplified campaign structure so AI can optimize effectively

Campaign simplification rules (operations playbook)

• Aim for one version of each campaign (avoid duplicate segmentation by match type/location)
• Each ad group focuses on a clear theme
• Have only one instance of each keyword in any match type
• Use experimentation, such as:
  • A/B test AI Max vs a baseline
  • Toggle features like Final URL Expansion in PMax

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AI products: what they do and how to choose

AIAX / AI Max (search-text-ad focused)

• Works in search inventory only (text ads in Google Search results)
• Key capabilities described:
  • Search term matching / keywordless intent capture (beyond exact keyword coverage)
  • Text personalization
  • Final URL expansion (AI selects the most relevant landing page per query/intent)

Performance Max (PMax) (cross-channel)

• Works across all Google channels (explicitly: YouTube, Gmail, Discover, Maps, etc.)
• Key capabilities described:
  • Keywordless targeting / AI-powered segmentation always on
  • Access to broader inventory than AIAX

Overlap / auction handling

• AIAX and PMax may be eligible for the same auction, but standard ad ranking rules still apply
• Exact match queries: described as having preference when the query exactly matches

Transition note

• DSA (Dynamic Search Ads) are expected to be phased out early next year
• Recommendation: experiment with Performance Max if you aren’t already using it

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Key AI mechanisms described (business execution details)

AI-powered segmentation (reach more intent)

• AIAX: search term matching (keyword → intent expansion)
• PMax: keyword targeting + keywordless segmentation
• Uses broad signals such as:
  • user history and what they browse/buy
  • device, time, location
  • combined with business signals (keywords, resources, landing pages)

Text personalization (creative optimization)

• Real-time variations based on user interests/context
• Uses existing ad assets (e.g., DSA resources/headlines) + generative landing-page information
• Update mentioned: ad personalization available for all languages globally
• Example use case:
  • Query about “hot sleeper” → create bamboo-sheet-specific titles/descriptions

Final URL expansion (landing-page optimization)

• Google AI crawls the site to choose the most relevant URL for the query/intent
• Controls/constraints exist
• Regulated industries note:
  • If Final URL expansion ignores asset pinning, propose using text disclaimers to keep legal text in the first description

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Controls to maintain governance while scaling (risk management)

Segmentation controls

• Negative keywords
• Location of interest (tight control; can reduce volume)
  • Useful for store/product availability by city/country (retail, travel, airlines, car rental)

Brand controls

• Inclusion/exclusion of branded traffic
• Guidance:
  • use brand controls carefully because they can limit search traffic
  • recommend starting with incrementality, then apply brand targeting

URL controls

• URL inclusion (e.g., lead gen form/contact page)
• URL exclusion (exclude low-value pages like blog/company homepage)
• Tradeoff:
  • too many URL controls can limit AI’s discovery and reduce performance

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Product feature updates / newer tooling (execution enablers)

Across AI Max + PMax (mentioned):

• Text guidelines
  • Exclude specific concepts/phrases (e.g., “cheapest”, “most affordable”, “free forever”)
• Total campaign budget
  • AI optimizes pacing toward goals across a defined time window (days/weeks/months) without daily manual maintenance
• Smart bidding exploration
  • Expanded to more campaign types
  • Later expansion noted for Shopping PMax with GMC feeds

AI Max specific:

• AI Brief
  • Provide brand guidelines, objectives, and audience goals “in your own words”
  • AI Summary shows example assets and searches to validate alignment
  • Existing text guidelines can migrate into AI Summary message guidelines
• Text disclaimers
  • Support regulated industries when Final URL expansion is enabled

PMax specific:

• Improved reporting features
• Exclusion of source audiences
  • Example rationale: focus spend on new customers (exclude recent converters/contact-form fillers) to shift budget toward acquisition rather than re-engagement

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Metrics & KPIs explicitly cited (from examples/results)

Performance benchmarks (system claims)

• AIAX: ~14% more conversions on average with similar CPA and ROAS
• PMax: ~9% increase in conversion value from Final URL expansion

Luxury Escapes (Australia travel) – 6-week proof of concept

• 10% increase in click traffic
• 11% increase in total conversions
• 10% increase in conversion value
• Approach:
  • AIAX + conversion-based bidding (value-based bids with target ROAS), plus:
    • negative keywords
    • comprehensive URL exclusions
    • geographic parameters
    • ad group-level locations of interest
    • text personalization to match long-tail intent

Greater China financial advertiser – generic campaign

• 860% increase in conversions
• Increased click coverage and voice share (market share objective)
• Approach:
  • AIAX with “Qless segmentation technology” / social matching (as described)
• Motivation:
  • expansion bottleneck; manual bidding/keyword expansion not sufficient

Other advertiser outcomes (generic success story)

• Better CTR
• Lower cost per conversion
• Longer dwell time per session
• Tested using an A/B testing framework with many AIAX functions enabled

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Actionable setup best practices (what to do)

Foundations (before AI)

Ensure measurement is aligned to conversion actions, such as:

• lead vs web conversions (example phrasing appears auto-transcribed, but intent is clear: configure conversion actions properly)

Also align:

• conversion goals
• bidding strategy
• budgets

Bidding/budget guidance

• Choose bidding strategy + flexible budget to capture opportunities
• Avoid overly tight bid-to-budget ratio

Landing page readiness

Optimize landing pages because AI selects/crawls content for:

• Final URL expansion
• creative relevance
• Keep the website up to date

Landing page + creative governance

Use:

• text guidelines
• message restrictions (carefully)
• text disclaimers in regulated industries

Governance guidance:

• Prefer concrete instructions (e.g., “use B, not A”)
• Avoid overly subjective/unrealistic claims (e.g., “generate 1000% ROI”, “make joy”)
• For region-specific audience messaging, create separate ad groups/campaigns if restrictions don’t support it

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Experimentation / optimization loop

• Run experiments with minimal errors:
  • single-click experimentation
  • A/B testing for AI Max and PMax features (e.g., enable Final URL expansion)
• After rollout, consult reports such as:
  • keyword report
  • search terms report
  • resource reports
  • landing page reports
• Use the insights for smarter optimizations

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Audience-specific execution examples

E-commerce / retailers (maximize sales) – 4 best practices

• Build a solid product/offer “database” and use value-based offers + improved conversions
• Simplify account structure:
  • organize ad groups by product categories
  • merge low-volume campaigns
  • remove duplicate keywords
• Take full advantage of text customization with diverse resources
• Use URL controls to send users to intended product pages

Lead generation businesses (maximize quality leads)

• Set lead goals in Google Ads
• Import offline data:
  • lead-to-sale process and value-centric measurement to tie advertising to business outcomes
• Improve contact forms:
  • validate submissions and reduce spam
• Optimize search campaigns after foundations are set

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Mentioned presenters / sources

• Chelsea Drews (Regional Product Lead, AI-powered solutions; Australia & New Zealand; focuses primarily on MMS e-commerce)
• Kaylee (Greater China-based Regional Product Leader; located in Hong Kong; focuses on lead generation business)
• Danish (DH) (Regional Product Lead for AI solutions; based in Singapore; primarily focuses on commerce)
• Larry Page (quoted; founder; referenced the “ultimate search engine” statement from 2000)

Case study clients referenced

• Luxury Escapes (Australia travel brand)
• Greater China financial advertiser (name not provided in subtitles; head of marketing “Kevin” quoted/referenced)