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One of the major reasons PPC practitioners hold onto syntax-oriented keyword strategies is the disconnect between “query intent” and “conversion intent.” For years, you’ve likely relied on keywords to show you understand what your customers want and to prequalify traffic using syntax-oriented signals.

As user behavior shifts to more conversational queries and AI becomes an increasingly relevant part of the user journey, the distinction between these two intents becomes even more critical to understand and act on.

Here, we’ll define query and conversion intent and explore strategies to apply them effectively. This isn’t prescriptive. You should make decisions based on what will serve your business well. However, it provides a framework for analyzing your data and optimizing for the right humans.

Disclosure: I’m a Microsoft employee, and I’ll be sharing some examples that pull from Microsoft tooling. However, most of the strategies reflect platform-agnostic approaches.

What are query and conversion intents?

Query intent is the underlying need driving the text put into a search function. This search function can be on a SERP (search engine results page), video/social/gaming/email/site search bar, or AI surface.

Conversion intent is the human need to achieve some outcome, understood through stated and inferred data points. These range from text entered in various search experiences, content consumed, and tracked actions taken.

Different examples of query and conversion intent will have higher or lower rates of confidence based on how explicit text is, as well as patterns in content consumed.

For example, if I search “Microsoft ads login,” both query and conversion intent are clear — I want to log in. It’s easy to match ads and organic content to that query. Videos shown in any video query would have to do with logging in, and emails would be focused around login information.

Google SERP

Bing’s SERP

YouTube results

The query “Microsoft ads” is more nebulous, as such, needs to draw from other signals like previously engaged content and search history. While I might get a login page, I’d likely also see blog/sales content, third-party advice on Microsoft ads, and potentially competitor info trying to capitalize on the general nature of the query.

Google SERP

Bing SERP

YouTube results

Let’s look at a non-branded example as well. “Purple hair dye” has a clear transactional intent. While the user might not have a brand in mind, they know they want a specific color. 

We don’t know if the user is looking for a semi-permanent or permanent color. We also don’t know the user’s pronouns, so matching them to a specific demographic to entice a purchase is a gamble. 

Google SERP

Bing SERP

YouTube results

In the query “purple hair dye for long wavy hair,” the transactional intent is maintained. However, the query focuses more on the core needs of the person behind the text. Long, wavy hair means there needs to be enough dye to cover long hair.

Additionally, while some men have long wavy hair, the person behind the query is more likely to identify as female. 

Wavy hair has a different composition than straight or curly hair, so products specifically for wavy hair will be more relevant than those without hair type identifiers.

Google SERP

Bing SERP

YouTube results

In all of these examples, there was clear conversion intent. The human behind the query clearly wanted to achieve something. However, if we relied only on the text (i.e., query intent), we might miss a meaningful opportunity to connect with customers. 

This is why close variants (which have been available on both Google and Microsoft for ~10 years) represent a useful way to unshackle ourselves from syntax alone.

Additionally, by limiting our understanding of queries to SERPs, we ignore critical insights from where our customers connect, work, and play. Microsoft’s internal data from March 2024 shows that brands that use both Audience ads (display, native, and video) and Search see a 6x conversion rate. Part of this is brand recognition, and the power of brand media buys influencing performance.

Yet there’s also the pragmatic piece that some marketers refuse to engage with video and social. By being where your competitors refuse to be, you can shape and capture desire while they fight over a shrinking share of voice.

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How to optimize for each intent

Once you understand the difference between query and conversion intent, you can begin mapping out the actions needed to capitalize on both.

Conversion intent is much easier to understand than query intent. This is why AI systems typically run queries in the background to understand human input and get at the conversion intent behind the query. 

To succeed at shaping queries and capturing conversions, it’s critical to understand the input points for humans and the AI systems that will be serving them results.

Let’s revisit the “purple hair dye for long wavy hair” query:

Copilot surfaces how it arrived at the output by looking up information and finding the best matches. This is similar to the SEO concept of E-E-A-T.

Yet you’ll notice that the results for my personal Copilot are different than the traditional SERP (chiefly that ads aren’t the dominant result — ads serve at the bottom of clearly transactional conversations after organic listings).

This is where the “Details” function comes into play and can help you know where to focus content, feed, and messaging functions:

This product is pretty flat on price, save for some deep summer dips. If I’m desperate for color, I might buy now, or I might wait for what seems like a regular summer sale. I’m also getting insights into why this product is wonderful (hair conditioning, cruelty-free, vibrant, and customizable color, etc.).

These are things I’ve shown interest in through past purchases, conversations with Copilot, and other signals it has access to.

Brands that want to optimize for query intent need to make sure the following are in good order:

• Feed/landing page clarity
  • It should be incredibly easy to map what the product/service is to the query. While there is value in some 1:1 matching of language, it’s much more important that the core offering be understood as aligned with what the human is looking for.
  • For example, DUI and DWI are technically two different charges and have geo implications. However, DUI tends to be the universal legal charge and service.
• Images adding context
  • Visual content is critical to engage humans. However, if the image isn’t clear or is duplicative of another service/product page, you might confuse the user and the machine attempting to understand and position you for queries. This is why it’s critical to add alt text (even on paid landing pages) for images and videos.
  • A good way to test whether your visuals are serving you well is to put the landing page into a PMax campaign creator. If you see the images and they match the correct service text, you’ve done a good job.
• Invest time in understanding how humans and AI are querying
  • Free tools like Google Trends, Microsoft Clarity, and Bing Webmaster offer insights into search trends, citations, grounding queries, and which AI systems and humans are successfully engaging with your content.

Conversion intent is more straightforward, though debatably harder because it requires more creative and critical thinking: 

• Matching messages to personas
  • The reason one person says yes to you might be completely different from the reason someone else does. Locking in conversion intent includes being mindful of how you’re selling yourself. If you ignore what matters to your customers in reviews, intake from customer success or sales, and other signals, you risk selling yourself badly and losing the customer.
  • This is where AI-powered creative and audience mapping can be helpful, since platforms have access to more insights than a brand does during the auction.
• Honor the impulse nature of visual content
  • Someone coming to you from a display spot or short video is very different than someone coming from a text-laden SERP. They were inspired to act and need frictionless paths to conversion.
  • One-click checkout (including solutions like Copilot Checkout) ensures humans don’t need to think to do business with you.

Ultimately, both query and conversion intent need brand and performance marketing to be successful, and it’s critical to understand how the success metrics manifest.

The converging roles of brand and performance

For a long time, brand and performance marketing were treated as separate motions, with separate owners, budgets, and success metrics. 

• Brand was about reach, recall, and long-term connection. 
• Performance was about efficiency, conversion rate, and immediate return. 

That separation made sense when channels, measurement, and user journeys were cleaner than they are today. It’s much harder to maintain in an environment where AI systems infer intent continuously and across surfaces. 

A user doesn’t experience brand and performance as separate. They experience confidence, familiarity, relevance, and ease. Those signals are created over time through exposure, engagement, and trust, and they often determine whether conversion intent ever materializes, regardless of how “high intent” a query might appear on its own.

From a metrics perspective, this convergence is clear. Brand-oriented activity influences performance outcomes even when it isn’t the final touch. Exposure to display, native, or video doesn’t always produce an immediate click, but it changes how humans and systems interpret future behavior. 

When someone later performs a search, engages with an AI assistant, or compares options on a marketplace, prior brand interactions act as accelerators. They reduce hesitation, shorten decision cycles, and increase the likelihood that a conversion signal will be credited downstream.

From a strategy standpoint, this means brand work should no longer be evaluated solely on isolated upper-funnel KPIs, and Performance work can’t be evaluated purely on last-click efficiency. 

Audience-based formats, contextual placements, and visual storytelling directly shape conversion intent by shaping preferences and expectations before a query even occurs. Search and shopping formats then serve as capture mechanisms, translating that latent intent into action.

This is particularly relevant in AI-assisted experiences, where systems synthesize multiple inputs before presenting options or recommendations. Content, feeds, reviews, images, and historical engagement all influence how brands are represented and when they appear.

In these environments, strong brand signals don’t compete with performance outcomes. They enable them by making the brand easier to understand, trust, and choose.

Brand and performance don’t need to use the same tactics, but they must be planned together. Measurement frameworks should account for assistive value, not just final interactions.

Creative strategies should recognize that inspiration and conversion often happen at different moments. Optimization should focus less on forcing intent into rigid buckets and more on supporting the full decision journey.

When we recognize that query intent and conversion intent are related but not identical, the convergence of brand and performance becomes less a philosophical debate and more an operational necessity.

Success comes from designing systems that reflect how humans actually decide, not just how they type.

Key takeaways

• Query intent describes what is said; conversion intent reflects what the human needs to accomplish. They overlap, but they aren’t interchangeable.
• Brand activity shapes conversion intent long before a query is expressed and influences how future interactions are interpreted.
• Performance outcomes improve when Brand signals reduce friction, uncertainty, and choice overload.
• AI-driven experiences amplify this convergence by relying on cumulative signals rather than single actions.
• Sustainable optimization requires aligning brand and performance strategies, metrics, and expectations around the same human outcomes.

Google is enforcing a hard cutoff for older API versions, meaning advertisers and developers who don’t upgrade risk losing access to critical campaign management tools.

What’s happening. Google Ads API v20 will officially sunset on June 10, 2026. From that date onward, all requests to v20 will fail, requiring migration to a newer version to maintain uninterrupted API access.

Why we care. If you rely on the Google Ads API and don’t upgrade in time, automated workflows — including reporting, bidding and campaign management — could suddenly stop working. This could lead to data gaps, performance issues and operational disruption. Migrating early ensures continuity and avoids last-minute fixes that can impact campaign performance.

What to do. Google is urging users to upgrade as soon as possible and provides resources like release notes and upgrade guides to support the transition. Developers can also use the Google Cloud Console to review recent API activity, including which methods and versions their projects are calling.

Between the lines. API sunsets are routine, but the impact can be significant for advertisers relying on custom scripts, tools or third-party platforms. Missing the deadline could disrupt reporting, bidding or campaign automation workflows.

The bottom line. This is a firm deadline with real consequences: upgrade to a newer Google Ads API version before June 10 or risk losing access entirely.

Over the past few years, Performance Max has gone from an opaque experiment to a more capable — though still imperfect — campaign type for B2B marketers.

The fundamentals haven’t changed: skepticism still matters, first-party data is critical, experimentation is non-negotiable, and actionable reporting drives optimization. What has changed is how much better Google has gotten at operationalizing those inputs.

That means your Performance Max strategy needs to adapt. Here are five best practices for running more effective PMax campaigns for B2B today.

1. Guide AI with the right inputs

In 2022, given the automated nature of PMax campaigns and the aggressive way Google reps were pushing them, I predicted we’d see an accelerated move toward AI integration. That’s certainly played out, probably in part because of competitive pressures introduced by ChatGPT and the like. 

AI Max for Search (launched in 2025) and PMax are both being prioritized by Google, and that’s not necessarily a bad thing since Google hasn’t deprecated standard Search campaign for B2B and has provided a slew of helpful updates that make PMax more viable for B2B. 

Three updates worth using include: 

• Search themes, which are useful for more precise targeting.
• Brand exclusions, which help minimize CPC inflation and over-investment on less-incremental queries.
• Account-level channel reporting, which gives you a single dashboard look at performance across campaigns. For this feature, segment by conversion metrics to drill down on ROI by channel. You’ll quickly see overperformers where you can increase investment and underperformers that cry out for further optimization or reduced budget.  

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2. Address persistent lead quality issues

B2B lead quality in search campaigns has always been a challenge, and PMax’s relative lack of advertiser control makes that challenge tougher. I’ve pushed offline conversion tracking (OCT) since we’ve had that capability, but it’s an absolute non-negotiable for B2B campaigns.

Along with OCT, leverage a relatively new functionality, enhanced conversions for leads, and work around the edges by incorporating reCAPTCHA and testing other mechanisms to reduce PMax spam leads.

Dig deeper: The parts of Performance Max you can actually control

3. Build stronger audience signals

Citing the phase-out of third-party cookies that still hasn’t happened (!), Google officially sunsetted Similar Audiences in 2023, which — well, it was a big loss for advertisers.

To compensate, understand and adapt according to the nature of PMax targeting, which is based on audience signals. Feed the AI high-quality first-party data (CRM lists) and let the algorithm find “lookalikes” through its own internal signals.

CRM lists for B2B are obviously critical, and this should give you even more incentive to clean up and segment CRM data, with audience lists closest to the point of revenue (e.g., SQLs or revenue if you don’t have enough closed-won data to send strong signals), especially valuable for finding high-value new users.

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4. Make creative a performance lever

Creative is an important part of the puzzle for PMax. Good creative can prompt the right audience to engage, and great creative can deter the wrong audience from engaging.

Because YouTube is now a massive part of PMax campaigns, video — which has never been a B2B strength — should be prioritized more than ever for performance marketing.

Google has made this easier by adding the ability to build AI-generated assets right in the Google Ads interface. Just recently, they launched an important complementary feature in beta: PMax A/B creative testing to help advertisers understand which creatives are actually driving performance, and to use test-and-control structures to surface winning (and losing) elements.

Dig deeper: Is Google Ads Asset Studio a game changer? Not so fast

5. Use reporting to drive decisions

A major source of frustration with PMax has been a lack of transparency into results. Over the last few years, Google has introduced reporting updates to address some of those concerns.

Search term insights and auction insights in the Insights tab provide more visibility into performance. Search term insights show how your ads perform for the queries users actually type, including how those ads are being matched and served. This added nuance makes optimization more precise.

Auction insights add competitive context, showing how your campaigns perform against others in the same auctions through metrics like impression share and outranking share.

Finally, asset-level reporting brings visibility to creative performance, with data on impressions, clicks, cost, and conversions for each asset.

Together, these updates give you a clearer view into what’s driving performance — and where to focus optimization efforts.

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Make Performance Max work for you

Taken together, recent updates make PMax more viable for B2B marketers than it used to be, especially for those with strong first-party data to train bidding algorithms and a need to find new customer pockets.

After more than 10 years in marketing, I still prefer having controllable levers — and I’m not willing to fully trust Google to act more in my (or my clients’) best interests than its own. Use everything at your disposal to make PMax campaigns work for you, and keep an eye out for new features Google releases that can give you more visibility and control over your account performance.

Dig deeper: Auditing and optimizing Google Ads in an age of limited data

Google is filling a key measurement gap between awareness and consideration, giving advertisers a clearer view of how their brand is actually perceived — not just remembered.

What’s new. Google Ads has introduced a new “Association” metric within Brand Lift Studies. Advertisers can define a concept, category or attribute, and Google will ask users a survey-style question: which brands they associate with that specific idea.

How it works. Instead of measuring simple recall, the metric evaluates whether audiences connect your brand to a desired positioning. That could mean “premium,” “sustainable,” or even a product category — offering a more nuanced read on brand perception.

Why we care. Google is giving you a way to measure brand positioning, not just awareness or recall. The new Association metric helps determine whether campaigns are actually shaping how consumers perceive a brand — a critical step between being known and being chosen. It also enables more strategic optimization of creative and messaging, especially for brands trying to own specific attributes or categories.

Between the lines. Brand Lift has traditionally focused on awareness, recall and consideration. Association sits in between, helping advertisers understand whether their messaging is shaping how people think about the brand, not just whether they recognize it.

The catch. There’s still a constraint: advertisers can only select three Brand Lift metrics per study, so adding Association means making trade-offs with existing KPIs.

The bottom line. Association gives advertisers a more strategic lens on brand building — measuring not just visibility, but whether campaigns are landing the intended message.

First seen. This update was first spotted by Google Ads expert, Thomas Eccel who shared the update on LinkedIn.

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As AI Max turns 1, we’re helping you capture even more opportunities in the expanding Search universe.

Google is doubling down on AI-driven ads just as search behavior shifts toward conversational queries, giving advertisers more automation while trying to preserve control.

What’s new.

AI Max expands beyond Search: Now rolling out to Shopping campaigns and travel-specific formats, broadening reach across more advertiser types.

AI Brief (powered by Gemini): A new interface that lets advertisers steer AI using natural language inputs.

Text disclaimers + URL automation: Compliance-friendly updates to pair with automated landing page selection.

Why we care. Google is making AI Max a core layer across Search, Shopping and Travel, meaning automation will increasingly determine how ads are matched to user intent. This update expands reach into more conversational, high-intent queries that traditional keyword strategies miss, helping brands capture demand earlier in the journey.

At the same time, tools like AI Brief and new compliance features give advertisers more control over messaging and targeting, reducing the risk of fully automated campaigns feeling like a “black box.”

Shopping gets smarter. For retailers, AI Max for Shopping uses Merchant Center data to generate more adaptive ads that can respond to long-tail and exploratory queries, helping brands appear earlier in the discovery phase rather than only at the point of purchase. The rollout is positioned as a simple upgrade for existing Shopping campaigns, suggesting Google wants rapid adoption.

Travel gets consolidated. Travel advertisers get a consolidation play. Search Campaigns for Travel bring previously fragmented formats into a single interface with unified reporting and integrated AI Max capabilities. The move reduces operational complexity while reinforcing Google’s push toward centralized, AI-driven campaign management.

More control with AI Brief. The most notable addition is AI Brief, which attempts to solve a long-standing advertiser concern: lack of compliance control in automated systems. Advertisers can define messaging rules, specify which queries to prioritize or avoid, and shape how different audiences are addressed. The system then generates previews, allowing feedback before campaigns go live.

Automation meets compliance. Google is refining how traffic is directed to websites. Final URL expansion uses AI to select the most relevant landing page for each query, and the new text disclaimer feature ensures required legal messaging remains intact even when automation is active. This signals a push to make AI usable in more regulated industries without sacrificing compliance.

The bottom line. AI Max is evolving from a Search add-on into a foundational layer across Google Ads, combining automation, cross-format reach and advertiser input to adapt to a more AI-driven, conversational search landscape.

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