The Post-Keyword PPC Strategy: How to Structure Search Campaigns When Google Matches Intent, Not Just Keywords

For nearly two decades, PPC worked on a simple principle: you chose keywords, Google matched them to search queries, and you paid when someone clicked. The advertiser controlled targeting. The platform executed it.

That model is gone. Here is what replaced it.

Broad match now uses AI to understand query meaning, not just query text. A keyword like "PPC agency" can match queries like "who manages Google Ads campaigns for small businesses" because Google interprets the intent as equivalent. The matching is semantic, not lexical.

AI Max goes further. It reads your landing pages, analyses your conversion data, and proactively finds query categories your keyword list does not cover. Your keywords become a starting signal, not a boundary. For a detailed look at AI Max, read our guide on the AI Max DSA migration.

Performance Max has no keywords at all. Google's algorithm decides which queries to target based on your creative assets, audience signals, and conversion history. The advertiser provides inputs. The AI makes targeting decisions.

The common thread: Google's algorithm, not your keyword list, now determines which searches trigger your ads. This is not a subtle shift. It changes how campaigns should be built from the ground up.

Single keyword ad groups (SKAGs) and exact match strategies were designed for a world of literal matching. You chose the keyword, Google showed the ad for that keyword and close variants, and you could predict which queries would trigger which ads.

When Google interprets intent rather than matching text, these structures create three problems.

Overlap and cannibalisation. Multiple ad groups with similar keywords now compete against each other because Google sees them as targeting the same intent. Your own campaigns bid against themselves, driving up costs and confusing the algorithm about which ad to show.

Wasted granularity. Managing 200 ad groups with one keyword each made sense when each keyword had distinct matching behaviour. When broad match interprets all of them as variations of the same intent, you are doing ten times the management work for the same result as a single well-structured ad group.

Starved learning. Smart Bidding needs conversion data to optimise. Spreading traffic across hundreds of tiny ad groups means none of them accumulate enough data for the algorithm to learn effectively. Consolidation gives the AI the signal volume it needs.

The fix is not to abandon structure entirely. It is to restructure around how Google actually matches queries in 2026.

Instead of organising campaigns by keyword lists, organise them by buyer intent stage. This aligns your campaign structure with how Google's AI already thinks about queries.

Research campaigns target users who are exploring a problem but have not decided on a solution. Queries like "how to reduce Google Ads costs" or "is PPC worth it for small businesses" signal early-stage intent. Bid conservatively, use informational landing pages, and measure engagement (time on site, pages per session) alongside conversions.

Comparison campaigns target users evaluating options. Queries like "PPC agency vs in-house" or "best Google Ads management companies UK" signal mid-funnel intent. Use comparison landing pages, case studies, and social proof. Bid moderately with a focus on lead generation.

Purchase campaigns target users ready to buy. Queries like "hire PPC agency" or "Google Ads management pricing" signal high intent. Use your strongest landing pages, highest bids, and tightest conversion tracking. Every click here should have a clear path to becoming a lead or sale.

Within each campaign, ad groups represent intent themes rather than keyword buckets. An ad group for "agency selection" might contain keywords like "PPC agency," "Google Ads management," and "paid search company" because they share the same buyer intent, even though they are different keywords.

This structure gives Smart Bidding clearer signals. Each campaign has a consistent intent level, so the algorithm can optimise bids appropriately rather than trying to reconcile research queries and purchase queries in the same campaign.

Broad match is Google's most powerful and most dangerous match type. Used correctly, it finds high-intent queries you would never have thought to target. Used without safeguards, it bleeds budget on irrelevant traffic.

The safeguards that make broad match work:

• Smart Bidding is mandatory. Broad match without Smart Bidding is reckless. The algorithm needs automated bid adjustments to compensate for the wider query matching. Use Target CPA or Target ROAS, never manual bidding with broad match
• Strong conversion tracking. Smart Bidding optimises towards whatever you tell it is a conversion. If your conversion tracking counts page views or button clicks alongside real leads, broad match will happily find cheap traffic that triggers those low-value conversions. Track only meaningful business outcomes
• Comprehensive negative keywords. Broad match will find queries that look semantically related but are commercially irrelevant. A PPC agency bidding on "Google Ads" with broad match will attract queries about Google Ads certifications, Google Ads jobs, and Google Ads tutorials. Negatives are your only defence
• Regular search term reviews. Check your search terms report weekly for the first month, then fortnightly. Add irrelevant queries as negatives. Look for patterns, not just individual queries
• Sufficient conversion volume. Smart Bidding needs roughly 30 conversions per month at the campaign level to optimise effectively. If your campaigns convert less frequently, broad match is harder to control because the algorithm lacks data to learn from

If your PPC management setup lacks any of these safeguards, fix the foundations before expanding to broad match.

AI Max adds queries your keywords do not cover. That is its entire purpose. The risk is that it adds queries you would not have chosen, spending budget on traffic that looks relevant to Google's AI but does not convert for your business.

Three controls that keep AI Max expansion productive:

Landing page relevance. AI Max reads your landing pages to understand what you offer. The clearer and more specific your pages are, the better AI Max matches queries to your actual services. Vague, generic pages attract vague, generic traffic. Detailed, service-specific pages attract qualified prospects.

Negative keywords. AI Max respects campaign and account-level negatives. Use them aggressively. Every irrelevant query you spot in your search terms report should become a negative, both the specific query and the broader theme it represents.

Conversion signal quality. AI Max optimises towards your conversion goals. If your conversion tracking records low-quality actions (form spam, internal traffic, micro-conversions), AI Max will find more traffic that triggers those low-quality actions. Clean conversion data is the single most important input.

For a complete breakdown of AI Max mechanics and migration preparation, see our AI Max DSA migration guide.

In the old keyword-based model, landing pages mattered for Quality Score and conversion rate. In the post-keyword model, landing pages matter for targeting itself.

Google reads your landing pages to understand what you offer. AI Max and broad match both use landing page content as a signal for query matching. This means your landing pages are no longer just conversion assets. They are targeting inputs.

What this means in practice:

• A landing page about "PPC management for e-commerce" will attract e-commerce queries. A generic "PPC management" page will attract everything
• Pages with clear service descriptions, specific industries, and defined geographic areas give the AI precise signals about which queries to match
• Pages with thin content, vague descriptions, or outdated information send weak signals, leading to broader and less relevant matching
• Every landing page you link to in your ads becomes a targeting signal. Choose pages deliberately, not just based on conversion rate, but based on what traffic they will attract

If you are not sure whether your landing pages are sending the right signals, a PPC landing page audit will identify gaps between what your pages say and what traffic they attract.

In a post-keyword world, what you exclude matters more than what you include.

When you controlled targeting through exact match keywords, you defined a narrow set of queries to appear for. Irrelevant traffic was limited by the precision of your keyword list.

With broad match and AI Max, Google decides which queries are relevant. Its definition of "relevant" is broader than yours. The AI sees semantic relationships between queries that may not reflect commercial relevance. A query about "Google Ads certification" is semantically related to "Google Ads management" but commercially irrelevant to an agency selling management services.

Negative keywords are now your primary targeting control. They define the boundaries of where AI can and cannot take your budget.

Build negatives across these categories: job and career terms, educational queries, DIY and free alternatives, competitor brands you do not want to appear for, services you do not offer, and geographic areas you do not serve.

Download our free negative keyword list template with 500+ pre-built negatives organised by category. It is the fastest way to build a defensive foundation for broad match and AI Max campaigns.

When you cannot fully control which queries trigger your ads, your ad creative becomes a filtering mechanism. The right creative attracts qualified clicks and repels irrelevant ones.

Responsive search ads let Google assemble combinations of your headlines and descriptions. The AI selects which combination to show based on the query, the user, and the context. This means your headlines and descriptions are not just persuasion tools. They are qualification tools.

Write headlines that signal who your offer is for, not just what you offer. "PPC Management for B2B Companies" is more qualifying than "PPC Management Services." The former tells a B2C searcher this is not for them. The latter attracts everyone.

For a deeper look at how creative strategy has changed in the age of AI-driven targeting, see our guide on why creative is the new targeting.

The post-keyword PPC strategy comes down to five shifts:

1. Structure by intent, not keywords. Campaigns organised by buyer journey stage (research, comparison, purchase) instead of keyword groupings
2. Consolidate for data. Fewer, larger ad groups that give Smart Bidding enough conversion data to optimise effectively
3. Invest in landing pages. Your pages are targeting inputs, not just conversion assets. Make them specific, current, and aligned with the intent you want to capture
4. Defend with negatives. Exclusions are now your primary control lever. Build comprehensive negative lists and review them regularly
5. Use creative to qualify. Write ads that attract the right clicks and repel the wrong ones, because Google will show your ads to audiences broader than your keyword list

This is not about giving up control. It is about moving your control to the inputs that matter in 2026: conversion data, landing page quality, negative keywords, audience signals, and creative strategy. For the full picture of how AI is reshaping PPC, see our AI PPC Playbook 2026.