July 2026 - Dubado Solutions

How to Get the Most Out of the New AnswerThePublic (2026 Guide)

July 31, 2026/0 Comments/in Web Design/by Dubado Solutions

If you just logged into the new AnswerThePublic for the first time, there’s a lot more going on than the tool you might remember.

The version most people know was a keyword visualization tool. Type in a topic, get a wheel of questions people are searching. That version was useful. The new AnswerThePublic is a different category of product entirely.

It’s an AI content engine. You give it your website. It understands your business. It surfaces the keyword opportunities most likely to drive results for you specifically. It researches the competition. It writes the article. It publishes it to your WordPress site. And it repeats that process on whatever schedule you set.

This guide walks you through every part of the product in the order you’ll actually use it, so by the end, you’ll know where to start, what each feature does, and how to get your first published article live.

Two Ways to Start a Search

AnswerThePublic gives you two entry points, and the one you choose shapes everything that comes after.

The first is Analyze My Website. You drop in your URL, and AnswerThePublic reads your site to understand your business before you search for anything. The second is Search Keywords, the classic mode. Type in a keyword, get insights.

Both work. But if you use your website URL, every keyword idea, every content recommendation, and every article the tool generates gets filtered through your actual business context. Instead of generic volume-ranked results, you see the opportunities that actually move the needle for your site specifically.

For most users, starting with Analyze My Website is the right call.

The Business Summary: The Brain Behind Everything

When you analyze your URL, AnswerThePublic builds a Business Summary for you automatically. It includes your business name and type, your target customers, your key features and unique value proposition, your geographic focus, and the topics you should focus on for content.

You can view and edit this anytime, from the Business Summary button at the top right of the Suggested For You page, or inside Settings. This profile is what makes every recommendation specific to you rather than generic. If something’s off about how we characterize your business, fix it. Everything downstream improves when you do.

The Left Sidebar: Your Four Main Surfaces

Home is your search history. Every keyword you’ve ever searched, across every source: Google, Bing, ChatGPT, Gemini, YouTube, Amazon, and Instagram. Filter by region, language, provider, or date to find anything fast.

Suggested For You is your content command center. It’s where most users should spend most of their time.

Content Schedule is your publishing calendar. Set how many articles you want generated per week or per day, drag and drop to reorganize, and see status, ranking position, and search volume next to each item so you’re scheduling with context, not guessing.

All Content is your full article library. Every article generated, published, or sitting in queue. Searchable and sortable.

The left sidebar with all four sections visible: Home, Suggested For You, Content Schedule, and All Content.

Suggested For You: Where Most Users Should Spend Most of Their Time

This page is designed to eliminate the blank-page problem. When you land here, you see three things.

At the top: AI-generated content ideas, each tagged with one of three opportunity signals: Best for AI Visibility, Best Short-tail Opportunity, or Best Long-tail Opportunity. Each idea includes a reason why it’s a good opportunity for you specifically, based on your Business Summary. These are often the hidden gems that most keyword tools would never surface because they require understanding your business, not just your niche.

Below the suggestions: The classic AnswerThePublic keyword wheel, now grouped by topic cluster so related ideas stay together visually.

Below the wheel: A full table of your next 50 content ideas, ranked, categorized, and ready to generate. Click any one to start the content process.

AI suggested content ideas from AnswerThePublic

Clicking Any Keyword Opens the Full Research View

When you click into a specific keyword, you get a complete research page in a single view: search volume, CPC, and your Content Studio rank for that keyword.

Then the Top Ideas wheel, now with two layers. The inner ring shows what people are asking AI models about this topic. The outer ring shows what they’re typing into search engines.

Below that, the AI Prompts table: every AI prompt related to your topic, paired with three signals new to this version:

Intent: what the user is trying to accomplish with this query
Sentiment: the emotional tone of how AI models are answering this question
Brands: which companies are being mentioned in AI responses for this query

Keep scrolling and you’ll see Organic Searches from Google and Bing, a People Also Ask mindmap you can expand into a full tree view, Social Media results from YouTube, TikTok, and Instagram, and Shopping data from Amazon. Every source. One view. No tab-switching.

he keyword detail research page for a sample keyword, with the Top Ideas wheel (inner AI ring and outer search ring visible), the AI Prompts table with Intent/Sentiment/Brands columns, and the Organic Searches section below.

One-Click Content Generation from Anywhere

You can generate content with one click from anywhere on Suggested For You, and from anywhere on a keyword detail page. From the top suggestions. From the keyword wheel. From the table. From a People Also Ask node.

Before you hit generate, you get a review screen to check the target keyword, edit the content idea, pick a title, and see why this topic is relevant to your business.

When you click Generate Now, Content Studio runs a five-step editorial pipeline:

Researches the top-ranking pages for your keyword
Pulls the facts and statistics that matter
Builds an outline based on what’s already winning in the SERP
Writes the article in your brand voice
Refines it for natural language and flow

This isn’t a raw AI dump. It’s a structured editorial process trained on real ranking data. What used to take an SEO team days, Content Studio produces in minutes.

Full Control Inside the Article Editor

Once your article is generated, you have full control. Add images. Replace the cover image with the AI generator or upload your own. Rewrite any paragraph by hand.

And this is the capability most new users don’t discover: select any section and ask the AI to regenerate just that part. Not the whole article. Just the paragraph or sentence that needs a different angle. That single feature alone saves hours of editing in a typical workflow.

A plagiarism score runs in the background the entire time. By the time you hit publish, you know the content is uniquely yours.

The Right-Panel Tabs

Overview shows your target keyword, monthly searches, difficulty, plagiarism score, word count, and all internal and external links in one place.

SERP shows the top Google results currently ranking for your keyword, without opening a new tab.

Research shows every fact the article cited, with numbered sources and clickable links. Verify any claim before you publish.

Exporting, Saving, and Publishing

From the top of the editor: export to PDF, export to Markdown, save a draft, or publish directly. The Share button auto-generates captions for Twitter/X, LinkedIn, Instagram, and email, following best practices and character limits for each platform. Write once, distribute everywhere.

Settings: Set It and Forget It

Publish Controls connects your WordPress site. Choose Draft or Published as your default, or enable Auto Publish to send new articles live without manual review. For teams running a daily content cadence, this is transformative.

Image Styles gives you sixteen visual templates (corporate illustration, cartoon, photographic, and more), or let the AI Style Picker choose the best style for each article based on the topic.

Brand Voice lets you pick from templates like The Straight Shooter, The Grounded Guide, or The Curious Storyteller, or build a fully custom voice profile. This is what makes generated articles sound like your brand instead of a generic AI output.

Article Generation controls structure: set length from 500 to 5,000 words, toggle external links, add your sitemap for automatic internal linking, and schedule daily generation at a specific time.

Business Summary is the editable brand profile. Come back here anytime your business evolves: a product launch, a new service, a new audience segment.

Localization sets your content language and target country. Content quality improves significantly when these match your actual audience.

The Fastest Path to Your First Published Article

Four steps in order:

Add your website on first search, so the Business Summary gets built automatically.
Go to Suggested For You and pick an idea tagged Best for AI Visibility or Best Long-tail Opportunity.
Generate your first article with one click. Review the title and keyword, then hit Generate Now.
Connect WordPress in Settings under Publish Controls and publish.

The Bigger Picture

The thesis behind the new AnswerThePublic is simple: your website already tells us what your business is, what you sell, and who you’re selling to. Your customers are already searching for it, in Google, in AI tools, on YouTube, on Amazon.

The gap between what your customers are searching for and what you’ve published is your content opportunity. AnswerThePublic closes that gap automatically.

You just needed a tool smart enough to connect the dots.

Frequently Asked Questions

What’s different about the new AnswerThePublic vs the original?

The original was a keyword visualization tool. The new version adds AI content generation, a Business Summary that personalizes every recommendation to your site, a publishing calendar, WordPress auto-publish integration, and a full article editor with plagiarism scoring. It’s a complete content production system built on top of the original keyword research foundation.

Does AnswerThePublic write the full article, or just an outline?

It writes the full article following a five-step editorial pipeline: competitor research, fact gathering, outline, drafting, and refinement. You can edit any section manually or use selective regenerate to rewrite specific paragraphs.

Can I use AnswerThePublic if I don’t have a WordPress site?

Yes. Export articles as PDF or Markdown, or copy and paste the content directly to any platform.

Does it work in languages other than English?

Yes. AnswerThePublic supports multiple languages and regions. Set your content language and target country under Localization in Settings for best results.

The new AnswerThePublic is live, and you can try it free, no credit card required. Try the new AnswerThePublic.

Read more at Read More

TikTok Gives Creators More Control Over Keyword Metadata: What It Means for Social Search

July 29, 2026/0 Comments/in Web Design/by Dubado Solutions

Key Takeaways

TikTok now allows creators and brands to manage the keywords associated with their video metadata.
Keyword suggestions will still be reviewed by TikTok to help prevent spam and misleading tagging.
The update reflects TikTok’s continued evolution into a search-first discovery platform.
Brands should incorporate metadata optimization into their broader TikTok SEO and content strategies.
As social search continues to grow, keep a close eye on keyword performance and audience relevance.

TikTok has introduced a new way for creators and brands to improve how their content is discovered.

The platform now allows users to manage the TikTok keyword metadata associated with their videos, including removing irrelevant keywords and suggesting new ones that better match the content. TikTok will continue reviewing these changes before they are applied, helping maintain the quality and accuracy of search results.

On the surface, this looks like a minor product tweak. It actually points to a broader shift in how content gets discovered on the platform.

As more users turn to TikTok search for product recommendations, tutorials, reviews, and local businesses, the keywords attached to a video play a bigger role in determining who sees it. For brands, this creates another opportunity to improve content relevance while supporting broader social search optimization and AI visibility efforts.

Here’s what changed, why it matters, and how marketers should respond.

What Changed With TikTok Keyword Metadata?

TikTok’s latest update gives creators more influence over the metadata connected to their videos. Rather than relying solely on automated systems, creators can now help ensure the keywords associated with their content better reflect what viewers will actually find.

Source: https://influensly.com/how-to-search-on-tiktok/

Creators Can Now Manage Metadata Keywords

Creators and brands can now review the keywords attached to their videos, remove terms that don’t accurately describe the content, and suggest new keywords that provide better context.

This added control allows creators to improve the accuracy of their TikTok metadata, making it easier for the platform to understand what each video is about. Better metadata also helps align videos with the searches users are actively performing on TikTok.

Managing search keywords in the TikTok interface.

Source: https://www.socialmediatoday.com/news/tiktok-lets-users-add-relevant-keywords-to-metadata/818507/

TikTok Will Continue Reviewing Keyword Changes

While creators can recommend changes, TikTok isn’t handing over complete control.

The platform will review suggested keywords before applying them to prevent spam, keyword stuffing, or misleading descriptions. This review process helps maintain the quality of search results while giving creators more input into how their content is categorized.

The result is a balance between creator flexibility and platform integrity, ensuring that TikTok keyword metadata remains useful for both users and the recommendation system.

Why This Update Matters

Keyword metadata now plays a central role as TikTok expands beyond entertainment into a destination for search and discovery.

This latest update reinforces that shift by giving creators more opportunities to improve how their content connects with user intent.

Search Is Becoming a Bigger Part of the TikTok Experience

People are no longer using TikTok only to scroll through their For You feed. Many now use the platform as a search engine to find recipes, product reviews, travel tips, local recommendations, and answers to everyday questions.

As TikTok search continues to grow, accurate keyword metadata helps the platform understand which videos are most relevant for a given query. That makes search optimization a core part of content strategy, not an afterthought.

A graph depicting how many people use TikTok for search.

Source: https://www.socialmediatoday.com/news/almost-half-of-us-consumers-use-tiktok-as-a-search-engine/813576/

Better Metadata Improves Content Relevance

More accurate metadata doesn’t guarantee more views, but it can improve the quality of visibility by helping the right audience discover the right content.

For brands, this creates stronger alignment between content and user intent while supporting long-term TikTok discoverability. Rather than optimizing only for reach, marketers can focus on attracting users who are actively searching for information related to their products or services.

Brands that embrace these changes early will be better positioned as search continues to evolve. On-platform and off-platform search visibility is being shaped more and more by social search keyword performance, so brands that move quickly on new visibility tools will have an edge.

What This Means for Your Social SEO Strategy

TikTok’s latest update signals a broader shift in how brands should approach content discovery across digital platforms.

Treat TikTok Search as Part of Your SEO Strategy

Social platforms and search engines continue to influence one another, making TikTok SEO a core part of a broader digital strategy.

Keyword research shouldn’t stop with Google. Understanding how audiences search on TikTok can help brands create content that performs across multiple discovery channels while supporting broader AI visibility initiatives.

Monitor Performance Beyond Views

Views remain an important metric, but they don’t tell the whole story.

As metadata optimization becomes part of the publishing workflow, brands should also monitor search placement, engagement quality, audience relevance, and the keywords driving discovery. These insights provide a clearer picture of whether content is reaching the users it was designed for.

Social Search and SEO Are Becoming More Connected

The way people discover information continues to change.

Users move between traditional search engines, AI-powered assistants, and social platforms depending on what they’re looking for. TikTok’s latest metadata update reflects this shift by placing greater emphasis on keyword relevance and search intent.

For marketers, that means social search optimization should no longer exist in its own silo. Keyword strategies developed for search engines can inform content on social platforms, while insights from TikTok search can uncover new opportunities for SEO and content marketing.

As search behavior evolves, the brands that create content around how people actually search, regardless of platform, will be in the strongest position to earn visibility.

FAQs

What is TikTok keyword metadata?

TikTok keyword metadata refers to the keywords associated with a video that help TikTok understand its content and determine when it should appear in search results or recommendations.

Can creators edit TikTok metadata?

Creators can now suggest changes to the keywords attached to their videos, including removing irrelevant terms and recommending more accurate ones. TikTok reviews these suggestions before applying them.

Why is TikTok focusing on search?

More users are relying on TikTok search to discover products, businesses, tutorials, and recommendations. Improving keyword metadata helps the platform deliver more relevant search results.

How does TikTok keyword metadata affect visibility?

Accurate TikTok metadata helps connect videos with relevant searches, improving discoverability and helping brands reach audiences that are actively looking for related content.

Conclusion

TikTok’s new keyword management tools might look like a small feature update. The bigger story is what they signal about where the platform is headed.

The platform continues to invest in search, giving creators more opportunities to improve how their content is understood and discovered. For brands, this means TikTok keyword metadata should become part of a broader content strategy rather than an isolated platform feature.

As TikTok SEO, social search optimization, and AI visibility become more connected, optimizing metadata is another way to ensure your content reaches the audiences searching for it. Brands that begin testing these features now will be better prepared as social platforms continue expanding their role in how people discover information.

If you want to stay ahead of TikTok’s latest search developments, reach out to the NP Digital team to learn how emerging search experiences can fit into your long-term marketing strategy.

Read more at Read More

Platform properties roll out globally, plus a new social and video performance guide

July 29, 2026/0 Comments/in Google Search, Web Design News/by Dubado Solutions

Earlier this month, we announced platform properties for Search Console,
allowing you to track how your social and video posts on Instagram, TikTok, X, and YouTube perform on Google Search,
Discover, and Google News. Today, platform properties are globally available to everyone.

Read more at Read More

Attribution vs. incrementality: Why you need both

July 28, 2026/0 Comments/in Search Engine Land, Web Design News/by Dubado Solutions

Attribution vs. incrementality: Why the difference matters

Incrementality and attribution are two approaches to measuring marketing performance that are frequently discussed as though they are competing lenses viewing the same data. But they’re actually designed to answer very different questions, using different forms of evidence.

Attribution asks which observed marketing touchpoints should receive credit for a conversion. Incrementality asks whether the marketing activity caused additional conversions that wouldn’t have occurred without it.

A refresher on attribution

Attribution is the favored child of marketing analytics teams everywhere, circa 2015. Marketers discovered that some conversion paths contained multiple touchpoints across the digital landscape, like this:

Display → Paid Social → Organic Search → Email → Purchase.

That raised questions about which channel should get what “credit”:

Should the display ad get the most credit for the conversion because it was the first exposure?
Or should the email, because that’s the touchpoint that finally convinced the user to buy?
And what about the social ad and the organic presence in the middle?

That’s where attribution modeling came in. Attribution modeling provided frameworks for deciding how that credit should be distributed. Some models assigned the entire conversion to a single touchpoint. Others divided it among multiple interactions.

So if the final value of the conversion is $100, an attribution model tells marketers that display can take credit for $30, email for $30, and the remaining $40 is split between paid social and organic.

Then, when you’re evaluating the success of your channels, you have a more nuanced framework for distributing revenue credit. And when you’re deciding on what channels get what budget for the next fiscal year, you have a way to compare and contrast.

Example: How a $100 conversion might be distributed across four marketing touchpoints.

Attribution model	Display	Paid Social	Organic Search	Email	How credit is assigned
First-touch	$100	$0	$0	$0	All credit goes to the first observed interaction.
Last-touch	$0	$0	$0	$100	All credit goes to the final observed interaction before purchase.
Linear	$25	$25	$25	$25	Credit is divided equally among every observed touchpoint.
Position- based	$40	$10	$10	$40	The first and last interactions receive the most credit, while the middle interactions split the remainder.
Time-decay	$10	$20	$30	$40	Touchpoints receive progressively more credit as they occur closer to the conversion.
Data-driven	$30	$20	$20	$30	Credit is distributed according to each touchpoint’s estimated contribution to the conversion.

Note: These are simplified examples. Position-based models can use different weighting rules, time-decay allocations depend on timing, and actual data-driven models vary.

See exactly how your competitors win.

Uncover the keywords, ads, landing pages, and strategies driving your competitors’ paid search success—and find your next opportunity to outperform them.

Analyze your competitors

Incrementality 101

Incrementality began to gain renewed interest from marketers around 2020.

Rather than dole out credit for a sale to different touchpoints and channels based on a mathematical equation, incrementality relies on carefully guardrailed tests of real, live sales data that attempt to prove the “true” impact of a marketing activity rather than its correlation. Incrementality tries to answer the question:

How many of these sales were actually caused by this campaign, without counting how many would have happened regardless?

The answer to that question is what marketers call lift. And through tightly controlled tests leaning on the scientific method, marketers were able to isolate the difference in sales between a group exposed to the marketing activity and an equivalent group that wasn’t exposed to marketing materials.

Incrementality is best explained through an example.

Let’s say you want to discover the lift of a given marketing campaign. So you divide your audience into two groups: a control group of folks who won’t be exposed to the campaign and an exposed group that does see the campaign.

You run your campaign for 30 days, then look at the results. While the exposed group completed 1,000 purchases, the control group completed 800 purchases. The incremental lift of the campaign would be 200 purchases.

An attribution model could associate many or all 1,000 purchases with the campaign. It would allocate the value across the platforms and touchpoints involved according to the model you choose.

Incrementality, on the other hand, would conclude that only those 200 additional purchases were actually caused by the campaign.

Dig deeper: Why attribution and impact are no longer the same thing in PPC

Get the newsletter search marketers rely on.

See terms.

Using attribution and incrementality together

Where marketers go wrong is when they go all in on either framework. The two concepts can play nicely together (provided you’re using the right one to answer the right question). If you’re looking to optimize your campaigns or deep dive into the user journey of your customer, attribution is going to be your best friend, helping you evaluate platforms and touchpoints by giving you a shared success metric with which to compare them.

If, on the other hand, you’re defending your budget from a proposed cut, incrementality is going to be your strongest source of evidence regarding which channels actually create additional business with their budget, rather than capturing business that would have happened anyway.

	Attribution	Incrementality
Primary question	Which observed marketing touchpoints should receive credit for a conversion?	How many additional conversions occurred because of the marketing activity?
Best use case	Ongoing campaign optimization, understanding customer journeys, and allocating credit across measurable channels.	Validating whether an investment creates additional business value and informing higher-level budget decisions.
Main blind spot	Correlation is not causation: a touchpoint may receive credit for a conversion it did not actually create.	Tests can be expensive, slow, or difficult to design, and results may not explain which individual touchpoints influenced the customer.
Most likely stakeholder	Channel managers, performance marketers, platform teams, and marketing analytics teams.	Marketing leadership, finance, data science, growth strategy, and budget owners.

Where platforms get confused by attribution and incrementality

If there’s one question that has haunted me throughout my career, it’s this one: “Why don’t these numbers match?”

Most often, it’s asked when a channel platform’s reported revenue or conversions differ from the numbers found in the client’s CRM, web analytics, or other source of truth. They almost never line up perfectly.

What can be tough to explain succinctly to a client is this: The fact that they differ doesn’t necessarily mean either is incorrect. Each system applies its own logic based on the interactions it can observe, which conversions should qualify for credit, and how long after an interaction credit can still be attributed. But neither is “wrong.”

An advertising platform may correctly observe and report that a customer viewed or clicked on an ad before purchasing. But evidence that an ad was seen before a purchase isn’t necessarily proof that the ad caused it, nor is it proof that the ad didn’t cause it.

This becomes particularly important with automated campaigns, especially as platforms continue to push these automated solutions on marketers. Automated systems are designed to maximize performance based on the conversion signals defined inside the platform. They’re simply not designed to maximize performance based on your carefully calculated incremental lift test results.

As a result, automated campaigns target audiences, placements, and queries already associated with users likely to convert, such as existing customers, branded searchers, and remarketing audiences. Those conversions may be entirely valid according to the platform’s attribution model, while creating less additional revenue than the campaign report implies.

In other words, automated campaigns can increase the number of conversions credited to a given campaign without actually causing an equal increase in total sales.

Dig deeper: Your ROAS looks great — but is it actually driving growth?

A note on in-platform lift studies

It’s true, platforms are increasingly offering lift studies and other incrementality-focused tools. But it’s a mistake to assume that incremental value is automatically incorporated into automated campaign optimization.

After all, “data without insights is meaningless, and insights without action are pointless.” In other words, a lift study will only affect performance if and when someone applies its findings to the campaign’s objectives, inputs, or budget decisions.

A platform like Google Ads may provide a controlled lift experiment, but unless the advertiser applies the test findings — or selects a campaign setting explicitly designed to optimize for incrementality — the measurement system and the delivery system are still going to be working toward two different definitions of success.

Some platforms are starting to address this. Meta, for example, now offers a very promising incremental attribution model intended to optimize delivery toward conversions it predicts were directly caused by advertising. For now, though, that’s a specific optimization choice that, again, requires action by the advertiser and isn’t an inherent feature of every automated campaign.

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

Know which question you’re trying to answer

In sum, attribution and incrementality aren’t competing methods for finding one definitive metric. They’re different tools designed to answer different questions. And like most tools, they perform best when they’re doing the job they’re designed for. You wouldn’t try to use your Allen wrench as a hammer, would you?

Attribution helps us marketers understand which touchpoints contributed to a conversion and provides a shared basis for comparing channels. Incrementality helps businesses understand whether their marketing investment generated additional conversions that wouldn’t have occurred otherwise.

The best marketers need both. While attribution provides the ongoing signals needed to optimize campaigns and understand customer journeys, incrementality helps validate whether those optimizations are creating new business value or simply capturing demand that already existed.

As automated campaigns take greater control over targeting, placements, bidding, and budget allocation, understanding both sides will only become more important. A system can become exceptionally efficient at maximizing attributed conversions without becoming equally effective at producing incremental growth.

So the next time a platform report contradicts your CRM, don’t assume either number is wrong — ask which question each number was designed to answer.

Dig deeper: The end of easy PPC attribution — and what to do next

Read more at Read More

Putting Google Ads AI Max’s automated ad copy to the test

July 28, 2026/0 Comments/in Search Engine Land, Web Design News/by Dubado Solutions

One of AI Max’s capabilities is creating assets for you. This can take the strain off the PPC team by reducing the need to customize ads for every single ad group.

We wanted to quantify how well the text customization feature worked for various companies, so we ran tests with three different companies to understand how much we should or shouldn’t be using text customization.

As we’re a software company that helps companies manage their PPC accounts, not the agency doing the work, we worked with the companies to guide them on how to set up and analyze the tests.

We’ll start by examining the process we used to help the companies set up the tests so you can run this experiment yourself, and then we’ll examine the test results.

Text customization and messaging restrictions

Before you run this test, you need to understand the features involved.

First, you need to turn on AI Max and the text customization feature.

Since this is AI working in the background for you, it can tailor the assets in every single ad group to the keywords in that group. While this sounds nice, the assets can sometimes be used to run promotions or advertise products and services you don’t offer.

To help guide the system, you should apply messaging restrictions when using auto-created assets.

Messaging restrictions can help guide the system on what the ads should and shouldn’t say. In addition, you can give it rules around your brand guidelines.

The overall process for creating good messaging restrictions is fairly simple and only takes an hour or two:

Use a prompt in Gemini to create your initial assets.
Then use a prompt to make the ads overly promotional, create promises you don’t like, etc. Essentially, you’re having the system write ads you don’t approve of and want to ensure Google doesn’t create assets like these on your behalf.
Create messaging restrictions to stop the assets you don’t like from being generated.
Use a prompt to create new, highly promotional ads with your messaging restrictions until all created assets fit your company’s messaging guidelines.

Dig deeper: Is your account ready for Google AI Max? A pre-test checklist

See exactly how your competitors win.

Uncover the keywords, ads, landing pages, and strategies driving your competitors’ paid search success—and find your next opportunity to outperform them.

Analyze your competitors

Choosing the campaigns to test

We wanted to see how these assets performed across different types of companies and different levels of campaign optimization.

Therefore, we first chose three business types:

Ecommerce.
B2B lead gen.
B2C lead gen.

In each account, we only wanted campaigns that met a specific set of criteria:

Did not use brand keywords.
Spent at least $20,000 per month.
Had at least 100 ad groups.

Most companies have some campaigns that are their best performers, where the team spends a lot of time optimizing the campaigns. Then you have your campaigns that are long-tail, do well in aggregate, but receive less attention.

To understand how well text customization was going to perform, we used two campaigns that were highly watched and two that were somewhat neglected from each account.

We also wanted to see how the new assets performed, so we chose campaigns that didn’t rely heavily on pinning, which excluded many of the highest-spending campaigns, since most large and enterprise companies extensively use pinning in their top campaigns.

Finally, we wanted to test only the assets, not URL expansion, so none of the campaigns used the final URL expansion feature.

Asset review

As you run these tests, you’ll want to monitor the auto-created assets and remove any that don’t align with your brand messaging or offers.

When looking for AI-generated assets, it’s essential that you change the default filters to include the ad, as this filter isn’t chosen by default.

Google Ads AI Max - Asset review filters

The companies in the test monitored these assets as they were created and removed them before they received many impressions. Ignoring the B2B results (more on that later), approximately 19% of the auto-created assets were removed.

Get the newsletter search marketers rely on.

See terms.

The results

Ecommerce campaigns

This ecommerce company sells over 100,000 SKUs, so it has a lot of products, and many users are accustomed to visiting the website and searching again if the landing page doesn’t have the specific product they’re looking for.

At first glance, it appeared that both AI Max and text customization were incredibly successful.

However, after further analysis, we found that AI Max was poaching impressions, clicks, and conversions from other campaigns and that the overall revenue for the account declined.

The company added many search terms as keywords to help Google prioritize the correct ad group and campaign. Then it added more negative keywords and audience lists to slow cannibalization and reran the tests.

We observed that AI text customization wasn’t as effective as human management of assets for highly optimized campaigns. However, it was good at assisting the long-tail campaign.

Dig deeper: Why your brand campaign may not be ready for AI Max

B2B lead generation

When creating RSA assets for B2B companies, one of the most important considerations is how to properly prequalify your audience through your asset usage. You want your ads to be unattractive to B2C searchers and appeal to B2B searchers.

This company had previously used pinning quite extensively across its assets to ensure this qualification. However, it wanted to see how well Google could optimize its accounts, so it removed its pins during this test.

The nuance of prequalifying a B2B audience is one that text customization clearly doesn’t understand. The B2B accounts saw their CTRs skyrocket. However, the conversion rates declined significantly since the ads were attracting many B2C searchers.

The messaging restrictions included language to ensure the assets prequalified users as part of a B2B audience. While some of the assets met this criterion, the overall ads that were shown to users didn’t properly appeal to B2B buyers.

The other tests ran for over a month. However, after three weeks, the results were so poor that this company stopped the tests and went back to pinning its ads and removing the auto-created assets. Within a week, its results returned to their pretest levels.

B2C lead generation

Our last test was with a B2C lead generation company that localizes its ads through geographic ad copy or geographic insertion.

Its optimized campaigns had tailored ad copy for the keywords in every single ad group. Its long-tail campaign had a few headline assets in each ad group, tailored to the keywords, but most assets were reused across ad groups.

Seeing formulaic ad copy in lower-priority campaigns is quite common, and this is where we were hoping to see AI auto-created assets perform well, since there was a lot of opportunity for better ads.

AI Max auto-created assets didn’t disappoint in these low-priority campaigns. While these assets didn’t outperform the assets humans had spent a lot of time testing in their top campaigns, AI performed quite well for the long-tail campaign.

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

Where AI Max automated assets work best

AI is a fantastic tool at your disposal. For ads where you’re spending a lot of time thinking through your messaging, it can be good at helping you generate ideas, but human-created assets still outperform AI-generated assets.

If you need specific types of assets, such as prequalifying users for B2B audiences, specific offers, or short-term promotions, then you should take control of the assets yourself and not turn them over to AI.

However, auto-created assets shine when you just don’t have enough time to fully optimize your creatives. Using AI to create your assets, assuming you have good messaging restrictions and regularly review these assets, can help your overall performance.

We’re still a long way from AI being a turn-on-and-forget setting. It needs babysitting and oversight. However, having AI do the heavy lifting in areas where you don’t have the time to fully optimize, and then spending your time reviewing and tweaking the outcomes, is the best use of AI in ad creation.

Read more at Read More

Google indexed Claude Chats because Anthropic didn’t block your private chats from search engines

July 28, 2026/0 Comments/in Search Engine Land, Web Design News/by Dubado Solutions

Sadly, every so often, you hear of content being indexed and exposed on Google and other search engines. Often the issue is not necessarily with the search engine but with the site that hosts and holds that information. Those sites often do not set the proper blocking mechanisms in place to communicate to Google and other search engines that the content should not be indexed and shown within the search results.

That is what happened recently with Anthropic’s Claude Chats showing up in Google, Bing and other search engines.

More details. Wired’s story named Private Claude Chats Exposed in Google and Bing Search Results explained how private chats from Claude were found on the web on Google, Bing and other search engines. The chats included politics, health discussions and more, all pretty sensitive chats. “Claude allows users to share with other people “snapshots” of chats by creating a public URL to a specific chatbot thread,” Wired explained.

“The reasons some of these URLs were indexed by major search engines comes down to the basic functions of websites, search engines, and the collision of the two when generative AI gets in the mix,” Wired added.

The primary issue is that if you block both using robots.txt directive and use noindex on that page, search engines like Google and Bing won’t be able to see the noindex tag since the crawlers won’t be able to access the page with the directive.

Doing a site command for [site:claude.ai/share] would return hundreds of chats from Claude over the weekend, but now those results have been removed.

Glenn Gabe said on X that he wished these journalists would have spoken to an SEO before covering the story. “It’s filled with bad information. If you block via robots.txt AND noindex the page, Google and Bing *cannot* see the noindex tag since they can’t crawl the page and see the tag in the HTML,” he explained correctly.

This is not new information; Google’s own documentation has a huge notice at the top of the page that says in bold and red highlights:

“Important: For the noindex rule to be effective, the page or resource must not be blocked by a robots.txt file, and it has to be otherwise accessible to the crawler. If the page is blocked by a robots.txt file or the crawler can’t access the page, the crawler will never see the noindex rule, and the page can still appear in search results, for example if other pages link to it.”

What Google said. Ned Adriance, a Google spokesperson from the Google Search side of the team, understands how this works. And he told Wired, “Neither Google nor any other search engine controls what pages are made public on the web, and these pages were indexed across many search engines.” He added, “We give site owners clear controls to decide whether pages can be crawled or indexed, and we always respect those directives.”

For some reason, Microsoft Bing and Anthropic did not provide any comment to Wired on the issue.

Why we care. This shows the importance of consulting with an SEO who understands how to ensure the right pages are indexed and visible in search and maybe more importantly, the pages you do not want to show up in Google or Bing Search are not discoverable and do not show up in the search results.

Controlling the visibility of your content is SEO 101, and sadly, we see this issue come up over and over again with sensitive information being open and available on the web.

Read more at Read More

How SEO reduces blended customer acquisition costs

July 28, 2026/0 Comments/in Search Engine Land, Web Design News/by Dubado Solutions

For every dollar you spend on SEO, how much do you get in return?

Impressions, clicks, rankings, and query growth can show the results of SEO activity. But they don’t tell executives what they need to understand: how much it costs to acquire a customer (CAC), how that cost changes as SEO efforts continue, and whether overall acquisition efficiency is improving.

The challenge is that SEO rarely operates within the clean boundaries that a channel-level CAC calculation implies.

SEO creates entry points across the customer journey and influences other acquisition channels along the way. Its value, then, isn’t only in the customers directly attributed to organic search. It’s also in how SEO can make the broader acquisition system more efficient.

The reality of acquiring a customer

A user may first find a company through a nonbrand search, return through paid search, compare alternatives through content found in ChatGPT, sign up for a newsletter on the website, read through guides for a week, and then finally convert through the owned channel.

The final conversion might be attributed to email. Paid search may receive some credit for the return visit. The original organic discovery may disappear from the standard report entirely.

But SEO still influenced the acquisition and may have reduced its total cost.

CAC can be measured by individual channel or across channels as blended CAC. CAC expectations vary considerably by channel:

Paid search.
Paid social.
Email.
SEO.

Be the brand customers find first.

Track, grow, and measure your visibility across Google, AI search, social, local, and every channel that influences buying decisions.

Start your free trial

Paid search captures high-intent demand

Paid search may have the cleanest attribution. Users search for solutions to their problems, product terms, categories, or other related queries. You pay for the click, and a percentage of those clicks convert.

From there, you get spend / customers acquired = paid search CAC.

It’s also usually close to the transaction, which makes it easier to credit regardless of other factors, such as whether paid social may have warmed the audience first.

A user who clicks a search ad may already know the brand through social campaigns, podcast appearances, how-to guides, recommendations, or competitor research. The demand is high-intent, and paid search captures its final expression.

Paid social influences demand earlier

Paid social’s impact on CAC is often indirect because its primary strengths are creating awareness, warming audiences, building retargeting or feeder pools, and connecting users with problems they may want to solve before they’re ready to buy.

It’s unlikely that your users are scrolling on Instagram thinking, “I would like to spend some money right now.”

But seeing a product address their problem during their free time may make the brand more familiar when they later search for a solution at work, improving blended CAC efficiency.

If you looked only at paid social as spend / customers acquired = paid social CAC, you’d probably cut the budget. But then, if you look at what it does to paid or branded search CAC through holdout tests, you’d potentially restart the social budget after seeing the overall acquisition engine decline.

It’s a form of incrementality. Experiments compare exposed and unexposed groups to estimate how much additional activity a marketing investment produces instead of simply assigning credit to the last recorded touchpoint.

Email depends on other acquisition channels

Lifecycle channels like email work differently. If you own an audience through email capture and you look at converting them into paid users or continuous purchasers, you can think of email CAC along the lines of cost of email program / converted customer value.

But then you still have to run paid to capture the emails in the first place, or you need a strong SEO presence to do so. The apparent efficiency is highly dependent on other channels.

SEO touches all of these channels, and all of these channels can influence SEO in return. For example, a paid social campaign could generate 100 brand mentions that benefit your overall organic visibility.

Together, they create a connected acquisition system.

Dig deeper: SEO and PPC alignment starts with your org chart

Attribution models don’t fix the problem

It sounds like the solution is a better attribution model, and then SEOs can speak about CAC more effectively and get more budget. But there are still limitations.

Last-click attribution would just give credit to the final measurable source. First-click would just give credit to the initial source. Linear or position-based models distribute credit, and data-driven attribution would observe data to estimate what contributed most.

Data-driven attribution may improve reporting, but it remains a model rather than a complete record of the customer journey.

Because how do you evaluate interactions that aren’t observed, identified, or connected to a user’s journey? There are deleted cookies, consent restrictions, cross-device behavior, long sales cycles depending on your niche, offline conversions, and that list of limitations could go on for a while.

So, regardless of your attribution model, it doesn’t always provide a complete record of causality and shouldn’t be treated as such. This further reinforces that acquisition is a system, not an isolated channel.

As the search ecosystem changes, even more of SEO’s influence is becoming difficult to observe.

Dig deeper: Why first-touch analytics matters more than ever for SEO

Get the newsletter search marketers rely on.

See terms.

SEO’s influence is becoming harder to observe

Measuring CAC for SEO as an isolated channel is becoming increasingly difficult.

SparkToro’s analysis of Similarweb clickstream data found that 68.01% of U.S. Google searches ended without a click during the first four months of 2026. In 2024, the figure was 60.45%, representing an increase of roughly 7.6 percentage points in two years.

Users can still see a company in an AI Overview, read a search snippet, or engage in other behaviors, but fewer and fewer are measured through impression → click → conversion.

SEO still influences these interactions, but its impact may appear smaller in a dashboard.

There’s also significant overlap between SEO efforts and AI visibility, depending on which agency or existential hill you’re standing on.

SEO leans out blended CAC

SEO’s biggest advantage is that its financial returns can compound. A paid campaign stops sending traffic to the website when the budget stops, but a strong organic presence can continue creating entry points long after the initial investment.

If you build topical authority across a category with meaningful demand, the cost to maintain that visibility, including the costs of keeping up with competitors, is often lower than continuously buying the same demand through paid search.

That could include technical improvements, content production, digital PR, product pages, and ongoing optimization.

During the first few months, the program may appear inefficient from a CAC perspective because the investment occurs before returns materialize. Then, as visibility grows, that same work starts to increase customer volume while spend stabilizes at maintenance levels, and CAC decreases.

That’s one way SEO leans out blended CAC. It does this by:

Creating nonpaid entry points into the funnel.
Capturing demand that paid would otherwise have to buy.
Supporting paid search and paid social conversion.
Increasing branded and direct demand over time.
Educating buyers before sales conversations.
Improving conversion through comparison, use-case, and objection-handling content.
Feeding owned channels like email.
Reducing support and retention friction through product and help content.

When considering the impact, it can be true that SEO is among the more efficient levers for reducing a business’s blended CAC.

Dig deeper: 3 ways to build a more complete SEO ROI model

Own the conversation before your competitors.

See where your brand appears, where it doesn’t, and exactly how to win more visibility across search, AI, local, social, and every channel that matters.

Start your free trial

Reframe the SEO investment conversation

The attribution model can point to various channels as the highest-performing, but the organic infrastructure may be contributing to that performance.

That’s where SEOs should point when reframing the conversation.

Instead of answering how much you get in return for every dollar spent on SEO, consider how much more money you’ll have to spend on other channels for every dollar not spent on SEO.

If SEO is doing its job, it’s part of a cohesive system, and its role is to increase volume while reducing blended costs.

SEO teams should still report channel CAC when the data allows, but executives should evaluate it alongside influenced pipeline, replacement costs, and changes in blended acquisition efficiency.

Read more at Read More

Why creator content belongs in your AI search strategy

July 28, 2026/0 Comments/in Search Engine Land, Web Design News/by Dubado Solutions

Creator content increasingly informs AI answers.

After all, a large language model (LLM) can’t have an opinion. It can’t decide whether your product is the best moisturizer or the water softener that’s the best value.

So when someone asks a subjective question, an LLM borrows a point of view from wherever humans have already shared one. Reviews, community threads, editorial content, retailer pages, and creator content guide these answers.

Various teams own all of those sources. This makes showing up in AI answers less of a content creation issue and more of a coordination problem.

AI needs opinions to build out answers

In Tinuiti’s Q1 2026 AI Citation Trends Report (Disclosure: I’m the senior director of AI SEO innovation at Tinuiti), we found that roughly 82% of AI citations pointed to earned media, not a brand’s own site.

Creators are a fast-rising component of that mix. If you take a look at YouTube’s search engine results page (SERP) presence, inclusion in Google AI Overviews grew from 3.6 million to 36.2 million keywords year over year. That’s likely partially due to the increase in AI Overviews.

Yet YouTube visibility across the entire SERP has been evolving for a long time. Video has now become a format AI uses when it needs to explain or validate something.

Dig deeper: AI search engines cite Reddit, YouTube and LinkedIn most: Study

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

Social’s citation share swings hard by category

It’s tempting to invest in creators across industries, but the data doesn’t necessarily support that approach. In our Q2 2026 AI Citation Trends Report, social platforms drove about 13% of AI citations on apparel prompts — but only 3% on over-the-counter health.

Social citation trends move quickly. For example, Perplexity’s share of citations from social media fell from 31% to 13% in a single quarter as it pulled back from Reddit.

The social platforms that matter in each category continue to evolve, too. This requires deeper research into where LLMs source conversations. That’s exactly why a single team watching one social channel can’t see the whole picture.

Dig deeper: Why AI visibility starts before search and ends with citations

Traditional search has been signaling to social for a while

It would be easy to file all of this under AI search. But I’d argue it’s a pattern Google has been building toward as consumer behavior has moved to social.

In 2025, the search engine began automatically adding social media links to Google Business Profiles at scale. This update began surfacing brands’ recent posts right on their profiles.

Google has also started to display a short videos block on SERPs and within the search bar. This block includes vertical clips under five minutes, pulled from sources like Facebook, YouTube, and TikTok.

Based on Semrush organic research data for the past year (U.S.), YouTube’s estimated organic traffic roughly doubled. It’s now Google’s single largest organic domain. Meanwhile, organic traffic climbed by about 60% for both Facebook and Instagram.

Google keeps building surfaces to ingest, display, and now measure social conversations. If we use trends to help inform predictions, I think it’s safe to say there’s high value in social conversations and content, in the spirit of search everywhere optimization strategies.

Get the newsletter search marketers rely on.

See terms.

The creators winning citations aren’t who you’d expect

The content that wins YouTube citations isn’t the obvious kind. Long-form video accounts for 94% of AI citation, with 40.83% of cited videos having fewer than 1,000 views, OtterlyAI’s YouTube Citation Study 2026 found.

This indicates that popularity doesn’t predict citation value. Instead, structure does.

Mid-size niche creators tend to make well-structured content. These videos typically have clear titles, clean formatting, and a specific focus.

Comparison videos.
Honest reviews of a category.
How-to-style videos.
Skincare routines.
Tutorials for SaaS.

The sentiment that these videos express also affects AI search. In one client program, when mid-size creators published genuine review content, their language began appearing in citations for branded prompts and in our sentiment theme occurrence rates. A YouTube review and a blog each reached roughly 0.23% citation share on a target term, and it’s kept climbing.

AI search leans on creator content because it’s authentic and not branded. As a result, flooding search with citation bait breaks the very thing that makes it useful. The teams doing this well scale creator content when there’s a real idea or a brand story worth reinforcing.

Dig deeper: How AI-driven shopping discovery changes product page optimization

The real unlock is one shared objective

Most organizations run influencer and SEO on separate budgets, chasing distinct goals with reach and engagement over here and rankings over there. Instead, they should point teams at the same target and encourage them to exchange insights.

The influencer team gets to see its real role in search, while the SEO team brings citation data and measurement. Micro-influencers and repeated sentiment themes can matter as much as any single high-reach post. Shared reporting can show which creator content is influencing search and help both teams make better decisions.

Our tooling is catching up. In July, Google introduced platform properties in Search Console. This feature lets you track how your Instagram, TikTok, X, and YouTube content performs in Google Search, including the queries that send people to your posts. These insights can make creator choices evidence-based instead of instinctive.

Dig deeper: Why 2026 is the year the SEO silo breaks and cross-channel execution starts

Align your narrative across the content about your brand

Creator content is only one part of what AI engines encounter when forming a picture of your brand. They also draw from content, PR, commerce, social, affiliate, video, and paid.

When those sources reinforce the same narrative, AI models get a clearer picture. Creators are a smart place to start because they’re a growing source of opinions and experiences AI engines draw from.

The opportunity goes beyond any one channel. It’s about giving AI engines a consistent story about your brand wherever they look.

Read more at Read More

Google Officially Ends FAQ Rich Results: Should You Remove FAQ Schema?

July 27, 2026/0 Comments/in Web Design/by Dubado Solutions

Key Takeaways

Google has officially ended support for FAQ rich results, completing a phased rollout that began in 2023.
Most websites have not been eligible for FAQ rich results for nearly three years, so the practical impact on search visibility is minimal.
The announcement does not mean FAQ schema has lost its value.
Structured FAQ markup can still help AI-powered search engines better understand your content.
Website owners should keep existing FAQ schema and continue using it where a question-and-answer format naturally fits.

Google has officially ended support for Google FAQ rich results, bringing a long-running transition to a close.

For many marketers, the announcement may sound like a significant change. In reality, most websites stopped receiving FAQ rich results back in 2023 when Google limited the feature to government and health websites. The latest update simply formalizes what many SEO professionals have already observed in search results.

Some website owners may see the news as a reason to remove FAQ markup altogether. That would likely be a mistake. While FAQ rich results have disappeared from Google’s search results, structured FAQ data can still help search engines and AI platforms understand your content.

Here’s what changed, why it matters, and how you should approach FAQ schema moving forward.

What Changed With FAQ Rich Results?

FAQ Rich Results Have Been Phased Out Since 2023

In September 2023, Google dramatically reduced the visibility of FAQ rich results, limiting them primarily to well-known government and health websites. For businesses, publishers, and most other organizations, the expandable FAQ dropdowns largely disappeared from search.

Since then, many SEO professionals have continued implementing FAQ schema despite the lack of visible rich results. Google’s latest documentation update confirms that the phased rollout is complete.

Google documentation about FAQ schema removal.

Source

The Announcement Is a Documentation Update, Not a Ranking Change

The latest announcement is primarily a documentation update rather than a new ranking signal.

Google isn’t introducing a new algorithm update or changing how websites are indexed. Instead, the company has updated its Search Central documentation to reflect the current state of FAQ rich results.

For most websites, there shouldn’t be any noticeable change in traffic or search appearance because those rich results have already been absent for years.

Why You Shouldn’t Remove FAQ Schema

The announcement may lead some site owners to question whether FAQ schema is still worth keeping.

That’s understandable. If Google no longer displays Google FAQ rich results, removing the markup might seem like a logical cleanup task.

The reality is more nuanced.

FAQ Schema Still Helps AI Understand Your Content

Structured data has always served a broader purpose than generating rich results.

FAQ schema clearly identifies questions and answers, making it easier for machines to understand how information is organized on a page. As AI-powered search experiences become more common, that structured format may continue helping systems interpret and reference content more accurately.

While Google hasn’t confirmed that FAQ schema directly influences AI citations, structured content aligns with how large language models process information.

How FAQ schema translates to a rich snippet.

Source

Removing It Offers Little Benefit

There’s also very little to gain from deleting existing FAQ schema.

Removing the markup won’t improve rankings, restore lost rich results, or provide meaningful performance gains for most websites. At the same time, it removes structured information that could continue supporting future search experiences.

If your FAQ markup accurately reflects the content on the page and follows Google’s structured data guidelines, leaving it in place is the more practical approach.

FAQ schema hasn’t disappeared so much as taken on a new job. The bigger risk isn’t losing rich results but reactively stripping out markup that could still earn a spot in AI-generated answers.

As AI-powered search continues to evolve, structured data may play an increasingly important role in helping search engines and AI platforms interpret content. Keeping well-implemented FAQ schema in place helps preserve that context while requiring little ongoing maintenance.

What These Changes Mean for Your SEO Strategy

Google’s announcement doesn’t require a new SEO playbook. Instead, it reinforces the importance of focusing on content quality and structured information rather than chasing individual search features.

Keep Existing FAQ Schema in Place

If your pages already use FAQ schema appropriately, there’s little reason to remove it simply because rich results are no longer displayed.

Structured data still helps define your content in a consistent, machine-readable format. Keeping that markup in place allows your pages to remain well organized for both traditional search engines and emerging AI experiences.

Source

Use FAQ Schema Where It Makes Sense

FAQ schema should continue supporting content that naturally answers common questions.

Avoid adding FAQ sections solely to implement structured data. Instead, use the markup when it improves the page for readers and reflects the actual information being presented.

This approach aligns with Google’s long-standing guidance while creating content that’s easier for both users and AI systems to understand.

Structured Data Still Has a Role in AI Search

Search continues to evolve beyond traditional blue links, and structured data remains one way to help search engines interpret content.

Google’s decision to retire FAQ rich results doesn’t change that.

As AI-powered search experiences become more common, providing clear, well-organized information is likely to remain valuable. Schema markup is one tool that helps accomplish that, even if the visible search features associated with it have changed.

For marketers, the takeaway is simple. Continue using structured data where it genuinely improves your content and resist the temptation to remove useful markup based on assumptions about future search behavior.

FAQs

Why did Google remove FAQ rich results?

Google began limiting FAQ rich results in 2023 to reduce clutter in search results. The latest announcement officially ends support for the feature for most websites.

Should I remove FAQ schema from my website?

No. If your FAQ schema accurately reflects your content, keeping it in place remains a sensible approach. Removing it offers little benefit and could reduce the structured information available to search engines and AI platforms.

Does FAQ schema still help SEO?

FAQ schema no longer generates rich results for most websites, but it can still help search engines better understand your content. It also supports a structured format that may benefit AI-powered search experiences.

Is FAQ schema useful for AI search?

While Google hasn’t confirmed a direct connection, structured data helps organize content in a way that’s easier for machines to interpret. That makes it a worthwhile component of a broader content strategy.

Conclusion

Google’s official retirement of Google FAQ rich results doesn’t represent a major shift for most websites. The visible SERP feature largely disappeared in 2023, making this announcement more of a confirmation than a surprise.

The more important takeaway is avoiding unnecessary changes. Removing FAQ schema won’t restore rankings or improve performance, and it may reduce the structured information available to search engines and AI platforms.

As search continues evolving, creating helpful content with clear, well-implemented structured data remains a sound long-term strategy. Focus on providing answers that genuinely help your audience, and use FAQ schema when it supports that goal naturally.

If you want to stay ahead of Google’s latest search developments, explore our resources on AI SEO and content strategy, or reach out to the NP Digital team to learn how emerging search experiences can fit into your long-term marketing strategy.

Read more at Read More

How long does it really take to build a website with AI?

July 27, 2026/0 Comments/in Web Design News, Yoast SEO/by Dubado Solutions

Most AI website builders promise you can create a website in minutes, but what does that timeline actually include? While AI can generate a professional-looking website surprisingly quickly, you’ll still need time to choose a domain, review the generated content, make a few edits, and publish your site. In this guide, we’ll break down the entire journey and share a realistic estimate.

Key takeaways

AI website builders significantly reduce the time for initial website setup, but require additional time for edits and refinements
Creating a basic website typically takes 30 to 90 minutes, depending on preparation, while AI can generate a first draft in about 3 minutes
Key stages of website creation include defining purpose, selecting a domain, and adding content, each taking varying amounts of time
Post-launch, focus on content updates, SEO improvements, and monitoring performance to maintain a strong online presence
AI tools streamline the initial setup, but successful websites still require ongoing personalization and development to truly reflect the brand

A realistic timeline: How long each stage of website creation takes

Every website follows a similar journey before it goes live. Whether you’re creating a portfolio, a business website, or an online store, you’ll need to plan your website, register a domain, set up hosting, create pages, add content, and test everything before publishing.

The time required for each stage depends on your website’s complexity, the resources you already have, and how prepared you are before you begin. The table below provides a realistic estimate of how long each stage typically takes.

Stage	What it involves	Typical time
Define your website’s purpose	Decide what your website should achieve, identify your target audience, and outline the pages and features you’ll need. The clearer your goals are, the easier the rest of the process becomes.	30 minutes–1 day
Research your market (Recommended)	Review similar websites to understand industry trends, gather inspiration, and identify opportunities to differentiate your website.	1-3 days
Choose a domain name	Brainstorm a memorable domain name, check its availability, and register the one that best represents your brand.	30 minutes–1 day
Set up web hosting	Choose a hosting provider, create your hosting account, and configure the essentials needed to make your website accessible online. Tip: Bluehost Web Hosting includes reliable hosting, a free SSL certificate, domain management, and website management tools in one place, helping you get online without juggling multiple services.	30 minutes–1 day
Create your website	Build your website’s structure by creating pages, organizing navigation, choosing layouts, and adding the functionality your visitors will use.	1-7 days
Add your content	Write and review your page copy, upload images and videos, add contact information, and make sure every page accurately represents your brand.	1-7 days
Review and test your website	Test your website on different devices, verify links and forms, check loading speed, review mobile responsiveness, and fix any issues before launch.	2-8 hours
Publish your website	Connect your domain, perform final checks, and make your website publicly available for visitors.	30 minutes–2 hours

Additional factors that may extend your timeline

The timeline above reflects the steps involved in building a typical website. However, certain features and functionality can add additional time depending on your requirements. For instance, if you’re building an eCommerce website or a multilingual website, the following will be added to your timeline:

Requirement	Additional time
Setting up an online store	1-5 days
Adding products and categories	Several hours to multiple days
Configuring product variants (size, color, etc.)	A couple of hours to 2 days
Setting up payment gateways	1-2 days
Configuring shipping and tax settings	1-3 days
Configuring shipping and tax settings	2-8 hours
Connecting third-party tools (CRM, email marketing, analytics, booking systems, etc.)	A couple of hours to 2 days
Creating multilingual pages	Several days to weeks

Keep in mind that the estimates above focus solely on the website creation process. Some projects may require additional planning before you even begin building. For example, businesses entering a competitive market often spend extra time researching competitors, refining their brand positioning, defining their target audience, or planning their content strategy. While these activities can extend your overall timeline, they often result in a more focused website that better serves your visitors and supports your business goals.

How AI website builders have changed the website creation timeline

Traditionally, creating a website involves much more than writing content. Before you can even start customizing your site, you have to make a series of decisions that shape its overall structure and design.

The manual work AI helps you skip

Building a website from scratch typically involves tasks such as:

rowsing and selecting a template
Choosing colors and typography
Deciding which pages to include
Creating a navigation menu
Arranging sections on each page
Drafting placeholder content for your homepage and key pages

None of these tasks is particularly difficult on its own, but together they can easily add hours to the website creation process.

AI website builders shorten this setup phase by turning it into a guided onboarding experience. Instead of making every decision manually, you answer a few questions about your business, and the AI generates a website structure, page layouts, navigation, design elements, and draft content for you.

Rather than starting with a blank canvas, you start with a complete first draft that’s ready for review.

Putting AI website creation into practice

To see how this works in practice, I used the Bluehost AI Website Builder while building a website with AI from scratch.

The process was straightforward:

Describe the website in a single sentence
Create an account and verify your email address
Answer a few questions about your business, website goals, preferred design style, and overall tone
Let the AI generate the website

Once onboarding was complete, the AI produced a complete first draft in about 3 minutes. The generated website already includes:

A homepage
A navigation menu
Pre-designed page sections
AI-generated copy
Placeholder images based on the information provided

It’s still WordPress underneath

One feature that stood out was that the generated website wasn’t locked inside a simplified editor. Because Bluehost’s AI Website Builder is built on WordPress, I could immediately access the complete WordPress dashboard to:

Edit pages
Preview posts
Install plugins
Customize themes
Manage site settings

In other words, the AI accelerated the initial website setup without limiting what I could do afterward.

Where you’ll probably spend the most time

Although AI significantly reduces the time required to create the first version of a website, there are still several areas where you’ll likely invest additional time.

Refining your content

AI-generated copy provides a strong starting point, but it should reflect your products, services, brand personality, and unique value proposition. Reviewing and personalizing the content is one of the most important steps before publishing.

Choosing the right images

The first draft may include placeholders or stock images. Replacing these with your own photography, product images, or branded visuals helps create a more authentic and trustworthy website.

Expanding your website

Depending on your business, you may want to create additional pages beyond the initial draft, such as an About page, service pages, FAQs, testimonials, pricing information, or a blog. AI accelerates the initial launch, but your website can continue to grow over time.

Optimizing for search engines

Publishing your website doesn’t mean your work is finished. Optimizing page titles, meta descriptions, internal links, headings, and on-page content, as well as creating valuable blog posts, is what helps people discover your website through search engines over the long term.

While AI can dramatically reduce the time it takes to create a website, the biggest improvements usually come after the first draft. Personalizing your content, using original visuals, expanding your website with valuable pages, and continuously improving your SEO are what transform an AI-generated starting point into a website that genuinely represents your brand and stands out from the competition.

Final verdict: So, how long does it really take to build a website with AI?

If you’re wondering whether AI website builders really save time, the answer is yes, but perhaps not in the way most marketing claims suggest.

The website generation itself is remarkably quick. In my experience, the Bluehost AI Website Builder produced a complete first draft in around three minutes after the onboarding process. However, creating an account, verifying your email, answering the AI’s questions, reviewing the generated website, and making your own edits naturally add to the overall timeline.

For most people starting from scratch, it’s reasonable to expect a basic website to be online within 30 to 90 minutes, depending on how prepared you are. If you already have your domain, branding, and content ready, you could realistically publish in under 15 minutes. On the other hand, if you’re building a more polished website with custom copy, additional pages, and SEO improvements, you should expect to spend a few hours or even a full day refining it.

The biggest impact of AI isn’t that it builds a perfect website in minutes. It’s that it compresses what used to be the most time-consuming part of website creation, setting up the structure, layouts, navigation, and first draft into a guided process that takes only a few minutes. Instead of spending hours building a website from an empty canvas, you can dedicate your time to improving the content, design, and user experience, which are ultimately the elements that make a website successful.

So, are AI-generated websites any good?

For most individuals and small businesses, yes, they’re a strong starting point. AI website builders can generate a professional-looking first draft in minutes, but you’ll still get the best results by personalizing the content, visuals, and SEO to reflect your brand and goals.

AI builds websites quickly, but growing one still takes time

Once your website is live, keeping it useful, discoverable, and up to date still requires ongoing effort. AI website builders can help you create and publish a website much faster than traditional methods, but launching your website is only the beginning.

Here are a few areas to focus on after launch.

Publish helpful content regularly

Whether you’re running a business website or an online store, regularly publishing helpful content keeps your website fresh and gives people more reasons to visit. If you’re not sure where to start, check out our guide on writing an SEO-friendly blog post.

Keep your website up to date

Your website should evolve alongside your business. As your products, services, pricing, or contact information change, make sure your website reflects those updates. You can also expand your website over time by adding new landing pages, service pages, FAQs, or case studies as your business grows.

If you are using Yoast SEO, creating FAQ pages becomes very easy. The plugin’s FAQ content block converts your questions into structured data, making them easier for search engines and AI crawlers to digest.

A smarter analysis in Yoast SEO Premium

Yoast SEO Premium has a smart content analysis that helps you take your content to the next level!

Get Yoast SEO Premium Only $118.80 / year (ex VAT)

Continue improving your SEO

Publishing your website is only the first step. To help people find your website, you’ll need to continue optimizing both your content and your website’s technical foundation.

That includes creating helpful content around the topics your audience is searching for, improving internal linking, and regularly reviewing your pages to keep them accurate and relevant. It’s also worth checking that search engines can easily crawl and index your website, that your XML sitemap is up to date, that your pages load quickly, and that there are no broken links or indexing issues affecting your visibility.

If you’re using WordPress, our definitive guide to WordPress SEO covers both on-page and technical SEO best practices to help you build a strong foundation for long-term growth.

Monitor your website’s performance

Understanding how people discover and interact with your website helps you make better decisions.

Start by connecting your website to Google Search Console to monitor search performance, identify indexing issues, and see which queries drive traffic to your site. Pair it with Google Analytics to better understand user behavior and measure the impact of your SEO efforts over time.

Helpful resources:

Build your AI presence

As AI-powered search experiences continue to evolve, it’s becoming increasingly important to understand how your brand is represented beyond traditional search results.

If you’re using Yoast SEO AI+, Yoast AI Brand Insights helps you understand how AI platforms perceive your brand and identify opportunities to strengthen your online presence as AI search continues to grow.

How much faster is building a website with AI?

AI website builders don’t eliminate every step of website creation, but they dramatically shorten the time it takes to go from an idea to a working website. Instead of spending hours manually setting up the foundation, you start with a complete first draft that you can immediately personalize.

Here’s how the experience typically compares.

Traditional website creation	Building a website with AI
Days or weeks to create the initial website	A working first draft in minutes
Browse and compare templates manually	AI recommends a design based on your requirements
Build page layouts section by section	AI generates complete page layouts
Create navigation menus manually	Navigation is generated automatically
Write placeholder copy from scratch	AI creates an initial content draft
Start with a blank page	Start with a complete website structure
Spend time assembling the website	Spend time refining and personalizing it

The biggest difference isn’t that AI removes the need to edit your website; it changes where your time is spent. Rather than investing hours creating the foundation, you can focus on improving the parts that have the greatest impact on your visitors, such as your messaging, branding, content, and SEO.

AI gives you a head start, not the finish line

Creating a website no longer has to be a weeks-long project. AI website builders have transformed what was once the most time-consuming part of the process, setting up layouts, pages, navigation, and initial content, into something that can be completed in minutes.

That doesn’t mean AI builds a perfect website on its own. A successful website still depends on thoughtful content, strong branding, regular updates, and ongoing SEO. What AI does provide is a significant head start, allowing you to skip the blank page and spend your time refining a website instead of building one from scratch.

If you’ve been putting off creating a website because it felt too technical or time-consuming, AI has made getting started easier than ever. The sooner you launch, the sooner you can begin growing your online presence.

The post How long does it really take to build a website with AI? appeared first on Yoast.

Read more at Read More

Archive for month: July, 2026

Two Ways to Start a Search

The Business Summary: The Brain Behind Everything

The Left Sidebar: Your Four Main Surfaces

Suggested For You: Where Most Users Should Spend Most of Their Time

Clicking Any Keyword Opens the Full Research View

One-Click Content Generation from Anywhere

Full Control Inside the Article Editor

The Right-Panel Tabs

Exporting, Saving, and Publishing

Settings: Set It and Forget It

The Fastest Path to Your First Published Article

The Bigger Picture

Frequently Asked Questions

What’s different about the new AnswerThePublic vs the original?

Does AnswerThePublic write the full article, or just an outline?

Can I use AnswerThePublic if I don’t have a WordPress site?

Does it work in languages other than English?

Key Takeaways

What Changed With TikTok Keyword Metadata?

Creators Can Now Manage Metadata Keywords

TikTok Will Continue Reviewing Keyword Changes

Why This Update Matters

Search Is Becoming a Bigger Part of the TikTok Experience

Better Metadata Improves Content Relevance

What This Means for Your Social SEO Strategy

Treat TikTok Search as Part of Your SEO Strategy

Monitor Performance Beyond Views

Social Search and SEO Are Becoming More Connected

FAQs

What is TikTok keyword metadata?

Can creators edit TikTok metadata?

Why is TikTok focusing on search?

How does TikTok keyword metadata affect visibility?

Conclusion

A refresher on attribution

Incrementality 101

Using attribution and incrementality together

Where platforms get confused by attribution and incrementality

A note on in-platform lift studies

Know which question you’re trying to answer

Text customization and messaging restrictions

Choosing the campaigns to test

Asset review

The results

Ecommerce campaigns

B2B lead generation

B2C lead generation

Where AI Max automated assets work best

The reality of acquiring a customer

Paid search captures high-intent demand

Paid social influences demand earlier

Email depends on other acquisition channels

Attribution models don’t fix the problem

SEO’s influence is becoming harder to observe

SEO leans out blended CAC

Reframe the SEO investment conversation

AI needs opinions to build out answers

Social’s citation share swings hard by category

Traditional search has been signaling to social for a while

The creators winning citations aren’t who you’d expect

The real unlock is one shared objective

Align your narrative across the content about your brand

Key Takeaways

What Changed With FAQ Rich Results?

FAQ Rich Results Have Been Phased Out Since 2023

The Announcement Is a Documentation Update, Not a Ranking Change

Why You Shouldn’t Remove FAQ Schema

FAQ Schema Still Helps AI Understand Your Content

Removing It Offers Little Benefit

What These Changes Mean for Your SEO Strategy

Keep Existing FAQ Schema in Place

Use FAQ Schema Where It Makes Sense

Structured Data Still Has a Role in AI Search

FAQs

Why did Google remove FAQ rich results?

Should I remove FAQ schema from my website?

Does FAQ schema still help SEO?

Is FAQ schema useful for AI search?

Conclusion