In the ever-evolving world of digital advertising, the way we structure our search campaigns is undergoing a significant shift. What was once considered best practice – hyper-granular campaigns – might now be a hidden cost. This discussion dives into why simplifying your search campaigns is key to unlocking the full potential of AI Max and Smart Bidding, moving from chasing keywords to capturing intent across the entire customer journey.
Key Takeaways
- Control Evolves, It Doesn’t Disappear: In an AI-powered environment, control shifts from manual bids and single keyword ad groups to smarter controls like brand settings, geo-targeting, and high-quality conversion data.
- Keywords as Thematic Layers: Keywords are now more of a means to an end, acting as thematic signals to help Google understand the general intent of your ad groups and campaigns, rather than the sole driver of matching.
- Learning Periods Are Less Scary Than You Think: Many structural changes, like moving creatives between ad groups, shouldn’t trigger significant relearning periods because AI models focus on semantic features, not just campaign or ad group IDs.
The Evolution of Search Campaign Structure
For years, the standard approach to search advertising involved building meticulously detailed, hyper-segmented campaigns. This was a rational response to the limitations of manual bidding and the lack of sophisticated automation tools. Marketers had to split campaigns by match type, device, location, and more, using tiered bid sculpting to manage performance. While effective, this method was incredibly laborious, both to set up and to maintain.
However, the landscape has changed dramatically. With the rise of Smart Bidding, AI Max, and creative automation, the machine can now often outperform human management at scale. This has led Google to emphasize campaign consolidation, not as a goal in itself, but as an opportunity to achieve better performance with less effort.
Why Consolidation Matters Today
The core idea behind consolidation is that modern technologies allow for leaner, more efficient campaign structures. Instead of splitting campaigns to manage bids and ad copy manually, you can now rely on AI to handle these complexities. This shift means you can focus on aligning your campaign structure with your business goals rather than just your keyword lists.
When Does Segmentation Still Make Sense?
While consolidation is encouraged, it’s not a one-size-fits-all solution. Segmentation can still be logical in certain scenarios:
- Distinct Product Lines or Objectives: If different product lines have unique budgets and bidding goals, keeping them separate makes sense.
- Regional Focus: If your business operates with distinct regional budgets and management structures, replicating this in Google Ads can be beneficial.
- Alignment with Business P&Ls: The goal is to make your Google Ads structure align as closely as possible with how you run your business externally.
Redefining Control in an AI World
Concerns about losing control are common, but control simply looks different now. It’s less about manual bids and more about:
- Smart Bidding: Providing high-quality conversion data and accurate targets.
- Brand Control: Differentiating between brand and generic campaigns.
- Geo-Controls: Influencing query matching based on geographic intent.
Understanding Keywords and Intent
The role of keywords has also evolved. They are no longer just strict matching tools but are increasingly seen as signals of intent. This is particularly true with broad match and AI Max, where the focus shifts to understanding the user’s underlying need.
The Journey from Syntactic to Semantic Matching
Google has been moving towards semantic matching for years, recognising that user behaviour and information needs are becoming more complex. While exact match remains for tight control, products like AI Max are designed to capture broader intent and longer-tail queries that are difficult to enumerate manually.
Behind the Scenes: Continuous Improvement
It’s important to remember that query matching is constantly being refined. With the integration of LLMs, models can incorporate deeper intent signals, leading to matches that might seem unusual at first glance but are based on a more nuanced understanding of the query. Google is working on ways to expose these insights to advertisers.
Keywords in 2026: A Thematic Layer
When restructuring, the priority should be your business goals. Keywords then become a thematic layer to express the general intent you want to target within those goals. They help guide traffic to the right parts of your account but are not the end objective themselves.
Navigating Search Term Reports and Ad Group Theming
Seeing unexpected queries in your search term report can be concerning, but it’s an opportunity to be curious. As search behaviour shifts towards more complex and general queries, campaigns need to adapt.
Discovery and Early-Stage Intent
Search is no longer just a last-click channel. Campaigns should be able to serve users at different stages of their journey. This means:
- Query Matching: Ensuring matches across the full funnel of potential intents.
- Creative Customisation: Tailoring messages to resonate with users at various funnel stages.
- Smart Bidding: Differentiating between upper and lower funnel intent to ensure appropriate ROI.
If a query seems tangential, it might be priced appropriately, maintaining overall ROI.
Ad Group Theming: Still Relevant?
Yes, ad group theming remains important for segmenting traffic. The key is qualitative clarity: if you look at two ad groups side-by-side, is it clear they represent distinct concepts? If ad groups within the same campaign have similar landing pages and goals, it might be an opportunity for consolidation.
AI Max and Creative Controls
AI Max offers existing search campaigns an upgrade with features like search term matching, text customisation, and final URL expansion. Opting into these can lead to significant performance increases.
Trusting Generated Assets
Concerns about brand safety and relevance for generated assets are valid. Google is working to provide advertisers with more control:
- Text Customisation: Primarily grounded in landing page content.
- Final URL Expansion: Allows for control over inclusions and exclusions.
- New Controls (Beta): Features like term exclusions (negative keywords for assets) and matching restrictions (natural language prompts for creative copy) are being developed to give advertisers finer control over tone, messaging, and what to avoid.
Ad Group-Level Geo Settings
New ad group-level location settings help address ambiguity, especially with keywords containing location names (e.g., "hotels in London"). This provides clearer intent signals for matching and allows for more consolidated accounts.
Incrementality and Learning Periods
Driving Incremental Growth
Advertisers often worry that AI-driven campaigns might over-index on existing demand. To ensure incremental growth:
- Theming: Well-themed accounts reduce ambiguity.
- Brand vs. Generic Control: Use settings to create cleaner splits.
- Experimentation Tools: Google is developing better tools for A/B testing across campaigns to account for potential cannibalisation.
Understanding Learning Periods
- Substantive Changes: Adopting AI Max or changing bidding objectives will trigger a learning period.
- Cosmetic Changes: Consolidating ad groups within the same campaign or moving creatives between ad groups generally should not require significant relearning.
Data Density for Learning
Smart bidding typically needs around 15 conversions in 30 days. Using portfolio bid strategies or shared budgets can aggregate data across campaigns, helping models learn faster, especially in lower-conversion scenarios. Considering conversion actions further up the funnel can also provide valuable signals.
Migrating to a Modern Structure
For accounts with thousands of ad groups and years of history, the fear of performance damage during migration is real. The safest approach involves:
- Mapping Objectives: Start with your business goals and how they translate to Google Ads.
- Phased Rollout: Begin with lower-priority, lower-volume campaigns as a sandbox to test and iterate.
- Budget Consolidation: If campaigns share the same performance goals, consider shared budgets to allow budget to flow fluidly where it’s most effective.
Google is actively working to make its models robust against structural changes, aiming to minimise performance fluctuations.
Key Considerations for Mapping Your Structure
- Define Your Goals: What are your overarching business objectives?
- Thematic Breakdowns: How can you represent your business structure and marketing messages logically in Google Ads, remembering keywords are a means to an end?
- Be Curious and Test: Embrace new features like AI Max, explore bidding strategies, and experiment with creative controls. Don’t let fear of change hold you back.
What’s Next?
Google is focused on foundational quality improvements across query matching, bidding, and creatives. They are also exploring the evolution of search in the AI era, with exciting developments planned for later in the year. Advertiser feedback is crucial, and Google is committed to listening and responding to improve quality of life and address key advertiser pain points.
Community Q&A
Eligibility for AI Overviews and AI Mode:
To serve ads within AI overviews, Google considers both the user query and AI overview content. Broad match keywords or keyword lists in AI Max/PMax and Dynamic Search Ads are eligible. Even if exact match keywords are present, ads trigger based on deeper intent, not just exact query matching.
Exact vs. Broad Match in AI Overviews:
Previously, if an exact match keyword existed, it could prevent a broad match keyword from triggering in AI overviews. This has been updated: the presence of an exact match keyword will not prevent a broad match keyword from triggering an ad in an AI overview, as exact match keywords are not eligible for AI overviews themselves.
Unexpected Matches in AI Max:
Recent observations of unexpected matches attributed to AI Max, rather than keywords, have been investigated. In some cases, these occurred due to auto-complete suggestions in map searches. Standard keyword matching might miss these partial queries, but AI Max can connect them due to its ability to infer intent, especially in experiences like Lens and AI overviews. Google plans to improve transparency around these types of searches and update its help centre.
