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PPC / SEM Tips for Franchises: A Guide for Google Ads

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Key Takeaways

  • Franchise PPC campaigns must balance brand consistency with local customization to maximize ROI.
  • Geo-targeting improves conversion rates by refining ad reach at the city, state, or neighborhood level, reducing wasted spend.
  • A strong keyword strategy combines branded terms for brand protection and non-branded terms for customer acquisition.
  • Budgeting and bidding strategies impact cost efficiency, whether corporate manages the budget, franchisees control their own spend, or both share responsibility.
  • Tracking key metrics like click-through rate (CTR), conversion rates, and return on ad spend (ROAS) helps refine campaigns and increase returns.
  • AI-powered campaign types like Performance Max and AI Max for Search now drive franchise PPC performance, including placement inside AI Overviews, so campaign structure and ad copy quality matter more than ever.

If you’re running a franchise, keeping your brand consistent while still letting each location shine is the lifeblood of your business. That’s where franchise pay-per-click (PPC) advertising can help.

With PPC advertising, you can drive targeted traffic, generate leads, and increase visibility at national and local levels. It’s also a tried-and-true strategy, even as Google Ads becomes more AI-driven. Recent changes like the rollout of AI Max for Search campaigns, the planned upgrade of Dynamic Search Ads (DSA) into AI Max, and the phaseout of Enhanced cost-per-click (CPC) are giving marketers new opportunities, but also creating some uncertainty around control, campaign structure, and optimization. PPC can still get entrepreneurs to where they want to go, but unlike single-location businesses, franchises face unique hurdles. 

Who controls the budget—corporate or franchisees? How do you maintain a unified brand voice while personalizing ads for different locations? And how do you prevent franchisees from competing against each other for the same keywords?

The key to franchise PPC is strategy. I’ve worked with franchise brands running anywhere from 10 locations to more than a thousand, and the ones that win at PPC all have a clear system for who runs what. Whether you’re managing campaigns at the corporate level, giving franchisees control, or using a hybrid model, the goal is to maximize ROI without wasting ad spend.

This guide breaks down everything—from keyword research and geo-targeting to budget allocation and tracking success—so your franchise can dominate paid search.

Understanding the Franchise PPC Model

Franchise PPC campaigns can be structured in three ways: corporate-managed, franchisee-managed, or hybrid. Each has its strengths and drawbacks. Choosing the right one depends on your brand goals and market dynamics.

Corporate-Run PPC Campaigns

When the corporate office manages paid search for franchises, the focus is on brand consistency and centralized control. Ads are uniform, budgets are allocated from the top, and campaigns are optimized at scale. This is great for brand protection and cost efficiency, but it can limit franchisees’ ability to target local customers effectively.

Franchisee-Managed PPC Campaigns

This model allows individual franchisees to run their own PPC campaigns, giving them full control. While this improves local relevance, it can lead to inconsistencies in brand messaging and even keyword competition between franchise locations, driving up costs unnecessarily.

Hybrid Model

The hybrid model is often the best approach. The brand’s corporate office provides creative guidelines and high-level oversight, while franchisees have control over local targeting and budget allocation. This keeps brand messaging consistent while giving franchisees room for local customization, maximizing reach and conversions.

No matter which model you choose, effective PPC management for franchises requires maintaining a consistent brand experience while allowing room for local customization. A scattered franchise PPC strategy weakens performance, but a structured, well-coordinated approach can deliver strong, measurable results.

Keyword Research for Franchise PPC

PPC success starts with choosing the right keywords. For franchise paid search, this means striking a balance between national reach and local relevance. You need to target high-intent keywords that attract both broad and location-specific searches.

Branded vs. Non-Branded Keywords

Branded keywords (e.g., “Subway near me,” “McDonald’s delivery”) are essential for protecting brand visibility and driving customers already looking for your franchise. These should be managed by corporate to prevent franchisees from bidding against each other, thereby unnecessarily increasing costs. They are also essential for competitor defense and general brand visibility at the national/corporate level.

A Google search for “McDonald’s near me”

Non-branded keywords (e.g., “best sandwich shop in New York,” “affordable fast food in Austin”) help capture new customers who aren’t searching for a specific franchise. These are great for local franchisees to target because they drive discovery and increase conversion rates.

A Google search for “affordable fast food in Austin”

Competitor Bidding Strategy

Another strategy is bidding on competitor names. If someone searches for a rival franchise, your ad can appear alongside it. This can work well but must be done carefully. Some brands have strict policies against it, and any bidding here will incur an expensive CPC penalty for targeting their brand terms. A less risky tactic would be to bid for your competitor’s keywords. 

Automating Keyword Optimization

Managing franchise PPC keywords at scale can be time-consuming. Tools like smart bidding in the Google Ads platform help optimize bids, adjust keyword strategies, and reduce manual effort while keeping campaigns competitive.

Google’s AI Max is also a great tool for automating your keyword strategy. The platform offers keywordless targeting, which automatically matches your ads to relevant searches without manual keyword lists. For franchise campaigns, AI Max can expand reach efficiently, but it needs strong negative keyword lists and tight geographic controls to prevent ads from serving outside location boundaries or on irrelevant queries.

Structuring PPC Campaigns for Multi-Location Franchises

A well-structured franchise PPC campaign does more than allocate budget. It organizes ad groups, targeting settings, and landing pages to optimize performance across locations. Even within a corporate-run, franchisee-managed, or hybrid model, campaign structure determines how efficiently ads are served, how budgets are spent, and how local audiences are reached.

Here are the best approaches to structuring franchise PPC campaigns:

1. Account-Level Structuring

Franchise PPC accounts can be structured in one consolidated account managed by corporate or in separate accounts for each location:

  • Single corporate-managed account: This keeps control centralized and simplifies brand consistency, but can make local customization harder.
  • Individual franchisee accounts: These allow each location to tailor targeting, but can cause inconsistencies if not monitored closely.
  • Hybrid approach: A corporate account oversees strategy while franchisees manage localized campaigns within sub-accounts.

2. Campaign-Level Structuring

Inside each account, campaigns should have one of the following structures to avoid overlap and increase relevance:

  • Location-Based Campaigns: Each franchise location gets a dedicated campaign, making it easier to customize keywords, ads, and bids based on regional search trends.
  • Service-Based Campaigns: Useful for franchises that offer multiple services (e.g., cleaning, landscaping, tutoring). This ensures budget is distributed based on service demand.
  • Audience-Based Campaigns: Dividing campaigns based on customer behavior (e.g., new vs. returning customers) helps tailor messaging and bidding strategies.

3. Ad Group Structuring for Multi-Location Targeting

Within each campaign, ad groups should reflect specific keyword themes to improve relevance and quality scores:

  • Geo-Specific Ad Groups: If running a campaign for multiple locations, create ad groups that focus on specific cities, neighborhoods, or service areas.
  • Product/Service Ad Groups: Organizing by offerings helps franchises with diverse services or menu items.
  • Competitor Ad Groups: Bidding on competitor keywords? Keep those in a separate ad group to monitor performance without affecting broader campaigns.

4. Budget & Bidding Considerations in Multi-Location Campaigns

Even with the right structure, budget allocation determines success:

  • Corporate-Level Budgeting: A set monthly budget allocated per location based on search volume, competition, and past performance.
  • Performance-Based Budgeting: High-performing locations receive more ad spend, while low-performing areas get optimized for better efficiency.
  • Geo-Bidding Adjustments: Locations in highly competitive markets may need higher bids to remain visible, while locations in lower-competition areas can reduce bids to improve efficiency.

Performance Max and AI Max for Franchise Campaigns

Performance Max and AI Max for Search are changing how companies build franchise PPC campaigns. Performance Max distributes your assets across several Google channels using Google’s AI, which makes it useful for franchisees who want broad local reach without juggling separate campaigns. AI Max layers search term matching and asset optimization onto traditional Search campaigns, giving you stronger query coverage without the manual keyword bloat.

Both shifts tie into Google’s planned DSA upgrade to AI Max, which begins for Automatically Created Assets (ACA) and broad match campaigns in September 2026 and rolls out to remaining DSA starting in February 2027. If you rely on DSA to fill keyword gaps for franchise locations, now is the time to test AI Max directly. Run both in parallel for 30 to 60 days so you have performance data before the forced migration hits.

My recommendation is to start with AI Max on your highest-performing Search campaigns, then test Performance Max for new market expansion.

Geo-Targeting and Localized Ads

Franchise PPC campaigns must reach the right audience at the right location. Geo-targeting makes that possible by serving ads only to users in specific areas, reducing wasted spend and increasing conversions, like the McDonald’s example below.

Geo-targeted McDonald’s ads.

Source: https://www.hunchads.com/blog/ad-localization-complete-guide

Types of Geo-Targeting for Franchise PPC

  • Radius Targeting: Serves ads to users within a set distance from a franchise location. Useful for local foot traffic and service-based franchises.
  • City-Specific Targeting: Targets users searching within a particular city. Ideal for franchises with multiple locations in a metro area.
  • State-Level Targeting: Broadens reach to an entire state. Best for franchises with fewer locations but strong statewide demand.

Geo-targeting works best when ads speak directly to the local audience. A franchise in Chicago shouldn’t use the same ad copy as one in Miami. Location-specific language, offers, and landing pages improve engagement and conversion rates.

Performance Max and AI Max support location targeting, but the behavior differs from standard search. For franchise campaigns, set “Presence: People in or regularly in your targeted locations” rather than “Presence or interest” to minimize geographic bleed. Verify in your campaign reports that impression share is concentrated in intended service areas to get the best results.

Best Practices for Localized Ads

  • Include city or neighborhood names in ad headlines and descriptions.
  • Use call extensions with local phone numbers.
  • Customize landing pages with location-specific offers, hours, and testimonials.

A franchise PPC campaign that combines precise geo-targeting with tailored ad content will always outperform a generic nationwide campaign.

Budgeting & Bidding Strategies for Franchise PPC

Franchise PPC success depends on spending the right amount in the right places without wasting budget. Competitive markets require higher bids to stay visible, while lower-competition areas may need less aggressive spending. A flexible budget model helps high-performing locations scale up while reallocating funds from underperforming areas.

Whichever budget structure you chose earlier (corporate-controlled, franchisee-managed, or hybrid) should inform how you bid. Corporate-controlled budgets give you centralized spending power and stronger brand consistency but less local flexibility. Franchisee-managed budgets let individual locations invest more aggressively in high-performing markets, but risk inconsistent spend and execution. The hybrid model splits the difference: corporate sets budget floors, ceilings, and guardrails, and franchisees adjust within those limits based on local performance data.

Focus your bidding strategies on driving efficiency within that framework.

Bidding Strategies for Franchise PPC

  • Automated Bidding: Adjusts bids based on performance trends, optimizing cost per acquisition (CPA) and ROAS. Google deprecated Enhanced CPC for Search and Display campaigns in March 2025, so the Smart Bidding strategies most franchises rely on now are Target CPA, Target ROAS, Maximize Conversions, and Maximize Conversion Value. 
  • Competitor Bidding: Targets users searching for rival franchises, though this must be done strategically to avoid legal and brand reputation issues.
  • Seasonal Bidding Adjustments: Allocates more budget during peak seasons (e.g., holiday promotions, summer sales) to maximize conversions.
  • Geo-Bidding: Helps franchises spend more in competitive markets while reducing bids in areas with lower competition, improving cost efficiency.

A smart budget allocation and bidding strategy helps franchises optimize ad spend, scale campaigns, and drive better ROI without unnecessary waste.

Ad Copy & Landing Page Best Practices

A great PPC ad gets clicks. A great landing page turns those clicks into customers. Franchise PPC campaigns need ad copy that stays on-brand while feeling local. Generic ads won’t convert, and mismatched landing pages frustrate users. A seamless experience from ad to landing page improves engagement and conversion rates.

Best practices for franchise PPC ad copy include:

  • Stay consistent: Adhere to brand voice while adding local relevance.
  • Use localized CTAs: Instead of “Visit Our Store,” try “Get Fresh Pizza in Dallas Today.”
  • Highlight unique value: Mention promotions, delivery options, or local perks.
  • Include location extensions: A physical address and phone number improve trust and CTR.
  • A/B test: Try out different headlines, CTAs, and layouts to identify what converts best in each location. One format note: Responsive Search Ads (RSAs) are now the only standard Search ad format available, since Google retired expanded text ads in 2022. RSAs let you supply up to 15 headlines and four descriptions, and Google’s AI rotates the best-performing combinations. Google also now offers AI-generated headline and description suggestions directly inside the RSA builder, which can speed up creative testing for franchises managing dozens of location-specific ads.

Franchises looking to scale PPC efforts without managing every aspect in-house can also work with experienced PPC agencies to optimize ad copy, landing pages, and conversion rates.

Since landing pages typically are your last touch point before customers make a buying decision, you’ll want to make sure they’re well-optimized. Key landing page features you should focus on include:

  • A headline that matches the ad copy for continuity.
  • Location-specific details (address, phone, hours, testimonials) for credibility.
  • Fast load speed (under three seconds) to prevent drop-offs.
  • Clear CTA (buy, book, call, get directions, etc.) that drives action.
  • Mobile-friendly design, since most franchise PPC traffic comes from mobile users.

This example from Cinnabon showcases their newest product with an attention-grabbing headline, an easy way to find your location, and a clear CTA to order.

An ad from Cinnabon marketing their Refresher beverages.

Source: https://www.webfx.com/industries/franchises/website-examples/

Ads in AI Overviews: What Franchise Advertisers Need to Know

Paid ads now appear integrated inside AI-generated overview summaries at the top of search results. These placements are served through existing Google channels like Search, Shopping, and Performance Max campaigns with no separate setup required, as long as you’re using AI-powered targeting.

This matters for franchises because local service and product queries often trigger AI Overviews. A location bidding on “best [service] near me” may see its ad appear inside an AI Overview rather than in a traditional ad slot. Ad copy quality carries more weight in this placement, so location-specific headlines and offers tend to outperform generic brand copy when sitting alongside synthesized content.

You don’t need to optimize separately, but you should monitor impression share by placement type in your campaign reports to understand how much traffic is coming from this format.

It’s also worth keeping an eye on adjacent formats. OpenAI began testing sponsored placements in ChatGPT for free and lower-tier users in early 2026, while Perplexity pulled its ad experiment over trust concerns. Franchise paid strategies will increasingly need to account for these surfaces as they mature.

Tracking & Measuring PPC Success for Franchises

PPC success is about conversions, revenue, and long-term customer value.  When you’re focusing on PPC or other paid strategies, you’re actually in the realm of search engine marketing (SEM). It’s an important distinction, because the metrics that matter differ from SEO vs. SEM, so tracking the right ones ensures franchise owners use their ad spend to support the factors that are critical to improving their ROI.

Essential PPC metrics for franchises include:

  • CTR: Measures how compelling ads are. A low CTR means weak ad copy or irrelevant targeting.
  • Conversion Rate (CVR): Tracks how many clicks turn into leads or sales. A high CTR with a low CVR signals a problem with landing pages.
  • ROAS: Shows how much revenue ads generate compared to spend. A low ROAS means budget needs reallocation.
  • Cost Per Acquisition (CPA): Helps gauge efficiency in converting leads. Lower CPA = better ad performance.
  • Customer Lifetime Value (CLV): Helps franchises determine how much they can afford to spend on acquiring a customer and optimizing long-term profitability.

Use these tools for tracking franchise PPC:

  • Google Analytics: Tracks user behavior after clicking ads.
  • Call Tracking Software: Monitors phone leads from PPC.
  • CRM Integration: Connects PPC data to sales and customer retention.

Here’s what success could look like:

Let’s say a multi-location fitness franchise wanted to improve its PPC performance. Instead of running a one-size-fits-all campaign, they could restructure their strategy to separate local and national efforts.

Here’s how a campaign like that might play out:

  • Refined geo-targeting to focus ads on high-intent local audiences, reducing wasted spend.
  • Customized ad copy for each location, incorporating city names and locally relevant promotions.
  • Adjusted keyword bidding by prioritizing high-converting terms while lowering spend on broad, expensive keywords.
  • Optimized landing pages to match ad messaging, streamlining the user experience and boosting conversions.

As a result, their ROAS jumped 45 percent in three months, while landing page improvements increased conversion rates by 20 percent. This structured approach enables franchises to scale PPC campaigns effectively while maintaining brand consistency and driving local results.

Accurate attribution is getting harder as third-party cookies are becoming less popular. Originally, Google was in favor of full-on deprecation of cookies. While that decision has since been reversed, Google is still taking a “user choice” approach to data tracking.

For franchise campaigns, configure enhanced conversions at the location level rather than only at the account level. Server-side tagging through Google Tag Manager can make conversion tracking more reliable by routing conversion data through a server container before it’s sent to Google. This helps reduce reliance on browser-based tags, which can be limited by client-side tracking restrictions and may undercount leads.

Common PPC Mistakes Franchises Should Avoid

Franchise PPC campaigns often fail due to avoidable mistakes. Here are the biggest issues and how to fix them:

  • Poor Budget Allocation: A one-size-fits-all budget doesn’t work for franchises. Some locations face higher competition and need more aggressive ad spend, while others may waste budget on low-converting keywords.
    • Fix: Use performance-based budget allocation. Analyze conversion rates and ROAS by location and shift funds to high-performing areas while cutting spend where PPC isn’t delivering results.
  • Ignoring Local Customization: Corporate-managed campaigns often miss local intent. A gym franchise running the same ad nationwide might work in some cities, but local markets have different customer expectations.
    • Fix: Allow location-specific ad copy while keeping branding consistent. Franchisees should have input on promotions, seasonal messaging, and localized offers to improve engagement.
  • Competing Against Other Franchisees: Franchisees bidding on the same keywords without structured coordination drives up costs and reduces ROI.
    • Fix: Use keyword exclusions and bid limits to prevent franchisees from competing against each other. Corporate can manage branded keywords while franchisees focus on non-branded, local intent keywords.
  • Skipping Negative Keywords: Without negative keywords, franchises waste ad spend on irrelevant traffic. A fast-food franchise bidding on “best burgers” might get clicks from job seekers looking for fast-food jobs.
    • Fix: Regularly update negative keyword lists to filter out job-related searches, competitors’ names, and non-converting terms.
  • Ignoring Performance Data: PPC isn’t set it and forget it. Many franchises keep spending on underperforming campaigns because they fail to track key metrics.
    • Fix: Use automated bidding and AI-driven optimizations to adjust bids in real time. Leverage Google Analytics, call tracking, and CRM integrations to connect PPC efforts to actual sales.
  • Over-Relying on AI Campaign Automation Without Geographic Controls: With Performance Max and AI Max, campaigns can serve ads outside location boundaries if targeting is set to “presence or interest” rather than “presence” only.
    • Fix: Audit geographic impression distribution monthly and implement location-based negative targeting where ads are appearing in unintended areas.

Franchise PPC can drain budgets or fuel business growth. The difference comes down to eliminating these mistakes, making data-driven adjustments, and refining strategy over time.

FAQs

Is Google Ads good for franchises?

Yes. Google Ads works well for franchises because you can run brand-level campaigns alongside location-specific ones, capturing both broad awareness and high-intent local searches. The platform’s geo-targeting and ad customizers make it easy to serve the right offer to the right market without building hundreds of separate accounts.

How do you use Google Ads for franchise marketing?

Structure your account around your franchise model. Use a corporate-managed account with sub-campaigns per location or give each franchisee their own account under a manager account (MCC). Lean on location extensions, geo-targeting, and shared budgets to keep things efficient.

How do you set up a PPC campaign for a franchise location?

Start with location-specific keywords, set a tight geo-radius around the franchisee’s service area, and write ad copy that includes the city or neighborhood. Connect Google Business Profile for location extensions, then layer in call tracking to attribute leads back to the right unit.

How do franchisees keep up with SEO and SEM algorithm changes?

Subscribe to Google’s Search Central blog and follow industry sources like Search Engine Land. Better yet, partner with an agency that monitors changes for you, so updates get tested before they affect performance.

Conclusion

Franchise PPC in 2026 comes down to three things: structured campaigns, local targeting, and consistent measurement. The fundamentals haven’t changed, but the tools have. Performance Max, AI Max, and ads inside AI Overviews are reshaping how franchise locations compete for clicks, and the brands that adapt fastest will capture the most value.

If you’re managing PPC for a single franchise location or coordinating campaigns across hundreds, the playbook is the same. Match your campaign structure to your management model, keep ad copy locally relevant, and track the metrics that tie spend to revenue.

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Best Practices for Writing SEO Title Tags

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Key Takeaways

  • Google rewrites 76 percent of title tags as of Q1 2025, often when titles are too long, keyword-stuffed, or misaligned with the page’s H1.
  • Title tags remain the second most important ranking factor in Google’s algorithm, and the HTML version still influences ranking even when Google rewrites the displayed title.
  • The sweet spot for title tag length is 51 to 60 characters, which carries the lowest rewrite rate across large-scale analyses.
  • In 2026, your title tag works in two places: driving clicks in traditional SERPs and acting as a citable label inside AI Overviews.
  • Audit your existing titles by impressions and CTR. High-impression, low-CTR pages are your fastest wins.

Google rewrites 76% of title tags as of 2025, and AI Overviews are changing how title tags function even beyond click-through. They may not be the most exciting part of the SEO jigsaw puzzle, but if you want to drive organic traffic to your website, getting them right is vital.

Even Moz says, “Title tags are the second most important on-page factor for SEO, after content.” They’re a quick win if you want to supercharge your SEO strategy.

If you’re looking for a boost in the search engine results pages (SERPs), keep reading. I’ll share my title tag best practices to help improve your visibility across traditional Google rankings and AI Overviews.

What Is a Title Tag?

A page title tag is the headline that represents your web page in the SERPs.

Your meta tags are important because they work with your meta description (the text below the title tag) to tell potential customers about your page content. 

Let’s say you’re searching for “kitchen installation services.” One of the top results is IKEA, with the title tag “Kitchen installation services.”

Google results for “kitchen installation services,” demonstrating IKEA’s title tag. 

This is an excellent title tag, as it clearly explains the page’s purpose and aligns with IKEA’s brand.

There are two reasons why page title tags are so important:

First, if you have a clear title that’s relevant to your page, both humans and search engines will see that as a sign of a good page.

If your title tag SEO isn’t on point, people could skip over your content, and search engines may determine that your page isn’t as good as it could be.

A second reason why title tags are important is that they appear in browser tabs and are used when people share your pages on social media. Get your title tag right, and it can help your content stand out.

IKEA’s title tag, “Kitchen installation service: a recipe for success,” displayed in browser tab format. 

Now that you have the definition down, the next question is how to write meta title tags for SEO that actually earn the click.

How to Write an Effective Title Tag

If you want to increase your chances of ranking on the first page of Google, a well-crafted, unique SEO title tag can help boost your odds. Recent data shows that an SEO-optimized title tag is the second most important ranking factor in Google’s algorithm. 

A pie chart breaking down the weight each ranking signal carries in Google’s overall algorithm for 2025.

Source: https://firstpagesage.com/seo-blog/the-google-algorithm-ranking-factors/

Here are some SEO title tag best practices to help you nail the elements that’ll drive traffic.

1. Get the Length Right

Data shows that your title tag needs to be between 50 and 60 characters. This is the sweet spot that had the lowest amount of rewrites from Google (39 to 42 percent), because it coincides with the way Google truly measures your title tag: pixels. The sweet spot is 580 pixels, which aligns with the 50-60-character limit.

You also won’t be able to tell the search engines and potential customers what your page is about if it’s too short. Too long, and the search engines will cut off your title tag with an ellipsis (…).

A Google search result for Missy Empire’s Women’s Clothing page that shows the SEO title tag being cut off by the ellipsis. 

Some tools can help you see how your meta title tag will look in the search engine results and check your word count. One of my favorites is the Mangools SERP simulator.

Mangools SERP simulator homepage.

The HTML version of your title tag is also still important. You’ll want to abide by the pixel or character limit for display, but your HTML version still matters for ranking and relevance signals, even if your display version gets rewritten. 

2. Front-Load Your Target Keyword

For best results, try to put your focus keyword as close to the beginning of your title as possible.

This means search engines (and search engine users) will quickly see that your page is relevant.

Let’s look at “buy red shirt” as our focus keyword. These title tag examples use that keyword right at the start, increasing the chances of that all-important click.

Google search results for the focus keyword “buy red shirt.”

You’ll also want to make sure you’re using the right version. Check the Parent Topic in a keyword tool to ensure you’re using the highest-traffic version of the keyword, not just the most obvious one. You can also optimize for more than one keyword by incorporating the right keyword variants and synonyms into your title tag.

You could change your title tag from only including “cheap hotels” to including “affordable, cheap hotels and rooms,” for example, to catch more than one variant.

Keyword research tools are a great resource for finding and analyzing different versions of a single focus keyword.

Google Search Console, Moz’s Keyword Explorer, and SEMrush are just a few useful, easy options to choose from.

With SEMrush, for example, all you have to do is search your keyword and navigate over to the “Related Keywords” tab.

SEMrush’s Related Keywords report for “affordable hotels.”

From there, you can see information for the keyword(s), like organic search volume, the cost-per-click (CPC), statistics on competition and trends, and more.

Scroll down to find a list of related words.

The tool will analyze how closely “related” a keyword really is based on a 0-100 percent scale, the ranking difficulty, the total number of results for those words, and trends.

A list of keyword variants of “affordable hotels” in SEMrush. 

Of course, it’s vital to ensure that keyword placement is organic, no matter which variant you use. While using them is great, don’t shoehorn them in just to get a placement. It’s against title tag best practices to stuff keywords into your title. Yes, you can optimize for multiple variants, but only if it sounds natural. 

3. Show the Benefit or Value

You need to use your title tag to show how you provide value. What do customers get when they click on your page?

This benefit can depend on what you sell and what stage of the sales funnel customers are at (search intent). If you’re targeting people who are looking for information, you need to show what they can learn from your content.

I like this title tag – “12 Ways to get Heatless Curls Fast.” It’s enticing and shows that you can get results quickly.

A Google result for Luxy Hair Extensions with the title tag “12 Ways to get Heatless Curls Fast” demonstrates how your title tag should highlight your product or service’s benefits to customers.

Targeting people who are ready to buy? It pays to be concise. What are you selling, and what does the product offer?

While this title is a bit long, I like it because it says the product is customized for short, fine hair. None of the other results say this, which makes this title tag stand out. 

A Google result for the Dyson Airwrap sets itself apart by saying the product is customized for short and fine hair, while competitor entries don’t. 

If your page doesn’t provide what you promise in your meta page title, customers will get frustrated, and Google could rewrite your title tag, so don’t be deceptive. 

4. Use Power Words, Modifiers, and CTAs

A power word is highly persuasive and can trigger an emotional response in your customers. When used in your title tag SEO, they can encourage people to check out your pages!

Using a power word in your meta title tags is a fantastic way to get attention and boost your click-through rates. 

Here’s a brilliant example. This title tag could have easily been “50 top tips for changing how you cook,” but Taste of Home has gone with “50 secrets chefs won’t tell you.”

That sounds a lot more intriguing!

Here are some power words to get you started:

  • Free
  • New
  • Easy
  • Imagine
  • Instant

Another one of the popular SEO title tag best practices is to use numbers, because numbers attract our attention. They’re specific, they stand out, our brains can easily recognize them, and they’re great for growing search traffic.

Marketers have also been saying for years that pages with odd numbers in their titles will gain the most shares because odd numbers stick in your mind much better than even numbers.

A Google result for a Medium listicle, “29 reasons you’re reading this article,” shows us how odd numbers can be used in the SERPs.

So it might be better to conclude all of your lists once you reach an odd number, like 9, instead of one that “looks better,” like 10 or 20. Including the year can also boost your post’s performance. It can signal recency around topics where freshness matters, and increase click-through rates (CTRs). 

Just like numbers or the year, questions can be powerful for grabbing your audience’s attention. They pique our curiosity.

I’ve talked about the importance of using open-ended questions in your blog posts before. The same applies to title tags.

News sites like CNBC practice this tactic all of the time:

The Google result for CNBC’s “What does Google know about me?” article demonstrating the use of questions in the SERPs. 

You can even take a more creative approach and answer part of the question in your title as a teaser, like copyguide.co does:

A Google result for a copyguide.co article shows how partially answering a question is an SEO title tag best practice that can hook the reader. 

AYou might even increase your chances of being cited in Google’s AI Overviews if you ask a question in your title and provide a clear, comprehensive answer on your web page. 

AI Overviews pull from multiple sources to generate a summary answer at the top of the SERP, and they’re most often triggered by question-based, informational queries. That makes question-format titles a natural fit for capturing this kind of visibility.

For example, a search like “Why is Seattle called the Emerald City?” often surfaces an AI Overview that synthesizes explanations from several websites before the traditional organic results appear below.

Google AI Overview results for “why is Seattle called the Emerald City?”

Of course, the goal of title tag best practices and other SEO elements is to get readers to click. This is the very reason calls to action (CTAs) are just as important as, if not more important than, questions in your SEO title tags.

CTAs make people click because they do exactly what their name says. They “call people to act” on whatever you’re asking of them.

You’re probably already including them in ads, blog posts, and web pages. Why not include them in title tags, too?

Action words (or trigger words) provide users with something extra by giving them an incentive to do something.

Examples of action words include buy, download, watch, learn, find, listen, and view.

Android Developers’ Google result for their Studio & App tools uses the word “Download” in their title tag as a call-to-action.

Combine those words with terms like free, easy, or new, and people will be clicking on your content like never before.

Additionally, you may want to consider adding some top keywords to your title.

You can have too much of a good thing, though. Overusing or cramming all of these elements into your title tag may make it feel spammy and undermine the very SEO boost we’re trying to achieve.

How Google Rewrites Title Tags (And How to Prevent It)

As I mentioned earlier, Google rewrites over 76 percent of title tags according to SearchEngineLand! 

But why?

It turns out Google does this when its search algorithms think your title doesn’t represent the page’s content. It may see a mismatch between the user’s specific query and your title, or a mismatch between your title and your blog’s H1.

Title formatting can also trigger a rewrite. Google often rewrites titles that are too long, too short, or that overuse pipe characters.  

Your title could also be rewritten to remove keyword stuffing and boilerplate language, and to add context. For commercial queries, Google frequently emphasizes commercial elements and removes what it considers unnecessary fluff.

So if your title tags don’t look good to Google, they’ll consider other factors, including:

Take a look at this title tag: “Utilities and Electrical Services.”

Google search result showing “Utilities and Electrical Services – Murphy Group” as the title tag.

If you go to the homepage and view the source code (right-click and select “View Source” or “View Page Source”), you’ll see the actual title is “Utilities and Electrical Services – Murphy.”

The source code for the Murphy Group homepage confirms that the page title is “Utilities and Electrical Services – Murphy.”

Google rewrote it because it felt the revised title tag would help people more than the original.

A well-optimized title tag is still worth writing because it gives Google a starting point. Without one, Google starts from scratch, and the result is often worse.

The good news: If you follow the title tag SEO steps outlined in this article, Google should keep your title tags as they are. Keep titles under 55 characters, match the title closely to the H1, ensure the title accurately describes the page content, and avoid exact-match keyword stuffing, and you should be fine.

It’s also important to remember that a rewrite is more of a display issue and not a ranking signal issue. Google will continue to use your HTML title tag for ranking signals, even if it rewrites what’s displayed in the SERPs. 

Title Tags in the Age of AI Overviews

In 2026, your title tag is doing two jobs.

In traditional search results, it still drives clicks. In zero-click SERPs, where a user finds their answer in an AI Overview without leaving the page, a citation builds brand trust and mindshare even when no click follows. Both functions matter to your AI SEO strategy.

Google’s recent moves make this dual function even more important. In March 2026, Google confirmed it is testing AI-generated titles in traditional search results, not just Discover. The test is described as small for now, but Discover’s “small” headline experiment became a permanent feature within a month. Accurate, intent-matched titles are the most likely to survive both human and AI editorial review.

For AI Overview eligibility, your title tag should reflect a direct, citable answer to a common query, not just a click hook. Think of it as a label for a useful resource. That mindset aligns naturally with answer engine optimization, where clarity and accuracy outweigh clever phrasing.

We’re already seeing data to back this point. A recent study shows that title tags written to describe the general topic clearly get about two times the citations of titles strictly optimized for a keyword. 

How to Implement a Title Tag

Once you know how to create an SEO title tag that works, it’s time to add it to your web page.

Here are two different ways you might go about it.

Case 1: You Use WordPress

If you use WordPress, it’s super easy to add a title tag. There are extensions you can download to implement your SEO title tags. The benefit of using these is that you don’t have to edit your HTML.

My extension of choice is Yoast, although other options work just as well, such as Rank Math and Slim SEO.

Here’s how Yoast works once you’ve installed it. To edit the title tag for a page or post, navigate to that content and open the editor.

If you’re using the traditional WordPress editor, scroll down to the bottom of your post or page, and you’ll see the Yoast box, where you can edit the title tag and meta description. If you’re in Elementor, you can access Yoast by clicking the settings cog in the Elementor menu.

You can edit your title tag and meta description directly in Yoast. It’ll also give you a nice preview of your title and meta description so you can see how they’ll look in the search engine results.

A screenshot of the Yoast SEO WordPress plugin showing the SEO title, URL Slug, and Meta description. 

Case 2: You Use A Custom Site Not Hosted On A CMS

If your site isn’t hosted on a content management system (CMS), you can edit your HTML directly to add a title tag.

First, access the HTML for your page. I recommend checking with your hosting service on how to do this.

Once you’ve found the editable HTML, make sure you’re between the <head> tags.

A screenshot showing HTML source code for a page’s header, where you would edit SEO title tag information.

To create the title, use <title> tags. For example:

A screenshot showing HTML source code for a page’s header with an SEO title tag implemented. The title says “<title>Your Website title – Your Company</title>.”

Save your code, and your title will show up correctly.

If you don’t have a bespoke website or use a CMS other than WordPress, I recommend contacting your CMS provider or web host. 

They’ll be able to advise you on how to access your HTML to edit your page title tags, and you can move on to the next element of my on-page SEO cheat sheet to get the most out of your optimization efforts.

Expert Tips for More Clickable Title Tags

Your title’s formatting elements create a solid SEO foundation, but there are several tweaks worth layering on. Here are a few SEO title tags best practices that can make a real difference.

Use Your Brand Wisely

The title tag can be a great place to include your brand name, but don’t go over the top. You only have limited space, and it’s more important to use your title tag to show how you can solve your customers’ problems.

Google recommends using your homepage title tag to include additional information about who you are and what you do. That’s what I’ve done with the Neil Patel homepage, as you can see here:

Google entry for neilpatel.com demonstrating how you can use your SEO title tag to provide more information about your brand.

For the rest of your pages, adding your brand name to the end of the title tag will suffice (if there’s room).

Google entry for “How to Fix Leaky Pipes and Joints” from HowStuffWorks. The entry is an example of using your brand name at the end of a title tag to make it more clickable. 

Consider Making Your H1 Different From The Title Tag

Sometimes, your headline and title tag will be the same. But there are some cases where they won’t be.

For example, if your page headline is long and detailed, you might want a shorter, snappier title tag. This can look better in the search engine results and gives customers more context.

Here’s an example from Copyblogger. The title tag is “Content marketing tools and training.”

Google’s entry for Copyblogger’s homepage showing that the title tag is “Content marketing tools and training.”

However, the headline on the website is “The most important skill in business is the ability to move people with words.”

A screenshot of Copyblogger’s homepage showing the page’s headline is longer and more descriptive than their Google entry, saying “The most important skill in business is the ability to move people with words.”

Avoid Duplicate Tags

When creating lots of content, it can be tempting to use the same title tag for each page to save time.

However, this can cause issues with search engines. 

A screenshot of Google SERPs showing two entries for next.co.uk, both using the same “Buy Women’s Trainers Footwear Online” title tag.

Note this example of identical tags from next.co.uk. Listing multiple pages with identical title tags may confuse customers, leaving them unsure which page to click on. It can also confuse the search engines, as they won’t know which pages to prioritize for which search query.

The good news is that there are plenty of tools that will help you find duplicate title tags. My favorite is Screaming Frog, which quickly identifies duplicate title tags and meta descriptions.

Add emojis

At one time, Google had removed emoji characters from results pages.

Eventually, Google would reverse that decision, meaning that we can still leverage the power of emojis in the SERPs and on mobile.

That’s good news since emojis can add a sense of emotion to regular text or even replace text altogether.

But you can use emojis for more than just fun and games. They can also boost engagement.

You can add emojis to your title tags by copying and pasting them, using a WordPress plugin, or typing the code yourself.

If you’re using Yoast, you already have access to codes for each emoji that you can copy and paste.

A table showing emoticon Unicode and display across platforms.

Once you’ve selected an emoji, added it in, and published your page, it should look something like this on SERPs.

Mangools’ Google entry uses a rocket ship emoji in their title tag.

When you view the source code for your web pages, your code may look different depending on how you’ve built your page.

Some pages will show the emojis in your source code, but source code for other web pages that include emojis, like this one from Search Engine Journal, might cause emoticons to appear as code instead of displaying them. Either way, viewing the source code is a good way to confirm your chosen emojis made it into your title tag. 

An example of an emoji in Search Engine Journal’s title tag showing up as code. 

Here’s a quick tip: to view the source code for any web page, press Ctrl + U on a PC or ⌥ Option + ⌘ Command + U on a Mac.

Emojis will take up character space within your title tag, so keep that in mind when considering length, which we discussed earlier.

A/B test your title tags

A/B testing is a great way to experiment and see what SEO title tags drive the most clicks.

Start with Google Search Console’s Performance report, which surfaces click-through rate by URL and gives you a reliable baseline. Document the page’s average CTR for the 28 days before deploying the new title. Then, push the change live and compare CTR over the next 28-day window. That length helps smooth out daily fluctuations and seasonality.

For an extra layer of validation, third-party tools like TitleTester collect feedback from real users on which title variations they find most compelling. That kind of pre-deployment input can help you narrow your options before committing a page to a live test.

How to Audit Your Existing Title Tags

A title tag audit is a foundational technical SEO task, and you can run one in an afternoon. Start with a site crawler like Screaming Frog or Ubersuggest to flag titles that are missing, duplicated, longer than 60 characters, or lacking the target keyword.

Next, use Google Search Console’s Performance report to identify pages where the displayed title in search results differs from your HTML title. This surfaces pages Google has already rewritten, which are strong candidates for revision.

Once you have your list, prioritize fixes by traffic and impressions. Pages that already attract impressions but underperform on clicks should be natural candidates for title optimization, since the title is one of the few elements that influences clicks without requiring content changes.

Finally, check for significant misalignment between your title tag and your H1. As Zyppy’s title tag rewrite study showed, mismatched titles and H1s are a common rewrite trigger that’s easy to fix.

FAQs

Are title tags still relevant for SEO?

Yes. In 2026, title tags shape your page’s presentation in traditional search results, AI Overviews, and AI-generated rewrites. Skip them, and Google will create one for you, often with worse results.

Do title tags help SEO?

Yes. According to John Mueller, the HTML title tag still works for ranking purposes, even when Google rewrites the displayed version in the SERP.

How important is the length of a title tag for SEO?

Length influences whether Google keeps your title or rewrites it. Titles in the 51 to 60 character range have the lowest rewrite rate, per Zyppy’s analysis of 80,000+ title tags.

Does a duplicate H1 and title tag hurt SEO?

No. Closely matching your title tag and H1 reduces the chance of a Google rewrite. Significant misalignment is a known rewrite trigger, but there are instances where your H1 can be slightly different. You can use a longer, more descriptive H1 on your homepage than your title tag in Google as long as they both cover the same general topic. 

Conclusion

Title tags carry more weight than they used to, and they’re harder to get right. Google rewrites more titles than ever and AI Overviews read your title as a citable answer rather than a click hook, raising the bar for a “good” title. 

Ensuring you write accurate and intent-matched titles will serve you across traditional SERPs and AI Overviews. It can even help you avoid any AI-generated rewrites Google might roll out.

If your existing titles haven’t been audited in a year or two, they’re due for a refresh. NP Digital can help you audit your on-page SEO and surface the title tag opportunities most likely to move the needle.

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Hydration and SEO: How it works and why it matters

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Hydration and SEO- How it works and why it matters

If your site runs on a framework like Next.js or Nuxt, hydration shapes how your pages become interactive, but it’s rarely explained in terms that matter to SEOs.

It’s more approachable than it sounds. Here’s what hydration is, how it works, where it affects SEO (and where it doesn’t), and how different frameworks handle it.

What is hydration?

Hydration is the process of JavaScript running in your browser “taking over” the static HTML built on the server, turning it into a page you can actually interact with.

Here’s the process:

  • The server builds complete, fully formed HTML and sends it to your browser. You see the content right away, but it isn’t interactive. The buttons don’t work yet, and nothing responds to clicks.
  • Hydration happens when the page’s framework (Next.js, Nuxt, SvelteKit, and others) finishes loading. It walks over the existing HTML, attaches event listeners, and reconnects the visible markup with the logic that makes it work.
  • After hydration, the page behaves like a normal interactive app.

Server-rendered HTML paints quickly, which is great for first impressions and often for Largest Contentful Paint (LCP). As the timeline below shows, traditional hydration means the page isn’t actually usable until hydration finishes.

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Hydration adds interactivity, not content

Hydration doesn’t add content to the page. The text, images, and layout already arrived from the server. It only adds behavior, wiring up the existing HTML so it can respond to you. Put simply, before hydration you can read the page, and after hydration you can use it.

You can see this side by side below. The only difference between the two pages is whether the button responds.

Don’t confuse hydration with the rendering pattern, which determines where and when the page is built. Server-side rendering (SSR), static site generation (SSG), and client-side rendering (CSR) each decide how much of the page arrives as finished HTML versus how much JavaScript builds later in the browser.

Because hydration runs on server-rendered (SSR) and static (SSG) pages, the content is already present in the initial HTML. Google can index that content from the initial HTML instead of relying on the render step, which is more reliable than a client-rendered blank shell.

When hydration becomes an SEO problem

Most of the time, hydration isn’t directly an SEO issue. It only becomes one when something breaks, usually a mismatch. This is when the server’s HTML and what the framework builds in the browser don’t agree.

A mismatch typically comes from one of a few sources:

  • Content rendered from a browser-only API that the server can’t access, like localStorage.
  • A value that changes between the server and client, such as new Date().
  • A third-party script or browser extension that alters the DOM before the framework hydrates it.
  • Invalid HTML that the browser rewrites in the background, producing a structure the framework didn’t expect.

In these cases, hydration can’t reconcile the two versions, so the framework throws out the mismatched part and re-renders it. The exact process depends on the framework.

Here, a <time> value from new Date() renders differently on the server and in the browser, forcing a re-render.

That creates problems on three fronts. The re-render makes the page feel sluggish (INP) and shifts the layout (CLS). It can also leave the page outright broken because event listeners may fail to attach, causing buttons and forms to stop working.

In severe cases, because Google may read the raw server HTML before rendering the JavaScript, it can index the version that’s about to be discarded, storing content visitors never actually see.

Developers can resolve these issues by fixing the underlying causes of the mismatches. For example, they can use valid HTML so the browser doesn’t rewrite it behind the scenes.

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How to spot hydration problems on a live site

Hydration errors aren’t as explicit on a live site as they are during development. Start by checking the browser’s Developer Tools console for hydration or JavaScript warnings, then use these additional checks:

  • Watch the page load for content that shifts, flickers, or stays unresponsive.
  • Run important templates through Google Search Console’s URL Inspection tool to see how the page is rendered.
  • Crawl in JavaScript-rendering mode (Screaming Frog, Sitebulb) to compare rendered output against raw HTML at scale.

How frameworks handle hydration

Modern frameworks take different approaches to hydration, including ways to reduce or skip it, to balance performance, interactivity, and JavaScript execution.

The most common approaches are:

  • Full hydration: The whole page hydrates in one go. It sounds simple, but it ships the most JavaScript and puts the most work on the main thread.
  • Partial hydration: Only the interactive bits (“islands”) hydrate. The static parts stay as plain HTML and never get touched. Astro’s islands architecture is built around this.
  • Progressive hydration: The page hydrates in pieces, either as sections scroll into view or on a schedule, instead of all at once. Angular’s incremental hydration works this way.

Two newer approaches sidestep hydration:

  • React Server Components: Some components render entirely on the server and ship zero JavaScript, so there’s nothing to hydrate on the client.
  • Resumability: It skips hydration completely. The page picks up exactly where the server left off, with no components re-running on load. Qwik does this. It’s also the newest of these approaches and the least battle-tested.

Here’s how they compare:

Technique What hydrates JavaScript shipped Example
Full hydration The entire page Most Next.js (Pages Router)
Partial hydration (islands) Only interactive components Less Astro
Progressive hydration The page, in pieces over time Same total, spread out Angular
React Server Components Nothing (for server-only parts) Less Next.js (App Router)
Resumability Nothing, hydration is skipped Least Qwik

What this means for your site

Most of the time, hydration isn’t an SEO problem. It only becomes one when the server’s HTML and the browser’s rendered version disagree.

Newer frameworks leave less room for that to happen because each generation ships less JavaScript and does less work in the browser. Still, the mismatches that do surface matter, especially when search engines index a version of the page your visitors never see.

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Used or cited: The two ways brands appear in AI search

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Used or cited: The two ways brands appear in AI search

Ranking within Google’s traditional search results provides diminishing returns. Ads, AI Overviews, and other search engine results page (SERP) features push organic links further down the page.

As the search landscape changes, how should brands adapt to ensure they’re represented in AI-powered responses?

The more you know about how AI engines use your brand’s information and when they cite it, the better you can use AI search to your advantage. With that knowledge, you can move beyond whether AI models know your brand and start developing your own AI visibility strategy.

Collapse of the click economy

It’s important for most brands to understand AI search and begin developing an AI SEO strategy as quickly as possible. While a full transformation from organic to AI search appears to be years away, AI SEO may eventually replace traditional SEO.

Google is already leaning heavily on AI search. As CEO Sundar Pichai said in an April article from The Verge: 

  • “Search had a strong quarter with AI experiences driving usage, queries at an all-time high, and 19% revenue growth.”

At the same time, users are adapting to AI search features. When users encounter an AI-powered summary in search results, they click a blue link just 8% of the time, a Pew Research study found. When they don’t encounter AI summaries, they click blue links 15% of the time.

Although AI search traffic is still limited, it tends to have a higher conversion rate than organic search traffic. AI traffic had a conversion rate of 11.4%, compared to 5.3% for organic search traffic, per a Similarweb study.

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Brand presence within AI engines: Usage vs. citation

Brands can exist in AI systems in two distinct ways: usage and citation.

AI engines ingest information about your brand and use it when responding to search queries. This is somewhat similar to how Google traditionally indexes pages before ranking and serving them in search results.

When AI engines use your content, they may also mention your brand as an unlinked citation. This can drive discovery and may prompt users to search for and engage with your brand.

Citation occurs when an AI engine directly references your brand as a source of information. This may be a link to your web page, a link to your social profile, or a clickable phone link that lets users call you.

Within OpenAI, usage and citation rely on separate technical levers. As OpenAI’s documentation explains, there are four distinct user agents, with OAI-SearchBot and GPTBot deployed separately. Other AI systems have similar controls and measures that point to the same distinction.

Why citations are only part of the AI visibility equation

AI engines often answer questions directly without necessarily citing web sources. This isn’t a new phenomenon. Before AI Overviews, Google tried something similar with featured snippets.

ChatGPT retrieves almost the exact same number of cited (~16.57) and uncited (~16.58) URLs to generate an average response, according to an Ahrefs study. Yet Reddit accounts for more than two-thirds (67.8%) of uncited URLs. As a result, comparing cited and uncited URLs is really a comparison between search results and Reddit API output.

This demonstrates that many AI systems are biased in the uncited information they provide to users. Certain platforms and websites are better than others at helping brands appear in AI answers. Brands that try to force themselves into AI models without understanding where those models source most of their information will be at a distinct disadvantage.

How to improve AI usage and citation for your brand

Start by tracking your brand’s status and progress over time. Run a representative selection of prompts through an AI visibility platform and examine the citation sources. Where do they land, and what does that tell you?

There are many emerging AI citation tracking platforms to choose from. Established platforms like Semrush and Ahrefs have also integrated AI tracking features.

Scale your tracking and research efforts as much as possible. This can be difficult because AI prompt tracking often relies on API calls and is more expensive than traditional search ranking tracking.

As long as your sample is broadly representative, most tracking platforms will pull multiple responses and calculate some type of average. Although the volume of data is smaller, it’s usually quite rich.

Don’t forget to read AI and data vendor studies. They’re valuable sources of information because they show where AI engines pull information from.

Continual monitoring and adaptation are key. Over time, you can place your brand within the sources AI engines rely on most heavily.

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Should you bother with traditional search rankings?

Yes, you should continue to pursue traditional search rankings, but not for the reasons you might think. The connection between organic ranking positions and performance has become much more nebulous.

However, Ahrefs research suggests a correlation between AI citations and Google ranking positions, at least for Google AI Overviews. A July 2025 study found that 76.1% of pages cited in AI Overviews ranked in Google’s top 10 organic search results. For AI Overviews, which may become a dominant force in AI search over the coming years, traditional rankings still seem to matter.

How AI Overview citations rank in the SERPs

AI engines rarely cite generic content that restates what other sources already say, an April study from Semrush found. Content that earns citations adds unique value.

This aligns with Google’s helpful content guidance, which encourages brands to publish original information. Producing content with a unique, trusted, and statistically grounded perspective can also help improve Google rankings.

Since many tactics for earning higher organic rankings can also earn AI citations, there’s no reason to abandon traditional SEO techniques and content strategies.

The growth of AI visibility and the fate of traditional SEO

Both usage and citation require continual tracking and analysis. To increase the likelihood that AI engines use your brand’s knowledge and content, get your brand into the sources each AI model relies on. To earn citations, stay crawlable, rank organically, and say something original.

Classic SEO still earns its keep because the techniques that win organic rankings often earn AI citations as well. Yet the returns are diminishing, and AI SEO may one day replace traditional SEO altogether. That’s still a long way off, so for now, keep ranking, start tracking, and pursue both.

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Google merchant listings support sale duration and product category

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Google has updated its merchant listing structured data to support sale duration and product category property. This is to more align the merchant listing structured data support within Google Search with Google Merchant Center feed support.

Sale duration. Google added a new section on “Sale duration” to the Merchant listing structured data help document. Google said, “this explains how to use the validFrom, validThrough, and priceValidUntil schema.org properties to set the effective range for sale prices, including best practices and examples for placement on either Offer or PriceSpecification nodes.” Google added this because it “aligns schema.org usage with the Merchant Center feed attribute sale_price_effective_date, providing clear instructions and best practices for merchants using structured data.”

Here is that new section:

Product category. Google also updated that document to include support for Product.category property.

Google wrote it has updated the Merchant listing documentation to detail how the Product.category property can be used with both Text and CategoryCode types. “This aligns with the Google Merchant Center feed specifications for the product_type and google_product_category attributes,” Google added. Google also said this is to “help merchants provide both merchant-defined and Google-defined category information within their schema.org markup, enhancing product information for Google Search and Shopping.”

Here is what was added:

Why we care. If you maintain merchant listing structured data for Google, these additions may be useful. Product category support can help Google understand more about the products you are feeding it, which may help with showing that product for more relevant queries. Google’s sale duration support can let you plan your product sales more effectively and efficiently when updating your merchant listing structured data.

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How to get the most from Microsoft Advertising campaigns

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How to get more from Microsoft Advertising than a campaign import

If you’re struggling to scale performance with Microsoft Advertising, you may be treating it as a place to replicate a strategy developed elsewhere.

Import can get you live fast. Performance comes from adding human judgment, Microsoft-specific structure, foundational measurement, controls tailored to your business needs, and a broad range of creative assets that help AI understand your products or services.

The strongest accounts share a common approach: Import is a starting point, visual creatives unlock more demand and better performance, and AI performs best when you give it the right structure, creative, measurement, and guardrails.

Here’s how to use Microsoft-specific mechanics to improve performance while avoiding common pitfalls.

Note: I’m a Microsoft employee, and this article was written as objectively as possible. I’ve also included hidden gems sourced from the community that highlight favorite features where relevant.

1. Start with import, but don’t stop there

Import is useful because it removes friction. It can bring over structure, assets, and settings from Google, Meta, or Pinterest so you can launch faster. The mistake is assuming a successful import means your Microsoft Advertising strategy is finished.

Imported campaigns preserve yesterday’s assumptions. Microsoft Advertising still requires decisions about budget, bidding, audiences, creative, measurement, reporting, and AI-powered opportunities.

Decide whether sync helps or holds you back

One of the most important import decisions is whether future changes from the source platform should continue syncing to Microsoft Advertising. If your goal is to mirror another platform, automatic sync may reduce overhead. If your goal is to build a Microsoft-specific strategy, automatic sync can quietly erase the optimizations you make after launch.

To access the full list of import settings, go to Manual import > Advanced settings. Review which settings should stay, which should change, and which Microsoft-specific opportunities weren’t part of the original structure.

Review budgets, bids, currency, and Microsoft-only options

Imported budgets may not reflect the opportunity or efficiency available, especially if you consolidate campaigns with ad-group-level controls. 

Imported bids may preserve assumptions from another platform instead of giving Microsoft Advertising room to optimize for its own auction dynamics, audiences, and conversion data.

Review Microsoft-specific settings after import

Import also can’t choose Microsoft-specific opportunities for you. Review these settings after launch:

  • LinkedIn profile targeting: Bid up or down, observe, and use LinkedIn profile data as a Performance Max audience signal. Microsoft supports Company, Industry, Job Function, and Seniority.
  • Ad-group-level scheduling and location targeting: Override campaign-level schedules and location targets at the ad group level. You have access to the same settings, including whether ads serve in the user’s time zone or the account’s time zone.
  • Impression-based remarketing: Target, exclude, or adjust bids based on someone seeing your ad. As long as there’s at least one Audience ads campaign or ad group in the source seed lists (up to 20), any campaign can target any other campaign (for example, search can target search). Impression-based remarketing doesn’t require an existing email list or pixel, and members can remain on the list for up to 30 days after a single impression.
  • Multimedia ads: Visual-heavy ads that occupy a unique position on the SERP and are eligible to serve in Copilot. They have their own auction and can appear on the same SERP as your text ad without competing against it. You can bid more aggressively for Multimedia ads and create them in standard search campaigns by selecting that ad type instead of responsive search ads (RSAs).
  • Cross-account portfolio bidding: If you need to launch a new account for the same brand, you can allow it to benefit from the conversion data of an existing account.
  • Microsoft Clarity: A free behavioral analytics tool that helps you understand how people and AI engage with your site. It can reveal whether landing pages create friction, are easy for people and AI to understand, and which grounding queries (the searches AI performs in the background) your site naturally appears for and whether they align with your target search terms.
  • Creative and editorial considerations: Microsoft has stricter advertising policies than many other platforms, but it also offers some unique capabilities, such as allowing exclamation points in headlines and disclaimers of up to 500 characters that don’t take up ad space. Note: If you enable disclaimers, your ads will only serve when the disclaimers can appear alongside them.

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2. Build the signal foundation before optimizing

Account-level settings may seem overly technical. In practice, they determine whether AI receives clean signals or learns from bad data. Settings like business attributes also let you communicate why customers should choose your business.

Verify conversion tracking and attribution before changing bids

The best bidding strategy can’t compensate for incomplete conversion data. Microsoft Advertising provides account-level settings that help ensure conversion and attribution data flow correctly, including:

  • Microsoft Click ID (MSCLID): Helps connect ad clicks to conversion activity.
  • View-through conversions: Help you correctly attribute the role of visual creatives in the path to conversion.
  • Simplified conversion setup: Enables intelligent conversion action creation.

Without verified tracking, it’s easy to blame bidding, keywords, audiences, or creative when the real problem is incomplete or inconsistent conversion data.

If your organization relies heavily on UTM parameters, validate how auto-tagging and manual tagging interact. The goal is clean reporting, not duplicated parameters or attribution confusion caused by mislabeling.

Treat creative inputs as signals

When enabled, Microsoft Advertising can use images from your landing pages to create more compelling, relevant ad experiences that better match a potential customer’s intent and context. If you have strong, well-maintained landing pages, this can improve creative asset coverage without having to manually build every image variation for every campaign type.

AI-optimized creative works best when your site already contains brand-safe, relevant, high-quality imagery. If your pages contain images you wouldn’t want appearing in ads, or if the imagery is sparse, text-heavy, or doesn’t represent the offer well, upload the assets you want the system to use. Auto-retrieved images reduce creative friction. They don’t replace creative strategy.

Use account-level negatives carefully

Account-level negatives help eliminate unwanted traffic patterns across your account. Microsoft supports phrase and exact match negatives. If you want to eliminate a root problem, a phrase match negative is likely the better option. For a specific search term, an exact match negative may work better. Neither negative match type accounts for close variants.

Use account-level negatives only for terms you’re confident shouldn’t serve anywhere in the account. Keep nuanced exclusions at the campaign or ad group level.

3. Use structure and controls to help AI perform

Microsoft Advertising gives you useful controls, but the goal isn’t to micromanage every lever. Give AI cleaner inputs, stronger guardrails, and fewer structural problems to solve. Use human judgment to guide the system.

Concentrate signals instead of fragmenting them

Ad-group-level location and ad schedule settings can reduce the need to create duplicate campaigns or split budgets across multiple accounts.

I’ve seen advertisers create separate campaigns solely to accommodate different geographies or schedules. In many cases, those settings can be managed at the ad group level, resulting in a simpler structure and more concentrated conversion volume.

That consolidation matters because automated bidding generally performs best with stronger, more consistent signals. A practical benchmark is to aim for at least 30 conversions in 30 days, where possible. That level of steady signal gives automated bidding a better chance of making stable decisions than a fragmented structure with thin conversion volume.

Use scheduling, location, and disclaimers as guardrails

Location targeting deserves review. Microsoft Advertising supports geographic targets, radius targeting, and exclusions, but city-, county-, metro-, or DMA-level strategies may be more practical than forcing ZIP codes.

If Microsoft doesn’t support a specific location target, it defaults to the next-highest level (for example, ZIP code to city or city to DMA). If you need narrow targeting, consider using exclusions.

Avoid unnecessary learning volatility

Large bid or budget changes can create performance volatility as the system adjusts. As a general rule, keeping bid or budget changes below 15% over a 14-day period can help reduce avoidable learning volatility. Larger changes may still be necessary, but make them intentionally rather than accidentally resetting the system’s learning rhythm.

Seasonality adjustments help when you expect a temporary conversion rate change because of a sale, event, promotion, or other short-term spike. Data exclusions help when conversion tracking breaks or reports misleading data you don’t want automated bidding to learn from. These tools aren’t bidding hacks. They protect automation from learning the wrong lesson.

Use conversion value rules whenever possible

The best way to communicate with the bidding algorithm is through conversion value rules grounded in accurate conversion tracking. They let you create if/then statements for devices, audiences, and locations to add a monetary amount to or multiply your conversion value.

Microsoft supports bid adjustments across audiences, devices, demographics, locations, and time. Multiple adjustments can compound. If a user qualifies for several categories at once, your bid may become more aggressive than intended.

Before adding another layer, ask whether you truly want to spend more to reach that audience, in that location, on that device, during that time. If you want the algorithm to understand value, meaningful conversion values and conversion value rules are usually stronger signals. If values aren’t reliable, CPA-oriented bidding with carefully chosen adjustments can still work.

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4. Use audiences, inventory, and creative to shape demand

Microsoft’s differentiated audiences, inventory, and creative formats can help you generate and shape new demand rather than only capture existing demand.

Use LinkedIn profile targeting intentionally

LinkedIn profile targeting remains one of the most unique audience capabilities in Microsoft Advertising. You can apply bid adjustments based on company, industry, job function, and seniority. 

Multiple targets within the same LinkedIn profile category act as “or” statements, while targeting across categories narrows the signal. A company target plus a seniority target is more restrictive than choosing two companies, which is useful when intentional and expensive when accidental because bid adjustments compound.

For B2B advertisers, this can be especially useful, but it isn’t limited to enterprise brands. Any business selling to specific professional audiences can use these signals to prioritize valuable traffic.

For example, if a brand is trying to reach someone traveling for work with local experiences or travel gear, it might bid up on someone with a “Business development” job function in an industry with a conference taking place in the next two to three weeks.

Build audiences from exposure, not just site visits

Traditional remarketing relies on someone visiting your website. Impression-based remarketing introduces another option: building audiences based on people who’ve been exposed to your advertising. 

A prospect may not click the first time they encounter your brand, particularly in formats such as Audience ads, Premium Streaming, or Multimedia ads. Impression-based remarketing lets you continue that conversation later rather than treating the initial exposure as a failed interaction. An impression can be the starting point for an audience strategy.

Reevaluate search partners and exclusions

Many advertisers disable search partners because they assume they behave like display network expansions on other platforms. Search partner inventory is still search inventory, and Microsoft provides publisher visibility, so you can evaluate it rather than reject it based on assumptions. 

Recent Microsoft studies have shown a 45% improvement in conversion rates and a 20% reduction in low-quality impressions tied specifically to Search Partner inventory, independent of advertiser optimization.

If specific publishers aren’t performing, use the available controls. You can manage unlimited exclusion lists at the MCC account level, and each list can exclude up to 2,500 URLs. If you need to protect a campaign’s ability to target a placement, such as when running Performance Max and Audience ads simultaneously, exclude domains surgically rather than cutting off useful inventory.

Use Multimedia ads to expand your SERP presence and build impression-based remarketing lists

Multimedia ads participate in their own auction and can appear in prominent visual placements on the search results page. A traditional search ad and a Multimedia Ad can both appear for the same brand, increasing your presence on the results page. 

Multimedia ads can be enabled at the campaign level, with ad-group-level decisions that help direct budget toward or away from the format.

They also matter because they can amplify your visual presence, serve as ads in Copilot, and qualify for impression-based remarketing. Their value isn’t limited to direct-click performance. They can connect search visibility, visual storytelling, and remarketing strategy.

Use Audience ads to expand reach

Audience ads (display, native, and video) can be a controlled way to expand reach, support full-funnel strategy, and build remarketing inputs that inform other parts of the account.

Audience ads support audience strategies, placement preferences, content category controls, and creative preview before launch. For organizations that require legal, brand, product, or executive approval, preview capability can simplify the review process.

Use creative and editorial details to reduce friction

Microsoft Advertising has editorial policies you should understand rather than assuming every platform evaluates ads the same way. Claims such as “best,” “number one,” or other superiority language need clear landing page support. 

Microsoft Advertising also allows some emphasis you might not expect, such as one exclamation point in headlines, but that flexibility doesn’t remove the need for substantiated claims and clean final URLs.

Editorial issues often get misdiagnosed as platform friction. In many cases, the issue is a specific asset rather than the entire ad, but final URL problems are more fundamental and can prevent an ad from serving.

Extensions and visual assets can also help brands communicate more value before users reach the landing page, especially in competitive categories where plain text may not provide enough differentiation.

5. Treat PMax, AI Max, and Copilot as AI opportunities with guardrails

Microsoft’s approach to AI is most useful when viewed as an augmentation rather than a replacement. Human-centered AI should enable thoughtful scale while preserving advertiser consent, transparency, and trust.

Know what Performance Max is designed to enable

Performance Max can be powerful, but it requires a different mindset from traditional campaign structures. Asset groups aren’t ad groups. There’s no asset-group-level equivalent to ad-group negatives, and you can’t force one asset group to take priority over another.

Performance Max is designed for AI-driven allocation. If strict control is your priority, traditional Search, Shopping, and Audience campaigns may provide clearer governance. The best way to influence Performance Max is through:

  • Strong audience signals: Include impression-based remarketing and LinkedIn profile targeting, which are unique to Microsoft.
  • Relevant creative: Copilot can pull creative from your landing page and adapt existing creative with tonal shifts, rewrites, or formatting improvements.
  • Thoughtful search themes: Including the same search themes as your exact match keywords makes it harder for Performance Max because exact match keywords take priority in the auction.
  • Meaningful conversion tracking: Ensure you have accurate conversion tracking and conversion values because Performance Max needs conversions to perform effectively.
  • Landing pages that clearly communicate the offer: Your landing page is a critical part of the matching and creative logic. If you don’t use clear language, the algorithm may struggle to identify which queries are a good match. It also makes it harder for people to do business with you.

If you run the same search theme as an exact match keyword, there’s a strong chance the exact match keyword will serve instead of the Performance Max campaign. Use search themes as testing grounds rather than duplicating exact match keywords.

Performance Max website URL reporting provides URL-level visibility into spend, clicks, impressions, and conversions. This gives you more to work with than impression-only reporting and can make automated campaign testing easier to justify.

Separate campaigns when budget separation matters

If budget separation matters, create distinct campaigns rather than forcing multiple business objectives into a single Performance Max campaign. Microsoft’s campaign capacity of 300 Performance Max campaigns, compared with Google’s 100, can be useful when meaningful budget priorities require separation.

For example, if you have two equally important products with drastically different tROAS goals, you wouldn’t want them to share budgets because there’s no way to specify which asset group or product should take priority. They’re better served in separate campaigns with distinct budgets and tROAS goals aligned to their margins.

The rule is simple: If related assets and audiences can share a budget, consolidate Performance Max campaigns to strengthen conversion volume. If budget separation matters, build that control at the campaign level instead of trying to force it through asset groups.

Evaluate AI Max and Copilot for new opportunities

AI Max now addresses many of the use cases that once made Dynamic Search ads valuable. If your goal is to let Microsoft AI better match queries, creative, and landing pages, AI Max may be the better place to focus your testing.

That doesn’t mean you should abandon existing high-performing campaigns. It means you should be intentional about whether you’re investing in legacy dynamic functionality or AI-powered capabilities built on Microsoft’s latest technology.

Ads can appear in relevant Copilot experiences when Microsoft determines there’s clear commercial intent and the ad may help the user. Ads have served in Copilot since 2024. The goal isn’t to force ads into AI answers. It’s to preserve a useful experience for the user.

Copilot isn’t a separate campaign type you manually opt into. Performance Max, AI Max, exact, phrase, and broad match search campaigns, Multimedia ads, and Shopping ads are all eligible to serve in Copilot. Performance Max and AI Max have the easiest time serving in Copilot because they can adapt to AI-driven experiences.

Use generative AI as a creative workflow and diagnostic tool

Copilot can help you brainstorm, rewrite, refine, and adapt creative across workflows, including Performance Max, responsive search ads, Multimedia ads, Audience ads, and other campaign types where you need to adjust tone, rewrite copy, or develop stronger variations. Copilot doesn’t replace the marketer. It reduces friction between strategy and iteration.

Ad Studio can generate new creative assets and make adjustments such as background modifications, seasonal refinements, location-specific tailoring, and additional aspect ratios. Its best use isn’t replacing the brand team. It’s accelerating iteration once the overall creative strategy is established.

AI-generated assets can also help diagnose how clearly your site communicates. If the outputs accurately represent your business, your site is likely sending clearer signals. If they consistently miss the mark, your landing pages, messaging, or content structure may be confusing both AI systems and people. The Performance Max campaign generator can serve as a useful diagnostic shortcut for the same reason. 

6. Use reporting and Clarity to diagnose before blaming the auction

No amount of AI, bidding nuance, or audience strategy can compensate for poor measurement. Microsoft Advertising provides extensive reporting visibility, and you should use it before making media-only decisions.

Use transparent reporting to make better decisions

Microsoft provides visibility into every search term that generates a click as part of its transparency approach. That visibility can reveal whether a query is:

  • Genuinely wasteful: There’s no business case for targeting that search.
  • An AI-driven match: It may seem questionable until you examine the customer journey with behavioral analytics.
  • A landing page issue masquerading as a traffic problem: Before adding a negative keyword, evaluate post-click behavior to determine whether the landing page or conversion tracking is the real issue.

Use Microsoft Clarity before you make campaign changes

Microsoft Clarity answers an important question: What happens after the click? It can show whether users engage with the page, get confused, abandon forms, encounter technical issues, or complete actions that aren’t being tracked correctly.

Clarity should be part of your diagnostic process before making campaign changes.

  • If people arrive and get stuck, the issue may be the landing page experience.
  • If they complete the desired action but conversions don’t appear in Microsoft Advertising, the issue may be tracking.
  • If they arrive and immediately disengage, the issue may be creative alignment, traffic quality, or the offer itself.

Clarity can also help you understand how AI systems interact with your content, including the grounding queries that led AI systems to cite your domain and recommendations for improving citation opportunities.

If AI systems cite your domain as relevant, that can validate your content strategy. If they don’t, or if the queries reveal mismatches, that may point to gaps in how your content communicates its value.

Every click they win is a customer you lose.

See where competitors are investing, which keywords drive their results, and how to capture more of the market.

See who’s stealing your traffic

Apply Microsoft-specific optimizations

You can import existing campaign structures and assets while also taking advantage of Microsoft-specific capabilities. AI can play a central role, serve as an occasional assist, or be used selectively, though scaling becomes more difficult without some level of AI adoption.

Testing Microsoft Advertising doesn’t require a large investment, but it does require getting the fundamentals right, including conversion tracking, bid-to-budget ratios, and creative that reflects the channel’s visual nature.

When you get those fundamentals right, Microsoft Advertising offers search term transparency, GDPR-compliant impression-based audiences, and opportunities to reach people across the surfaces where they work, live, and play. 

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Google Search Console gains reporting on social and video platforms

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Google Search Console has released what it calls platform properties, which is a way to see how well your social and video content is performing within Google Search. Google will let you see the performance of your content on Instagram, TikTok, X and YouTube performs on Google Search.

More details. Google wrote, “Now, you can easily track which search terms lead people to your Instagram, TikTok, X and YouTube content on Search, and see exactly how your audience is interacting with your posts.” You can see this information within Google Search Console’s performance report, insights report and achievement sections.

  • Performance report: View your total clicks, impressions, and additional metrics. Filter and sort this data to see which specific posts and queries are driving the most traffic. If you prefer to analyze your performance using another tool you can export the data.
  • Insights report: View a high-level overview of your recent traffic trends, your top-performing posts, and how people discover your account on Google.
  • Achievements: Track your growth and celebrate milestones, such as reaching a new threshold for total clicks from Google Search in the last 28 days.

This is similar to the social channels details we had in the Search Console insights reports.

Here is a screenshot of my X account performance report:

Here is a screenshot from Google’s blog post of the insights report:

How to set it up. You will need to verify your platform property within your Google Search Console account, here is how to do that:

  • Open Search Console
  • Go to the Search Console verification page, or open the property selector dropdown anywhere in Search Console and click “Add property.”
  • Select one of the four available platforms: Instagram, Tiktok, X, YouTube.
  • Follow the onscreen verification steps to securely authorize the connection.

Slow rollout. Google said platform properties will roll out gradually over the coming weeks, so there is a chance you won’t see this yet. To learn more about platform properties and how to set them up, see Google’shelp center documentation. We actually saw Google publish this help document a few weeks ago, but then it was quickly removed.

Search profiles. This is different from the new search profiles feature, which actually has its own analytics.

Why we care. Previously, Google has not given us a real way to see how our content performs on domains/properties we do not own. But now, we are going to have access to see how our content performs of domains/properties we do not have developer access to. This is pretty cool and I am excited to see what we can learn from this.

Be the brand AI recommends.

See where your brand appears in AI search, where competitors are winning, and what it takes to become the answer AI recommends.

See your AI visibility

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Building a brand worth finding: Signals that fuel discovery

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Building a brand worth finding: Signals that fuel discovery

For most of the past decade, organic marketers have operated with a clear north star: visibility. Get on Page 1. Get in the featured snippet. Get seen.

That north star has now moved.

The question I put to the room at SMX Advanced on June 5 wasn’t, “How do you get found?” It was the even harder question: “How do you get chosen?”

In 2026, the answers are no longer the same, and the gap between them is where most brands lose ground.

In AI search, your reputation precedes you 

The complex, multi-touchpoint user journey of exploration, evaluation, and conversion has been dramatically compressed. A single AI prompt now does the same work that previously required a dozen searches, three Reddit threads, and a couple of comparison sites.

AI search doesn’t reward the brand that shouted the loudest in paid media or stuffed the most keywords into its metadata. Instead, it rewards the brand with the strongest reputation in the spaces that matter, the same spaces the user journey once encompassed. Reddit threads, comparison sites, and the like all get ingested by LLMs and blended into a single synthesized answer. 

AI search citation material

In other words, your brand is no longer just what you say it is. It’s how AI understands your brand, and the algorithm is reading everything everyone else has ever said about you.

Brand-owned content, across websites and social channels, will always be self-serving and promotional. AI looks for third-party validation to back up those claims.

This shift changes everything for organic marketers. Our job has gone beyond building visibility to building a brand that, once found, is correctly understood and ultimately chosen. Those are three distinct challenges, and they require three distinct strategies.

Be the brand AI recommends.

See where your brand appears in AI search, where competitors are winning, and what it takes to become the answer AI recommends.

See your AI visibility

Found: Be present in your audience’s actual search ecosystem

The first challenge is still about discoverability, but we now work with a much broader canvas than just Google. Consumers now discover brands across ChatGPT, Reddit, YouTube, TikTok, Google, Quora, LinkedIn, and, yes, word of mouth. There are dozens of entry points into the discovery ecosystem, and you need to be credibly present in the ones your specific audience actually uses.

This starts with understanding your audience’s sources of influence: the publications, platforms, communities, and voices they genuinely trust. The intersection of semantic relevance, domain authority, and audience affinity tells you which third-party properties are worth targeting. For one B2B audience, that might be Wired, Tom’s Guide, or a LinkedIn group that actively discusses vendors in a particular vertical. For another, it’s r/smallbusiness and a Substack newsletter with 40,000 subscribers.

Once you know where your audience spends time, you can create content and earn your spot in the conversation in those exact places. This is targeted, audience-first, performance-driven PR and organic strategy that puts your brand in the conversations already happening at the decision point.

The data underscores the importance of earned media. Across the top commercial sectors we analyzed, 93% of AI search citations come from third-party sources. If you’re only investing in content that sits on your own domain, you’re invisible to the systems now doing the heavy lifting of brand discovery.

Understood: Consistent signals across every surface

Getting found is necessary, but it’s not a standalone effort. If you’re getting found by machines, your brand is understood well enough to be surfaced.

LLMs go beyond crawling your website. They synthesize a consensus picture of your brand from everything about you that exists online: reviews, Reddit discussions, press coverage, YouTube commentary, Trustpilot ratings, forum threads, and more. If those signals conflict with what you’re saying about yourself, you have a problem.

A brand that claims premium positioning but has thousands of articles questioning whether it’s actually luxury, a history of heavy discounting, and a Trustpilot score of 1.3 isn’t going to be recommended by AI as a premium option, regardless of how well-crafted its homepage copy is. The algorithm has read the whole story, not just your version of it.

This means brand messaging consistency is now an SEO issue. Every piece of owned, earned, and paid content needs to reinforce the same core associations — because the model is building a cohesive picture from all of it. Conflicting signals confuse customers and actively suppress your AI visibility.

Digital PR plays a critical role here. It engineers the external narrative. Through strategic media placements, expert commentary, and search-informed coverage, you shape what journalists write about you and what the models learn about you. The query fan-out (the range of prompts a potential customer might use) requires positive, consistent answers across every touchpoint where an LLM might look.

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Chosen: Earning the trust signals that tip the decision

The third challenge is the hardest and arguably the most important. Trust has always been an SEO currency. As clicks decline and zero-click search becomes the norm, its importance has only grown.

Brand appearance in AI Overviews is most strongly correlated with branded web mentions (i.e., the number of times your brand is positively named across authoritative third-party sources), according to an Ahrefs study. This is essentially digital PR’s core output, and it is one of the most powerful levers available to organic marketers right now.

Based on the last 4,000 pieces of U.S.- and U.K.-based coverage we’ve driven for our clients, 91% of AI search citations include expert insight rather than branded content or product pages. This means expert-backed, editorially independent coverage is critical. That’s why your internal experts are your most valuable asset in the current landscape, and why brands investing in genuine thought leadership, original research, and data-backed studies are pulling ahead.

The three content formats consistently driving LLM feature inclusion are product roundups and listicles (getting your brand into trusted “best of” editorials), reliable data-backed research that journalists and LLMs cite as authoritative, and expert thought leadership that positions your people as the go-to voices in your category.

What doesn’t work (and what Google has explicitly flagged in its recent release of GEO guidelines) is seeking inauthentic mentions using methods like artificial link schemes, fake expert personas, and manufactured coverage. Models are increasingly adept at distinguishing genuine authority from manufactured signals, and the reputational downside of getting caught is severe.

None of this works as a one-time effort. Multiple studies, including research from Waseda University, have identified a correlation between AI brand visibility and content recency.

Brands that maintain a steady drumbeat of credible, expert-backed third-party coverage don’t just appear more often in AI responses. They appear more confidently.

Frequency and freshness of coverage both matter. It’s not enough to deliver a one-off PR campaign. This is a strategic investment that needs to be “always on.”

If AI can’t find you, customers won’t either.

Track your visibility across AI search, uncover missed opportunities, and grow your presence where customers are asking questions.

See your AI visibility

The framework in practice

When talking about brand discovery in 2026, three words are essential: 

  • Found: Map your audience’s real sources of influence and be credibly present there — across the fragmented ecosystem where discovery now happens.
  • Understood: Ensure that everything said about your brand tells a consistent story: one that matches how you want to be positioned and reinforces the associations that drive preference.
  • Chosen: Continuously generate genuine trust signals through earned coverage, expert commentary, and third-party validation so that when a human or a machine is deciding between you and a competitor, the weight of credible external evidence tips in your favor.

The brands winning in organic search right now haven’t cracked some new technical trick. They’ve built a reputation that’s genuinely worth recommending and made sure the machines know it. Stop chasing the algorithm and start building something worth finding.

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Web Design and Development San Diego

See how content from social and video platforms performs on Google Search

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Content creators and publishers use many channels beyond their own websites to reach their audiences.
As people gravitate toward firsthand perspectives and different content formats, we want to make
it easier for site owners and creators&mdash;even those without their own website&mdash;to get a consolidated view
of how all of their content is getting discovered on Search.

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How To Make AEO and GEO Profitable 

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Key Takeaways

  • AI visibility and AI profitability are not the same thing. Most teams are growing one without building the other. 
  • The four most common failure modes are optimizing for mentions over conversions, measuring AI visibility like rankings, chasing tactics without a revenue connection, and running AEO/GEO in a silo. 
  • AI-referred visitors convert at 8.3 times the rate of traditional traffic, close 62 percent faster, and generate 7 times more revenue per visitor. Those numbers only hold if your conversion architecture is built to receive them. 
  • The highest-performing campaigns share four traits: retrieval-ready content, strong authority signals, multi-channel distribution, and conversion systems designed for low-click environments. 
  • You can start building toward profitability in 90 days without a full overhaul, but the phases have to run in order. 

You might be showing up in ChatGPT answers. Getting cited in Google’s AI Overviews. Watching your brand mentions climb across the web. 

And still not seeing it move the revenue needle. 

That’s the problem a lot of marketing teams are grappling with right now. AI visibility is growing. Profitability isn’t keeping pace. After analyzing more than 100 AEO and GEO campaigns at NP Digital, I can tell you the issue isn’t the strategy itself. Most teams are simply optimizing for the wrong outcomes. 

A bar chart talking about where buyers discover brands.

If you already know what AEO and GEO are and you’re ready to actually make money from them, this post is for you. I’m going to break down exactly where the profitability gap comes from, what the winning campaigns have in common, and how to build toward revenue, not just visibility. 

Why Most AEO/GEO Efforts Don’t Make Money

Getting cited is not the same as getting paid. That distinction sounds obvious, but most AEO/GEO programs are structured around the former and hope the latter follows automatically. It doesn’t. 

After auditing campaigns across industries, NP Digital identified four failure modes that consistently prevent AI visibility from converting into revenue. 

An infographic covering why most AEO and GEO efforts fail.

Optimizing for mentions and citations. Mentions don’t pay the bills; conversions do. If your entire AEO/GEO program is oriented around getting named in AI responses, you’re measuring a proxy, not an outcome. A citation that doesn’t connect to a conversion path is brand awareness you can’t prove. 

Measuring AI visibility like rankings. Citation volume tells you nothing about pipeline. Teams that treat AI mention counts the same way they used to track keyword rankings end up with  

dashboards full of activity metrics and no way to show leadership what any of it is worth. 

Chasing AI-specific tactics in isolation. Schema updates, prompt engineering, entity optimization do matter, but tactics without distribution don’t compound. Teams that bolt on AEO/GEO tactics without building content and authority infrastructure underneath them tend to see short-term citation spikes that fade quickly. 

Running AEO/GEO separately from revenue goals. This is the biggest one. Visibility disconnected from business outcomes is overhead. The teams getting budget approved for AI search have tied it to pipeline, not impressions. 

NP Digital data tells the story clearly. AI visibility index climbed to 133 across tracked brands, while the profitability outcomes index reached 174. The gap between those two numbers is the opportunity this post addresses. 

The Profitability Gap: What Changes When Buyers Use AI

Buyers who find you through AI tools are not the same as buyers who find you through traditional search. They arrive differently, they behave differently, and they convert differently. 

The traditional funnel started with discovery through search, a click-through to compare options, an early-stage arrival that needed nurturing, and multiple touchpoints before a decision. The AI-influenced funnel runs differently. Research happens inside AI tools. Buyers validate brands before they ever click. They arrive later, already informed, and convert faster when trust exists. 

That shift is an advantage, but only if your conversion architecture is built to receive it. 

NP Digital data across 40-plus B2B and B2C campaigns makes the opportunity concrete. AI-referred visitors convert at 5.97 percent. Traditional traffic converts at 0.72 percent. Time to conversion drops from eight days to three. Revenue per visitor rises from $2.56 to $18.04. 

A bar chart comparing different AI-referred visitors and what converst faster.

The volume is still small. AI traffic accounts for about 0.58 percent of total traffic but drives 5.09 percent of sales. Lifetime value is also stronger at $325, up from $271 for Google-referred traffic. 

The math works. But capturing those numbers requires a funnel built for visitors who arrive intent-driven rather than still in the research phase. 

What the Profitable Campaigns Have in Common

Across the campaigns NP Digital analyzed, the ones generating real pipeline from AI search shared four traits. These traits reinforce each other, which is why building them together matters. 

A graphic talking about what profitable campaigns have in common.

Content Built for Retrieval

The content types that drive both AI citations and conversions are high-intent formats that answer specific questions buyers ask when they’re close to a decision. Not top-of-funnel awareness pieces. 

Comparison pages and alternatives content convert AI-referred traffic at 6.8 percent, the highest of any page type NP Digital tracked. First-party research and original data earn citations because they can’t be replicated elsewhere; they become reference points AI engines return to repeatedly. Bottom-funnel educational content and FAQ frameworks round out the top performers. 

Format is as important as topic. Lists and listicles account for 48 percent of AI citations in NP Digital’s research. Step-by-step guides come in at 17 percent. AI engines pull from content structured for easy parsing. Content not formatted for retrieval tends not to get retrieved. 

Strong Authority Signals

NP Digital scored six trust signals across ChatGPT, Gemini, Copilot, Claude, and Perplexity on a one-to-five scale. Third-party citations scored between 4.5 and 4.8, the single most consistent signal across every platform. Expert authorship scored between 4.0 and 4.6. 

AI engines reward signals that are difficult to manufacture: named, credentialed authors; external sources citing your content; consistent brand presence across multiple platforms. Publishing on your own site still matters, but earning coverage and mentions outside it is what drives citations. 

Multi-Channel Distribution

NP Digital tracked 75 brands across AI platforms and found a direct correlation between monthly publishing channels and AI visibility score. AI engines validate authority through repetition and consistency. Presence across YouTube, LinkedIn, Reddit, and PR channels signals to AI tools that your brand is real and relevant, not just self-published. 

A bar chart showing the top sources AI pulls from.

Conversion Architecture for Low-Click Environments

AI-referred visitors arrive pre-qualified. They’ve already done the research, compared options, and formed an opinion. A landing page designed for someone at the top of the funnel is the wrong tool for a visitor who’s already at the bottom. 

The brands capturing revenue from this traffic have built accordingly: fast pages, strong trust indicators placed prominently, simplified calls to action, bottom-funnel calculators and tools, and conversational paths that confirm a decision rather than explain a product category. 

A graphic showing the AI traffic conversion rate by different landing page types.

How to Measure AEO/GEO for Revenue, Not Just Visibility

The metrics most teams track are measuring the wrong thing. Rankings, raw traffic, click-through rate, AI mention counts, these are visibility metrics. They tell you whether people are seeing your brand. They don’t tell you whether it’s generating revenue. 

The teams getting AEO/GEO budgets renewed are the ones connecting citations to pipeline. That requires a different measurement stack. 

Stop tracking: raw rankings, organic traffic volume as a primary metric, click-through rate, AI mention counts, raw citation tracking, vanity impressions. 

Start tracking: influenced conversions, brand search lift, assisted pipeline, returning visitor quality, and conversion rate by intent source. 

NP Digital’s outcomes-first measurement framework organizes this into three tiers. At the foundation: visibility and influence signals, including brand search volume, share of voice, community engagement, and earned media. In the middle: demand signals, including multi-touch attribution, AI-driven lead scoring, behavioral intent, and consumption depth. At the top: business outcomes, including revenue, CAC:LTV ratio, retention, expansion, and advocacy. 

Build reporting from the bottom up. Track from the top down. The goal is a dashboard leadership reads as a business document, not a marketing activity report. 

NP Digital research shows how much KPI priorities have shifted. Leadership priority for rankings dropped from 88 to 63 between 2024 and 2026. Pipeline contribution rose from 23 to 70. Revenue growth held steady at 96 to 98. Your measurement framework needs to reflect where leadership attention already sits. 

A graphic comparing raknings and traffic over time.

A practical starting point: for every vanity metric on your current dashboard, add one outcome metric alongside it. That shift is often enough to change the budget conversation. 

The 90-Day Plan to Turn AEO/GEO Into Revenue

You don’t need to overhaul everything at once. You do need to run the phases in order. Each phase builds on the one before it, and skipping ahead consistently produces weaker results. 

Days 1 to 30: Audit and Fix the Foundation

Start by auditing your current AI visibility across ChatGPT, Gemini, Claude, Perplexity, and Google AI Overviews. Search your brand name and core topics. Note where you appear, where competitors appear instead, and where no one appears. Those gaps are your priority list. 

From there, identify high-intent content gaps where competitors are getting cited and you aren’t. Improve structured formatting across your highest-traffic pages with clear headers, FAQ sections, and concise direct answers. Strengthen author and entity signals. Clean up trust indicators including reviews, third-party citations, and brand consistency across platforms. Apply schema and retrieval-friendly formatting throughout. 

One consistent finding across NP Digital’s audits: brand authority, PR and mentions, and community visibility are almost always the lowest-scored areas. Start there before investing more in content production. 

Days 31 to 60: Create and Distribute for Profitability

Create the content types that drive both citations and conversions: comparison pages, original research and proprietary data, buyer guides, and FAQ expansions. These formats earn citations and convert the traffic those citations send. 

Distribute across LinkedIn, YouTube, PR placements, expert commentary opportunities, and community channels like Reddit. The goal is consistent presence across multiple ecosystems. AI engines validate authority through repetition across platforms, not just depth on your own site. 

Days 61 to 90: Optimize Conversion and Measurement

With the foundation fixed and the content layer built, optimize for what happens when AI-referred visitors arrive. 

Improve bottom-funnel UX for high-intent visitors. Add calculators, tools, and simplified calls to action. Optimize assisted conversion flows. On the measurement side, track influenced pipeline from AI-assisted traffic, compare conversion quality across platforms, and build an executive dashboard tied to revenue rather than visibility metrics. 

The window to establish AI search presence is real and won’t stay open indefinitely. The brands building this infrastructure now are accumulating authority signals that compound over time and become increasingly difficult for competitors to overcome. 

FAQs

How do you connect AEO/GEO to revenue? 

The connection runs through your measurement framework and your conversion architecture. On the measurement side, track influenced conversions, assisted pipeline, and brand search lift rather than citation counts. On the conversion side, build landing pages and CTAs designed for visitors who arrive already informed. AI-referred visitors are pre-qualified and need a fast path to a decision, not an introduction to your product category. 

What metrics should you track for AEO/GEO profitability?

Move away from rankings, raw traffic, and citation volume as primary KPIs. The metrics that connect to profit are influenced conversions, brand search lift, assisted pipeline, returning visitor quality, and conversion rate by intent source. Build toward a three-tier measurement stack: visibility and influence at the foundation, demand signals in the middle, and business outcomes at the top. 

What content converts best from AI-referred traffic? 

Comparison pages and alternatives content convert AI-referred traffic at 6.8 percent, the highest of any page type in NP Digital’s research. First-party research, bottom-funnel educational content, and FAQ frameworks also perform well. Format matters as much as topic. Lists and listicles account for 48 percent of AI citations because they’re structured for easy extraction. 

Conclusion

The winners in AI search don’t just focus on earning the most citations but make sure they can turn citations into pipeline. 

That requires connecting visibility to conversion architecture, measuring outcomes rather than activity, and building the content and authority signals that AI engines reward consistently over time. None of those things happen by accident. 

The brands doing this work now are building compounding advantages. Authority signals accumulate. Citation patterns stabilize. Conversion infrastructure improves with data. Starting later means starting behind. 

If you want support building an AEO/GEO strategy tied to revenue rather than just visibility, NP Digital’s team works through exactly this kind of profitability infrastructure with clients. 

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