Get ready, Japan! We’re thrilled to announce the return of Search Central Live Tokyo on Nov 7,
2025! If you are fluent in Japanese and are interested, read on! We’re bringing
back all the elements you loved, with even more opportunities for you to shape the experience.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2021/12/web-design-creative-services.jpg?fit=1500%2C600&ssl=16001500http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-12 06:00:002025-09-12 06:00:00Search Central Live Tokyo: The 2025 Return
I analyzed over one million keywords across 10 industries.
The average cost per click (CPC) for Google Search ads in 2025 is $8.34. And the median CPC is $4.52.
Legal had the highest average CPC at $22.75.
Ecommerce had the lowest, at just $0.82 per click.
But there’s no flat rate for CPC.
Even if two advertisers bid on the same keyword, they won’t pay the same.
Costs can vary based on several factors — and CPC is just one part of the equation.
Google Ads pricing also involves other expenses that can affect your total budget.
In this guide, you’ll learn:
How much Google Ads really cost
What your budget should be
How you can lower your ad costs (without hurting results)
Let’s dive in.
How Much Does a Google Ad Cost?
Google Ads can cost anywhere from $500 to $100,000 per month.
There’s no fixed rate. And CPCs can change from year to year based on competition and demand in your industry.
That’s why you set the budget that makes sense for your goals.
When I worked at marketing agencies, I’d see brands start with as little as $200 per month.
But in most cases, that isn’t enough to generate real data to measure performance, optimize targeting, or drive consistent leads.
It’s recommended to start with at least $500 a month.
I asked Sam Maugans (a PPC Director and Business Owner, FourHorse Digital LLC) how much does it cost for Google Ads. He said:
“Smaller companies can run remarketing campaigns for as little as $500 per month. Medium-sized businesses usually start out at around $5,000 and, with good performance, can increase their monthly budgets all the way up to $50,000. Similarly, larger businesses may start at $5,000 and over the years work their way up to $100,000 and even $1,000,000 a month.”
I talked to other experts as well.
Here’s what a typical monthly budget looks like, based on business size:
Small business: From $500 to $5,000 per month
Mid-size business: From $5,000 to $50,000 per month
Large business: From $25,000 to $100,000+ per month
In the end, what you spend depends on how aggressive your goals are.
If you want more clicks and leads, you’ll need a larger budget to reach enough of the right people.
You can’t expect to generate 100 high-quality SaaS leads with just $500 a month. That kind of reach takes more spending.
And remember, not all clicks are equal.
A higher CPC can still be worth it if it brings in better-quality leads that are more likely to convert.
Use our Google Ads Budget Estimator to calculate your starting budget. Just plug in your CPC, lead goals, and conversion rate.
What You’re Paying for With Google Ads (and Why It’s Not Fixed)
Google doesn’t charge you to show your ad.
You only pay when someone clicks. That’s why it’s called pay-per-click (PPC).
This model mainly applies to Search ads, where you bid on keywords.
But other ad formats (like Display, YouTube, and Shopping) use different pricing.
Some charge you per view. Others per 1,000 impressions.
(We’ll cover this when we break down campaign types later in the guide.)
Still, all of them run on one thing: Google’s ad auction.
Every time someone searches, there’s a lightning-fast auction to decide whose ad shows and what they pay for that click.
For example:
Let’s say someone searches “divorce lawyer near me.” And they click on a Google search ad.
That single click could cost around $8.43 in the U.S.
But if they search for something like “dog groomer near me,” that click might only cost $1.35.
Same platform. Same system. Very different costs. Because the value of each click is different.
But here’s the thing:
You don’t always pay the amount you bid.
When you run a campaign, you set a maximum bid, which is the most you’re willing to pay for a click.
But what you pay is usually less.
That’s because Google’s auction considers more than just your bid when deciding which ad shows up and at what price.
So, what affects the cost of Google Ads beyond your max bid?
Let’s break down the seven biggest factors.
Factors That Impact Your Cost Per Click
How much Google Ads costs isn’t set in stone.
Your CPC can change dramatically depending on these seven factors:
Your Industry
Your cost per click depends heavily on the industry you’re in.
When I analyzed over one million keywords across 10 industries, the differences were huge.
Some industries consistently came in high. Because the value of a single lead is massive.
Others stayed low, likely due to lower margins or less commercial intent.
Here’s a breakdown of the average and median CPC for each industry in the dataset:
Side note: In every industry, the median CPC is lower than the average. That means a few high-cost keywords pull the average up, but most keywords cost much less.
Industry
Average CPC
Median CPC
Legal
$22.75
$8.00
Finance
$11.25
$6.43
SaaS / Tech
$10.14
$6.68
Home Services
$8.86
$5.82
Marketing & Advertising
$8.33
$6.18
Education / Online Learning
$8.21
$4.87
Automotive
$5.90
$2.01
Health & Wellness
$5.50
$3.98
Real Estate
$1.65
$0.60
Ecommerce / Retail
$0.82
$0.63
To put that into perspective:
A click for “dog bite lawyer san jose” costs around $229.
A click for “keto diet nutritionist” costs about $0.85
That’s not just a pricing difference. It reflects the value of a lead in each industry.
If you’re in a high-cost niche like legal, finance, or SaaS, you’ll need a bigger budget to compete.
But if you’re in ecommerce or real estate, your clicks are cheaper. And you can start smaller.
Methodology
This data is based on a sample of over one million keywords pulled from Semrush’s U.S. database (July 2025.)
We analyzed keywords across 10 industries, using between 7 and 35 seed keywords per industry, and extracted up to 30,000 related terms for each. (Keywords with zero search volume were removed.)
The final mix of commercial, transactional, navigational, and informational search queries gave us a realistic snapshot of what businesses pay to advertise on Google Search ads.
The Types of Keywords You Target
Different types of keywords affect how much you pay.
They vary by:
Intent: Is the person ready to buy, or just looking for information?
Length: Broad terms vs. long, specific phrases
Match type: How closely a search needs to match your keyword
Broad, generic terms like “plumber” are comparatively affordable.
But, they’re less targeted. And often trigger your ad for searches that don’t match what you offer.
More specific terms like “emergency plumber in Chicago” tend to cost more.
But those clicks are from people who are ready to take action.
Where your ad runs — and on which device it appears — can affect your cost per click.
Targeting a competitive city usually means higher bids.
For example, the search term “plumber near me” costs $62.67 per click in Austin, Texas.
In Lincoln, Nebraska, that same keyword costs just $20.11.
Why?
Fewer advertisers. Less bidding. Lower CPC.
Similarly, device targeting affects cost as well.
Google Ads lets you set different bids for mobile, desktop, and tablet traffic.
Each device type can have its own CPC, depending on competition and performance.
For instance, if more advertisers are targeting mobile, clicks on mobile can cost more.
Or, if desktop traffic converts better in your industry, advertisers may bid higher there, which results in higher CPC.
Campaign Type (Search, Display, Shopping, YouTube)
So far, I’ve focused on Search ads, where you bid on keywords and pay when someone clicks.
That’s the most common format.
In fact, when most people say “Google Ads,” they’re usually talking about Search.
But Google Ads includes other campaign types too. And they’re priced differently.
With YouTube ads, your video can appear before, during, or after another video on YouTube.
You usually pay when someone watches a part of your ad. This is called cost-per-view (CPV).
Display ads are shown across Google’s Display Network, which includes websites and apps that run Google ads.
They’re often priced by impressions.
You’re charged per 1,000 views of your ad. Even if no one clicks.
Shopping ads show up in Google search results. But instead of text, they pull product images, prices, and titles from your product feed.
These ads are click-based, like Search. So, you pay every time someone clicks on it.
Each campaign type targets people differently. And Google Ads pricing varies depending on whether you’re running search, display, shopping, or YouTube ads.
That’s why your campaign type has a direct impact on how much you’ll pay.
Your Quality Score
Google doesn’t just look at your bid. It also scores the quality of your ad.
This is called Quality Score — a number from 1 to 10 that Google assigns to each keyword you target.
Each factor is graded as “Above average,” “Average,” or “Below average” compared to all other advertisers on Google Ads.
These ratings combine to form your overall Quality Score.
The higher your score, the less you pay for the same position.
The lower your score, the more you’ll need to bid to compete.
That means two advertisers can target the same keyword, but the one with the better ad and landing page might pay less per click.
This shows how much Google Ads costs is influenced by far more than your bid.
Your Bidding Strategy
Google Ads gives you two main ways to bid: manual or automated.
With manual bidding, you set the maximum amount you’re willing to pay for a click.
It works best when you already have historical data and know your ideal CPC. You’re in full control, but it takes more time to manage.
With automated bidding, you let Google set your bids based on your goals.
It tends to work better at scale, once Google has enough data to optimize toward those goals. That could be getting the most clicks, driving more conversions, or hitting a target cost per lead.
Here are the most common automated strategies and when to use them:
Maximize Clicks: Good for driving traffic quickly, especially in early testing
Maximize Conversions: Best when your goal is to get as many leads or sales as possible within budget
Target CPA: Works well when you know your ideal cost per lead or sale
Target ROAS: Best for ecommerce or campaigns where revenue tracking is set up, and you want to hit a specific return
If Google sees strong signals that a searcher is likely to convert, it may raise your bid automatically. Which can lead to higher CPCs.
Manual gives you more control. Automated gives you speed and scale.
The more control you want, the more work it takes. But giving up control may mean paying more.
Either way, your bidding strategy directly impacts what you pay. And how efficiently your budget gets spent.
How Your Account Is Set Up
Here’s a basic structure of a Google Ads account:
You create a campaign.
Inside that campaign are ad groups.
Each ad group includes a set of keywords, a specific ad, and a matching landing page.
Why does this matter? Because Google ranks your ad based on a combination of factors, including relevance.
And relevance depends on how tightly those elements match.
Let’s say you run one ad group for all your services: plumbing, HVAC, and electrical.
You use one ad and one landing page for all of it.
To Google, that looks messy. The ad isn’t specific. The landing page isn’t focused.
Someone searching for “emergency plumbing repair” sees a generic ad for “Plumbing, HVAC & Electrical Services.”
They land on a page trying to cover everything at once.
Relevance drops. So does your Quality Score. This results in a higher cost per click.
Now take the same budget and split those services into separate ad groups. Each with its own focused keywords, ad, and landing page.
Suddenly, your ads are more relevant. And Google rewards you with lower CPCs.
Other Costs Beyond Your CPC
Running Google Ads often comes with expenses outside of what you pay per click.
These can add up quickly:
Tools and software: Keyword research platforms, landing page builders, or call tracking tools can cost $50–$300+ per month, but they help improve campaign performance
Creative assets: Copywriting, landing page design, graphics, or video production. High-quality creative can boost CTR and conversions, but may require a few hundred to several thousand dollars.
Management fees: Whether you hire a freelancer, agency, or in-house specialist, expect to budget $100 to $10,000+ monthly, depending on scope
Many small businesses begin with $500 to $5,000 in their first month.
That’s usually enough to get real traffic, measure early performance, and understand what’s working.
Set a number you’re comfortable testing. Then, apply that as your monthly cap inside Google Ads.
For example, $900 = $30/day.
But be cautious not to spread your budget too thin, says Kalo Krastev, Team Lead Performance Marketing (SEA) at ImmoScout24
“Small-budget Google Ads accounts struggle the most, because lower investment means a slower learning curve. A small business owner should plan a short, cost-intensive testing phase to figure out what works, like search terms, settings, and targeting.”
Let’s say you spend $1,000 and get 250 clicks.
If your site converts 1 in 25 visitors, that’s 10 customers at $100 each.
If your average sale brings in $300, that’s a 3X return.
If your numbers look good, increase your monthly budget by 10-20%. (That’s enough to grow your reach without overspending too quickly.)
If performance is weak, don’t increase the budget. Instead, review your targeting, ad copy, and landing page to find what’s holding things back.
Once your campaign is converting reliably, scaling up becomes simple.
You’ll know what you’re paying to get a customer. And how much more can you spend to get more of them.
As you scale, be careful not to bleed cash.
Here are some signs that you’re overspending on Google Ads:
Cost per lead or customer is higher than your profit margin
You’re paying for clicks on irrelevant keywords
Campaigns run 24/7, but most conversions happen at certain times
CTR is dropping while spend stays the same or increases
If you spot these, analyze your campaigns and take steps to lower the cost. Start with the tactics in the next section.
Note: Download our Google Ads Budget Estimator to calculate the budget for your first Google search ad campaign.
6 Ways to Lower Your Google Ads Costs
Spending more doesn’t always get you better results.
In fact, most small businesses overpay for clicks without realizing it.
I saw this all the time with the agency clients — campaigns wasting money on keywords or placements that had no chance of converting.
The good news?
You can bring your costs down without turning off campaigns or cutting corners.
Here are six ways to do that:
1. Improve Quality Score
Google Ads uses Quality Score to assess the quality of an ad.
Improving this score can help lower your cost per click.
Relevance is a big part of the equation.
Your ad should match what the person is searching for — both in wording and intent.
For example, someone searching for “roof leak repair” is more likely to click on an ad that says “Roof Leak Repair: Book a Local Pro” than something generic like “Plumbing and Roofing Services.”
You can also make your ad more clickable by adding assets like site links, callouts, or structured snippets.
These help your ad stand out in search results and attract more qualified clicks.
Your landing page needs to deliver a good experience, too.
It should load fast, work well on mobile, and convey the same message.
If the page feels off-topic or slow, your score drops and your costs go up.
When your keyword, ad, and landing page all align, it may increase your Quality Score and lower your CPC.
2. Use Negative Keywords to Stop Paying for Useless Clicks
Not every click is a good click.
Your ad might show up for searches that sound relevant, but aren’t.
For example: You sell premium leather sofas, but your ad shows for “free leather sofa giveaway.”
Someone clicks, you pay…and they bounce.
Negative keywords help you block that.
They tell Google: “Don’t show my ad if this word is in the search.”
Before you launch, consider adding common negatives like:
“jobs” (people looking for employment)
“template” or “example” (informational searches)
“how to” (DIY intent)
“free” (no intent to buy)
Here’s how adding “free” as a phrase match negative keyword blocks irrelevant searches:
Take some time to identify more negative keywords that are irrelevant to your offering and may not lead to conversions.
After your ads run, check the “Search terms” tab inside Google Ads.
It shows a list of terms that triggered your ad.
If you see anything that doesn’t match your offer, looks irrelevant, and has low conversions, add it to your negative keyword list.
3. Focus on Long-Tail Keywords with Higher Intent
Long-tail keywords are longer, more specific search phrases — usually 3 to 5 words.
And unlike short, generic keywords, they make it clear what the searcher actually wants.
Think:
“roof leak repair near me” instead of just “roofing”
“tax accountant for freelancers” instead of “accountant”
These get fewer searches.
But they’re cheaper, have less competition, and usually convert better.
Why?
Because someone searching for a long-tail keyword is further along in their journey. They’re not just browsing. They’re ready to act.
So, instead of going after broad, high-cost terms, focus your budget on these high-intent searches.
Open the tool, enter your seed phrase (e.g., “roof repair”), choose your target location, and click “Search.”
You’ll see a long list of keyword ideas.
Next, we’ll narrow it down using filters.
Phrase Match: This keeps results closely related to your original phrase
KD %: Set “To” as 29 to filter for low-competition keywords
Advanced filters > Word Count: Set “From” as 3 to show only longer phrases
Intent: Choose “Commercial” and “Transactional” to focus on buyers
Exclude keywords: Remove irrelevant terms like “free” or “jobs”
Now you’re looking at a refined list of long-tail, high-intent keywords.
This is how you avoid broad, expensive clicks. And focus your budget on searchers who are ready to act.
4. Target Specific Locations to Lower Competition
One of the easiest ways to waste money on Google Ads?
Targeting a too-broad area.
If you’re a local business (or serve just a few regions), you don’t need your ads to show in places you don’t operate.
Running ads across a large area means more competition.
But narrowing your location targeting often leads to lower CPCs and better leads.
For example: Instead of targeting all of Texas, narrow it down to just the Dallas-Fort Worth area.
You’ll avoid competing with advertisers in Houston, Austin, and San Antonio — who are all bidding on the same keywords.
Same campaign. Same budget. Less competition.
Inside Google Ads, you can target by city, region, zip code, or even a radius around your address.
Start by focusing your budget where your best customers are.
You’ll cut waste and make your ad spend go further.
5. Run Ads When Your Customers Are Most Likely to Convert
Google’s Smart Bidding is smart, but it’s not magic.
If you’re running ads 24/7, it won’t automatically stop spending at 2 a.m. — even if those clicks rarely turn into customers.
That’s where ad scheduling comes in.
If you run a local business or only serve customers during specific hours, you don’t want to pay for clicks when no one’s around to respond.
For example:
If you’re a plumber or accountant and someone clicks your ad at 11 p.m., but your office opens at 9 a.m., they’ll probably move on before you can follow up.
In Google Ads, you can set your campaign to only run during your business hours.
You can also use the “Hour of the day” report to see exactly when conversions happen. So you can schedule your campaign based on real performance data.
Once you’ve got data, you can expand to early mornings or weekends if performance is strong.
Less waste. Better timing. Same budget.
6. Test Your Landing Pages to Maximize Budget
If you’re getting 100 clicks and only 2 leads, that’s not a CPC problem.
That’s a landing page problem.
The best ad in the world won’t help if the page people land on doesn’t convert.
I’ve worked with clients where we didn’t change the ad at all. Just added a few bullet points near the top of the page.
That one small tweak doubled their conversion rate.
Small changes like that can make a big difference in how many leads you get from the same ad spend.
For starters, you can tweak different parts of your landing page: the headline, form length, call to action, or how quickly your value is explained.
What to Do Before You Launch Your First Google Ads Campaign
Google Ads can feel simple on the surface: set a budget, write an ad, go live.
But if you skip a few key steps before launch, your budget can disappear fast.
I’ve seen businesses launch campaigns without setting up conversion tracking.
Some forgot to set their location targeting and showed ads in cities they don’t even serve. Others launched without a daily budget cap and burned through hundreds in a single day.
Small misses like that lead to wasted clicks, high costs, and zero results.
That’s why I created a pre-launch checklist.
It walks you through the exact steps to take before your first campaign goes live across Search, Shopping, Display, and YouTube.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-11 15:10:562025-09-11 15:10:56How Much Does Google Ads Cost? (2025 Data + Insights)
AI is already reshaping how buyers discover and choose brands.
When someone asks ChatGPT or Google AI Mode about your category, two things happen:
Brands are mentioned in the answer
Sources are cited as proof
Most companies get one or the other. Very few win both.
And that’s the problem.
According to the latest Semrush Enterprise AI Visibility Index, only a small fraction of companies appear in AI answers as both seen (mentions) and trusted (citations).
That gap is the opportunity.
We’re proposing the Seen & Trusted (S&T) Framework — a systematic approach to help your brand earn mentions in AI answers and citations as a trusted source.
Do both, and you multiply visibility, trust, and conversions across platforms like ChatGPT, Google AI Mode, and Perplexity.
SEO remains the foundation.
But AI doesn’t just look at your site. It pulls signals from review platforms, Reddit threads, news coverage, support docs, and community discussions.
When those signals are fragmented, your competitors will own the conversation.
This guide shows you exactly how to fix that with two playbooks:
Get Seen: Win favorable mentions in AI answers
Be Trusted: Earn citations as a reliable source
Run them together and you give AI no choice but to recognize, reference, and recommend your brand.
Why AI Search Strategy Isn’t Just SEO’s Job
Your SEO team can optimize every page on your site and still lose AI visibility to a competitor with weaker rankings but stronger brand signals.
Why? Because AI systems pull signals from everywhere, not just your website.
When AI generates responses, it mines:
Review platforms for product comparisons
Reddit threads for pricing complaints
Developer forums for implementation details
News sites for company credibility
Support docs for feature explanations
The challenge is that these signals live across different teams.
For instance, your customer success team drives customer reviews on G2 and Capterra. But if they’re not tracking review quality and detail, AI has nothing substantive to cite when comparing products.
Similarly, your product team controls whether pricing and features are actually findable. Hide everything behind “Contact Sales” forms, and AI will either skip you entirely or make assumptions based on old Reddit threads.
Your PR team lands media coverage and analyst reports. These third-party mentions build the trust signals AI systems use to determine authority.
Your support and community teams shape what gets said in forums and Discord servers. Their responses (or silence) directly influence how AI understands your product.
SEO and content teams own the site structure and content creation. But that’s just one piece now.
Without coordination, you get strong performance in one area, killed by weakness in another.
To grow AI visibility, you need synchronized campaigns — not just an “optimize for AI” line item tacked onto everyone’s OKRs.
That’s where the Seen & Trusted Framework comes in. It gives every team a role in building the signals AI depends on.
Note for enterprises: Cross-departmental coordination is challenging.
Fortunately, any progress each team makes in their area directly improves AI visibility.
Better reviews? You win. More transparent pricing? You win. Active forum engagement? You win. It all compounds.
This guide can be your internal business case. Forward the data on AI visibility gaps to stakeholders who need to see the competitive threat.
Solve this, and you’ll gain a big edge over competitors who are stuck in silos.
Playbook 1 – How to Get Seen (The Sentiment Battle)
Getting “seen” means showing up in AI responses as a mentioned brand, even without a citation link.
When a user asks ChatGPT, “What are the best email marketing tools?” they get names like HubSpot, ActiveCampaign, and MailChimp.
These brands just won visibility without anyone clicking through.
But here’s a challenge:
You’re fighting for favorable mentions against every competitor and alternative solution.
This is the sentiment battle.
Because AI doesn’t just list brands. It characterizes them.
You might get mentioned as “expensive but comprehensive” or “affordable but limited.”
Like here, when I asked ChatGPT if ActiveCampaign is a good option:
In some cases, the response could be more negative than neutral. Like this:
These characterizations stick.
So, how can your brand get more mentions and have a positive sentiment around?
There are four main sources that AI systems mine for context.
Pro tip: Track how AI platforms perceive your brand using Semrush’s Enterprise AIO sentiment analysis.
It shows whether mentions across ChatGPT, Claude, and other LLMs are positive, neutral, or negative.
Step 1. Build Presence on the Right Review Sites
AI systems heavily weigh review platforms when comparing products. But not all reviews are equal.
A detailed review explaining your onboarding process carries more weight than fifty “Great product!” ratings.
AI needs substance, like specific features, use cases, and outcomes it can reference when answering queries.
G2 is one of the top sources for ChatGPT and Google AI Mode in the Digital Technology vertical, according to Semrush’s AI Visibility Index.
The platform gives AI everything it needs: reviews, features, pricing, and category comparisons all in one place.
Slack ranks among the top 20 brands by share of voice in AI responses for the Digital Technology vertical.
Share of voice is a weighted metric from Semrush that reflects how often and how prominently a brand is mentioned across AI responses.
Part of that success comes from their G2 strategy.
When I ask ChatGPT, “Is Slack worth it?” it cites G2 as one of the sources.
Look at Slack’s G2 reviews and you’ll see why.
Its pricing, features, and other information are properly listed and up-to-date
Users write detailed reviews about channel organization, workflow automation, and integration setups.
G2 isn’t the only platform that matters.
For B2B SaaS: G2, Capterra, and GetApp
For ecommerce: Amazon reviews
For local/service businesses: Yelp and Google Reviews
In my experience, the depth of the review matters just as much as the platform — if not more.
You’ll see many very detailed product reviews as a source in AI answers from sites with low domain authority.
So, what does this mean in practice?
You need reviews from customers. And your review strategy needs four components:
Timing: Email customers after they’ve used your product enough to give meaningful feedbac, but while the experience is still fresh
Templates: Provide prompts highlighting specific features to discuss. “How did our API save you development time?” beats “Please review us.”
Incentives: Reward detail over ratings. A $XX credit for reviews over 200 words can generate more AI-friendly content
Engagement: Respond to every review. AI systems recognize vendor engagement as a trust signal.
Step 2. Participate in Community Discussions
Community platforms are where real product conversations happen. And AI systems are listening.
Reddit threads comparing alternatives
Stack Overflow discussions about implementation
Quora answers explaining use cases
These unfiltered conversations shape how AI understands and recommends products.
Reddit and Quora consistently rank among the top sources cited by ChatGPT and Google AI Mode across industries.
Like in the Business & Professional Services vertical here:
Online form builder Tally is a great example of dominating community discussions and winning the AI search.
AI-powered search is now their biggest acquisition channel, with ChatGPT being their top referrer.
This is their weekly signup growth of the past year, driven by AI search:
“Inclusion of web browsing is turned on by default, which made forums, Reddit posts, blog mentions, and authentic UGC part of the AI’s source material… We’ve invested for years in showing up in those places by sharing what we learn, answering questions, and being human.”
Here’s Marie talking about her product on Reddit:
And answering users’ questions:
And partaking in ongoing conversations:
This authentic engagement creates the context AI needs.
So, when I ask ChatGPT what’s the best free online form builder, it mentions (and recommends) Tally.
Big brands like Zoho take part in Reddit discussions as well. To answer questions, address concerns, and control their brand sentiment.
Like here:
Zoho ranks among the top brands by share of voice in ChatGPT and Google AI Mode responses. Just behind Google.
The community platforms like Reddit, Overflow, Quora, and even LinkedIn matter a lot in AI visibility:
Your community and customer success teams should be active on these platforms.
But presence alone isn’t enough.
Your strategy needs authenticity.
How?
Answer questions even when you’re not the solution
Address common misconceptions about your product (don’t let misinformation take over threads)
Share your actual product roadmap, including what you won’t build
Give detailed, honest responses to user complaints, even if it means acknowledging past mistakes
Encourage your product, support, or founder teams to answer technical or niche questions directly
AI systems can detect promotional language. They prioritize helpful responses over sales pitches.
The brands winning community presence treat forums like customer support, not marketing channels.
Step 3. Engineer UGC and Social Proof
User-generated content and social proof create a feedback loop that AI systems amplify.
When customers share their wins on LinkedIn
When users post before-and-after case studies
When teams document their workflows publicly
…all of this becomes training data.
Brands with strong community engagement and visible social proof see higher mention rates across AI platforms.
Patagonia is a fitting example here.
When I ask ChatGPT about sustainable outdoor brands, Patagonia dominates the response.
In fact, Patagonia holds the highest share of voice in AI responses for the Fashion and Apparel vertical.
They consistently appear in discussions around “ethical fashion” and “sustainable brands.”
Not because they advertise, but because customers evangelize. And that advocacy is visible everywhere.
Customers regularly mention their positive experience with Patagonia’s exchange policy.
There are countless positive articles written on third-party platforms about their products.
And on social platforms like Instagram.
These real-world endorsements are the kind of social proof AI recognizes and amplifies.
No wonder Patagonia has a highly favorable sentiment score (according to the “Perception” report of the AI SEO Toolkit).
So, how do you get people creating content (and proof) that AI pays attention to?
Encourage customers to leave ratings on trusted third-party sites
Partner with micro-influencers to share authentic product stories, tips, and reviews in their own voice
Invite users to post before-and-after results or creative use cases
Design features or experiences users want to show off (like Spotify Wrapped)
Reward customers who share feedback or use cases publicly (early access, shoutouts, or swag)
Reply to every public mention or tag because AI recognizes visible engagement
The mistake most brands make?
Asking for just testimonials instead of conversations.
Don’t ask customers to “share their success story.” Ask them to help others solve the same problem they faced.
The resulting content is authentic, detailed, and exactly what AI systems look for.
Step 4. Secure “Best of” List Inclusions
Comparison articles and ‘best of’ lists are key sources for AI citations.
When TechRadar publishes an article on top “Project Management Tools for Remote Teams,” that article becomes source material for hundreds of AI responses.
When Live Science reviews running watches, those comparisons train AI’s product recommendations.
These third-party validations carry more weight than your own content ever could.
In fact, sites that publish “best of” listicles consistently appear as top sources for AI platforms — including Forbes, Business Insider, NerdWallet, and Tech Radar.
Garmin is a perfect example.
Their products appear in virtually every “best GPS watch” article across running, cycling, and outdoor publications.
Like in this Runner’s World article:
Or this piece in The Great Outdoors:
But what makes their strategy work is consistency across platforms.
Yes, the specs are the same by nature.
But what stands out is how consistently those specs, features, and images appear across independent sites.
That repetition reinforces trust for AI systems, which see the same details confirmed again and again.
So, when I ask ChatGPT, “Which is the best GPS watch?” it mentions Garmin.
And it doesn’t stop there. It highlights features that other third-party articles emphasize, like battery life, accuracy, solar charging, and water resistance.
This consistency across independent sources is why Garmin holds one of the highest shares of voice in ChatGPT and Google AI Mode responses for the Consumer Electronics vertical.
So, how do you land in these “best of” lists?
It starts with a great product. Without that, no list will save you.
That aside, you need to make journalists’ jobs easier. Most writers work under tight deadlines and will choose brands that provide ready-to-use assets over those that make them hunt.
So build a dedicated press kit page with specs, pricing, high-res images, and other assets.
Like Garmin does here:
Next, reach out to journalists and niche publications. Don’t wait for them to find you.
Timing matters a lot as well.
Most “best of” lists update annually. So, pitch your updates a few months before refreshes.
Also, don’t just target obvious lists. Focus on category expansion.
For instance, Garmin doesn’t just appear in “best GPS watch” roundups. They also feature in broader outdoor and fitness lists that cover running, cycling, and multisport gear.
That reach multiplies the mentions AI systems can cite.
The bottom line: AI visibility favors the brands that keep showing up in independent comparisons.
Secure those “best of” inclusions, and you increase your chances of being mentioned in AI answers.
Playbook 2 – How to Be Trusted (The Authority Game)
Getting mentioned is half the battle. Getting cited is the other half.
When AI systems cite your content, they’re not just naming you. They’re using you as evidence to support their answers.
Look at any ChatGPT or Google AI Mode response.
At the bottom or side, you’ll see a list of sources. These citations are what AI considers trustworthy enough to reference.
According to Semrush’s AI Visibility Index, certain sources dominate AI citations across industries. Like Wikipedia, Reddit, Forbes, TechRadar, Bankrate, and Tom’s Guide.
They have achieved, what I call, the “Citation Core” status.
Citation core (n.): A small group of sites and brands that every major AI platform trusts, cites, and uses as default sources.
Why do these platforms get cited so often?
AI systems trust sources with verified information, structured data, and established credibility. They need confidence in what they’re citing.
This is the authority game.
You’ve earned mentions through the sentiment battle. Now you need to build the trust that also earns you citations.
This is how you maximize your AI visibility.
Here are five ways to build that authority.
Step 1. Optimize Your Official Site for AI
AI platforms can only cite what they can crawl, parse, and understand.
If your details aren’t exposed in clean, readable code, you’re invisible. No matter how good your content is.
Use semantic HTML to structure your content.
That means marking up pricing tables, product specs, and feature lists with tags like <table>, <ul>, and <h2>.
Don’t tuck information inside endless <div>s or custom layouts that hide meaning.
Also, avoid relying on JavaScript to render your main content.
AI crawlers can’t read JavaScript.
If your pricing or docs load only after scripts fire or buttons click, those details will be skipped.
Almost every top-cited site in AI answers passes the Core Web Vitals assessment, which signals that the page loads fast, stays stable, and presents content in a clean structure.
Like Bankrate — the most cited source in Google AI Mode for the Finance vertical:
Or InStyle — the 8th most cited source on ChatGPT in the Fashion & Apparel vertical.
These sites consistently surface in AI responses because their pages are easy to crawl, fast to load, and simple to extract structured information from.
A lot of what you’ll do to optimize your site for AI is SEO 101.
Structure all key information in native HTML elements (no custom wrappers)
Keep important content visible on initial load (no tabs, accordions, or lazy-loaded sections)
Use schema where it reinforces facts: pricing, product, FAQ, organization
Run regular audits with JavaScript disabled to see what AI sees
Minimize layout shifts and script dependencies that delay full render
To check your entire site’s health and performance, use Semrush’s Site Audit tool.
Get a detailed report showing technical issues on your website and how you can fix them.
At the end, you want a fast, stable, and easy-to-parse website.
That’s what earns AI citations.
Step 2. Maintain Wikipedia + Knowledge Graph Accuracy
AI systems rely on public data sources to build their understanding of your brand.
If that information is wrong, every answer AI generates about you will be too.
Wikipedia is one of the most cited sources on ChatGPT for all industries covered in Semrush’s AI Visibility Index.
Interestingly, Google AI Mode leans heavily on its Knowledge Graph to validate facts about companies and products.
When your Wikipedia page contains outdated info — or your Knowledge Graph shows old details — those inaccuracies get baked into AI responses.
That hurts trust, sentiment, and your chance of being cited in the long-term.
So your job is twofold:
Make sure your brand exists in these systems
Keep the data clean and current
Start with your Wikipedia page.
If you have one, audit it quarterly.
Fix factual errors, like outdated product names, revenue ranges, or leadership bios.
Support every edit with a credible third-party source: news coverage, analyst reports, or industry publications.
Wikipedia doesn’t allow brands to directly promote themselves. And promotional edits get removed.
But updates to fix factual errors usually stick. As long as you provide solid citations.
You can use the “Talk” page of your Wikipedia entry to propose corrections.
If you don’t have a Wikipedia page, you’ll need to meet notability guidelines.
That typically means coverage in multiple independent, well-known publications.
Once that’s in place, a neutral editor (not on your payroll) can create the page.
Next, fix your Knowledge Graph.
Google pulls its brand facts for its knowledge graph from multiple sources. Like Wikidata, Wikipedia, Crunchbase, social profiles, and your own schema markup.
Start by “claiming” your Knowledge Panel.
This means a knowledge panel already exists for your company when you search its name. You just have to claim it by verifying your identity.
If you don’t see one, you’ll need to feed Google more structured signals.
Start by adding or improving your Organization schema on your homepage.
Then, make sure your company has a proper Wikidata entry. Google may use this to build its Knowledge Graph.
Note: Adding your company to Wikidata is much easier than getting a full Wikipedia entry. But you still need to follow the guidelines. Stick to neutral language, avoid any promotional tone, and cite credible third-party sources.
A strong Wikipedia page and Google knowledge panel shape how AI understands your brand.
Get them right, and you build a foundation of factual authority that AI systems can trust.
Step 3. Publish Transparent Pricing
Hidden pricing creates negative sentiment that AI systems pick up and amplify.
When users can’t find your pricing, they turn to Reddit and LinkedIn. And the speculation isn’t always favorable.
For instance, Workaday doesn’t show its pricing.
And the Reddit comments aren’t helpful to its potential customers.
According to Semrush’s AI Visibility Index, when enterprise software hides pricing behind “Contact Sales,” AI uses speculative data points from Reddit and LinkedIn.
And it often links that brand with negative price sentiment.
Because AI systems are biased toward answering, even if it means citing speculation.
They’d rather quote a complaint from third-party sites about “probably expensive” than admit they don’t know.
Without clear pricing, you’re also excluded from value-comparison queries like “best budget option” or “most cost-effective for enterprises.”
Publishing transparent pricing creates reliable data that AI trusts over speculation.
Now I understand this isn’t always possible for every brand. Whether to show pricing depends on various other decisions and strategies.
But if you want to build trust for higher AI visibility and positive sentiment, transparent pricing is important.
Which means:
Include tier breakdowns with feature comparisons
Spell out annual vs. monthly options
List any limitations or user caps
Update your pricing on G2, Capterra, and other review sites
When reliable sources like your pricing page and G2 have clear information, AI stops turning to speculation.
That transparency becomes part of your brand identity and authority.
Step 4. Expand Documentation & FAQs
Your support docs and help center often get cited more than your homepage.
Because AI systems look for detailed, problem-solving content. Not marketing copy.
Apple holds one of the highest shares of voice in ChatGPT and Google AI Mode responses for the Consumer Electronics vertical.
Its support documentation appears consistently in AI citations across tech queries.
When I ask ChatGPT how to fix an iPhone issue, it cites support.apple.com.
Product documentation dominates citations in technical verticals.
Why?
Because it answers specific questions with step-by-step clarity.
Your product documentation is a citation goldmine if you structure it right.
Start by creating dedicated pages for common problems. “How to integrate [Product] with [Product]” beats a generic integrations page.
For example, Dialpad has dedicated pages for each app it integrates with.
And each page clearly explains how to connect both apps.
Next, write troubleshooting guides that address real user issues.
(You can learn about these issues from your sales teams, account managers, and social media conversations.)
Also, build a comprehensive FAQ library that actually answers questions. Not marketing-friendly softballs, but the hard questions users really ask.
Make sure every page is crawlable:
Use static HTML for all documentation
Create XML sitemaps specifically for docs
Implement breadcrumb navigation
Add schema markup for HowTo and FAQ content
The goal is to become the default source when AI needs to explain how your product works.
Not through SEO tricks, but by publishing the most helpful, detailed, accessible documentation in your space.
Step 5. Create Original Research That AI Wants to Cite
Original research gives AI systems something they can’t find anywhere else. Your data becomes the evidence they need.
Take SentinelOne as an example. It’s a well-known brand in cybersecurity.
They regularly publish threat reports, original data, and technical insights.
This is one of the reasons they often get cited as a source in AI responses.
In the intro, I said very few brands are both mentioned and cited by AI. Remember?
SentinelOne is one of those brands that has built dual authority.
According to Semrush’s AI Visibility Index, it’s the 15th most cited and 19th most mentioned brand in the Digital Technology vertical.
Because it publishes original insights that aren’t available anywhere.
And AI systems want: verified data, industry insights, and quotable statistics.
But not all research gets cited equally.
Annual surveys with significant sample sizes (think: 500+) carry weight. But “State of [Industry]” reports based on 50 responses might not.
Benchmark studies comparing real performance data become go-to references. But thinly-veiled sales pitches disguised as research might get ignored.
You can use your proprietary data to create original research reports.
Or team up with market research companies like Centiment that can help you collect data through surveys.
When creating these reports:
Lead with key findings in bullet points
Include methodology details for credibility
Provide downloadable data sets when possible
Add structured data markup for datasets
Also, promote findings through press releases and industry publications.
When Forbes, TechCrunch, and other leading publications cover your research, AI systems are more likely to notice.
Like this SentinelOne report covered by Forbes:
The compound effect here is powerful.
Your research gets cited by news outlets → which gets cited by AI → which drives more coverage → which builds more authority.
That’s how you go from being mentioned to being the source everyone (including AI) trusts.
Pulling It All Together – Running Both Playbooks
You’ve seen the framework. Now it’s time to execute.
Step 1. Audit Your Current AI Visibility
Start by understanding your baseline.
Run test queries in ChatGPT and Google AI Mode. Search for your brand, your category, your product, and the problems you solve.
Note where you’re mentioned (in the answer itself) and where you’re cited (in the source list). Screenshot everything.
If you’re using Semrush’s Enterprise AIO, you can use Competitor Rankings to see how often your brand shows up in AI answers compared to your competitors.
Step 2. Build Parallel Campaigns
Both playbooks need to run simultaneously.
You can’t wait to be “seen” before building trust.
Playbook 1 (Seen): Customer success drives review campaigns. Community managers engage in forums. PR pushes for “best of” list inclusion.
Playbook 2 (Trusted): Product publishes transparent pricing. SEO and engineering improve site structure. Support expands help content. Marketing creates original research.
The key is coordination.
Create a shared dashboard to track each team’s contributions to AI visibility.
Step 3. Monitor and Iterate
AI visibility shifts fast. What worked last month might not work today.
Track your mentions and citations monthly.
Use an LLM tracking tool like Semrush or a manual prompt list to see how you’re showing up (and how often).
Google is piloting a new “Sales & Promotions Feature Bundle with Flighted Budgets” in Google Ads, designed to help advertisers push harder during short-term promos without wasting spend.
What’s new
Campaign Total Budgets: Fix a set spend across 3-90 days.
Promotion Mode: Accelerates spend for 3-14 days, prioritizing volume over strict efficiency.
Cross-campaign support: Works with Performance Max, Search, and Shopping – including tROAS and tCPA bidding strategies.
Why we care. This update gives more control over spend pacing and volume during promotions, something current Google Ads tools can’t fully deliver. Instead of just telling Smart Bidding that conversion rates will spike, the feature bundle actively reallocates budget to hit promo goals – whether for flash sales, holiday weekends, or ticket launches. In short, it helps advertisers spend faster, scale smarter, and maximize returns when timing matters most.
How it’s different. Instead of just adjusting for expected conversion rate shifts, the bundle uses sale dates, promo assets, and explicit ROAS tradeoffs to give Google Ads stronger signals for promotion periods.
Best fits
Flash sales
Holiday weekends and seasonal promotions
Ticket launches, travel deals, and other time-sensitive offers
What’s next. Advertisers running Q4 promos could see major upside if they test this tool early. The big shift will be deciding when to prioritize scale over efficiency – a tradeoff this feature makes more explicit than ever.
First seen. This alpha release was noted by Yash Mandlesha, co-founder of Mediagram, on LinkedIn.
The search and marketing world never slows down. Last week’s inaugural edition of Semrush’s Marketing Countdown, featuring Search Engine Land, explored how the landscape is rapidly shifting under our feet.
We unpacked five of the biggest stories making waves:
Bottom line: SEO remains critical in the AI-driven search era. A strategic, brand-focused, and user-first approach is essential. Companies must align messaging, produce authoritative content, and track emerging AI visibility metrics to thrive in a diversified, AI-influenced ecosystem.
Here’s the video of everything you need to know to stay ahead of the curve – plus takeaways and insights you won’t want to ignore.
Marketing Countdown was hosted by Rita Cidre, head of Academy at Semrush, and featured:
Mordy Oberstein, Founder of Unify and communications advisor for Semrush
Danny Goodwin (that’s me), Editorial Director at Search Engine Land
Erich Casagrande, content product specialist at Semrush
It focused on the evolving landscape of SEO, the impact of AI on search, and actionable marketing strategies. Some of the key themes discussed:
Generative AI in search
AI is changing how people research, but Google remains the dominant starting point due to habit and trust.
AI summaries offer convenience but often reduce clicks to websites, posing challenges for publishers.
Google’s AI upgrade
Google’s announcement of its biggest search upgrade lacked transparent data.
Publishers report rising impressions but falling clicks, showing a “great decoupling” between search visibility and user traffic.
Answer engines and content
Platforms like Perplexity highlight the need for authoritative content, topical authority, and trusted citations.
Video content and user engagement are increasingly important for visibility.
Google AI Mode
Rolled out in 180+ countries.
Presents comprehensive AI-generated answers in a separate tab, suggesting a future where AI synthesizes multiple subtopics into a single response.
ChatGPT & Google
Despite OpenAI’s claims of Bing reliance, ChatGPT Plus reportedly pulls from Google results, reinforcing Google’s central role in SEO.
Shift in marketing strategy
Marketers need to blend tactical SEO with brand-building.
Fragmented channels and AI-driven search require holistic, integrated strategies.
Unsiloing teams
Consistency across marketing and AI platforms is essential to avoid contradictory brand messaging.
SEO best practices
Focus on high-quality, user-centric, contextual content rather than outdated keyword tactics.
New metrics include brand mentions, sentiment analysis, and AI visibility tracking.
Content sources for AI
YouTube and Reddit are frequently cited in AI answers.
TikTok and Instagram are less influential in this context.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/09/marketing-countdown-5-industry-shakeups-sept-2025-GbUl0D.jpg?fit=1920%2C1080&ssl=110801920http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-09 14:00:002025-09-09 14:00:00Video: 5 AI search stories you need to know (September 2025)
Google is rolling out new tools in Google Ads designed to unify web and app advertising, making it easier for marketers to deliver consistent customer journeys and measure performance across platforms.
What’s new
Web to App Connect expansion: You can now send YouTube, Hotel, and Demand Gen ad clicks directly to apps – extending the feature beyond Performance Max, Search, and Shopping campaigns. Google says brands using Web to App Connect on YouTube have seen 2x higher conversion rates.
Unified workflows:
In-product nudges now help you optimize toward in-app events.
Unified conversions bundle app and web events for easier setup.
A new combined overview card shows side-by-side web and app performance directly on the Ads homepage.
App install measurement from web campaigns: For the first time, Search and Shopping campaigns can be credited with driving new app installs and in-app conversions.
Why we care. Managing campaigns across websites and apps has long been a pain point. Customers often bounce between platforms before converting, and disconnected reporting makes it difficult to see what’s working. These updates could help you tighten your funnel, reduce wasted spend, and create app-first strategies that unlock higher ROI.
The big picture. By connecting web and app activity inside Google Ads, you can:
Attract high-value customers: Push users into apps, where they’re more likely to engage and convert.
Streamline campaigns: Target and optimize across web + app without juggling separate workflows.
See the full funnel: Attribute installs and conversions to web campaigns for a more accurate performance picture.
What’s next.With unified reporting, it’ll be easier to spot which touchpoints drive the most value – but it may also expose underperforming spend. Expect brands to test more app-first journeys, especially in categories like retail, travel, and subscription services, where in-app conversions typically outperform the web.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-09 13:24:592025-09-09 13:24:59Google Ads links web + app campaigns with new features
Today, we’re excited to welcome Yoast AI Summarize to our growing family of AI features. Just like our other AI tools, this new feature is designed to make your publishing process faster and easier by putting powerful, practical AI right where you work, in the WordPress Block Editor.
Yoast AI Summarize is perfect for bloggers, content teams, agencies, and publishers who want to give readers instant value while also making sure their posts clearly communicate the intended message.
What does Yoast AI Summarize do?
You’ve finished drafting your post, great! But before you hit “Publish,” wouldn’t it be helpful to instantly see the core points your content is actually conveying? That’s exactly what Yoast AI Summarize does.
With one click, you can insert a Key Takeaways block into your content. Yoast AI Summarize scans your post’s main body and creates a short, bullet-point summary, giving your readers a quick, scannable snapshot, and giving you a chance to check if your post is truly saying what you want it to.
How you can access the new feature
Yoast AI Summarize is automatically available to all Yoast SEO Premium customers. Just make sure you’ve updated to the latest version and granted consent to use AI.
Once enabled, simply:
Open your post in the WordPress Block Editor.
Add the new block from the “Yoast AI Blocks” section
Click to generate summary, and watch your Key Takeaways section appear in seconds.
Where you can use Yoast AI Summarize
Right now, Yoast AI Summarize works in the WordPress Block Editor on posts and pages. The block is fully editable, you can change the title, rewrite bullet points, or move it anywhere in your content flow.
Pricing and usage
There are no hidden costs for Yoast AI Summarize, it’s included in Yoast SEO Premium. Like our other AI features, it uses our spark counter to track usage.
A spark is a single click on an AI feature.
Generating one summary = one spark.
Your spark counter resets at the start of each month.
There’s currently no hard limit, so you can experiment freely.
Limitations
Yoast AI Summarize is currently in beta. That means you may notice a few restrictions:
Only available in the WordPress Block Editor.
Summaries are excluded from Yoast SEO and Readability Analysis to protect your scores.
Currently works only on published or drafted content within supported blocks.
For very long posts, it may take a few seconds for the summary to generate.
Try out Yoast AI Summarize today
Upgrade to Yoast SEO Premium to unlock this and all our AI features, including the award-nominated Yoast AI Generate and the powerful Yoast AI Optimize. With Yoast AI Summarize, you can work faster, keep your content aligned with your intent, and give your readers instant value with clear, scannable takeaways.
Update to the latest version and try it out today!
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-09 09:09:432025-09-09 09:09:43New: From longform to key takeaways, in seconds. Meet Yoast AI Summarize
As part of our broader APAC plan, which includes new Deep Dive events and two local language
editions, we are happy to announce the details for our Chinese language event: Search
Central Live Hong Kong!
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2021/12/web-design-creative-services.jpg?fit=1500%2C600&ssl=16001500http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-08 06:00:002025-09-08 06:00:00Search Central Live Hong Kong 2025: Event in Chinese focusing on international ecommerce
Product variations are more than just an ecommerce feature. They give your customers choices, whether it’s size, color, style, or material, while helping your store stand out in competitive search results. When optimized correctly, product variations do more than display available options. They improve the customer experience by making shopping easier. At the same time, they boost conversions by catering to diverse needs and support your SEO strategy by targeting more keywords.
This guide will explain the best practices for product variations and show you how to optimize them for search engines and customers so your ecommerce site can grow in traffic, rankings, and sales.
What are product variations in ecommerce?
Product variations or product variants are different versions of the same product designed to give customers options. These variations can be based on attributes like size, color, material, style, or capacity. Instead of creating multiple product listings, variations group all options under a single product, making it easier for customers to browse and purchase.
For example, when you search for an iPhone on Amazon, you’ll see options for different colors and storage capacities, all available on a single page. This setup lets customers explore multiple choices without leaving the main product page.
Example of product variants
Managing product variations depends on the platform you use:
In WooCommerce, product variations are created using attributes such as size or color, and then assigning values to those attributes. Store owners can upload unique images, set prices, and adjust stock for each variation
In Shopify, variations are managed under the ‘Variants’ section of a product. You can add options like size, color, or material, and then assign values. Each variant can have its own price, SKU, and image, making it simple to customize how the variations appear in your store
Okay, now let’s see why you need product variants and not upload each option as a completely separate product. Think of it this way: customers don’t want to scroll through endless listings just to compare a black t-shirt with a white one or a 64GB phone with a 128GB version. Variations keep everything in one place, making shopping smoother and more intuitive.
Here’s why product variations are so important for your customers:
Improved shopping experience: Variants reduce unnecessary clicks and allow customers to compare options side by side within a single product page. This saves time and makes decision-making easier
Higher conversions and lower bounce rates: When customers find their preferred size, color, or feature right away, they are more likely to complete a purchase instead of leaving your store
Reduced purchase anxiety: Variants ensure customers do not feel limited by stock. Seeing multiple choices available decreases the chance of cart abandonment
Personalization and satisfaction: Offering customers options empowers them to choose a product that feels tailor-made for them, improving overall satisfaction
Indirect SEO benefits: A better shopping experience often leads to longer session durations, fewer bounces, and more engagement. These signals may indirectly support stronger SEO performance, as they align with positive user experience metrics
How do product variations support your ecommerce SEO strategies?
Product variations are not just about creating a better shopping experience; they also bring direct ecommerce SEO benefits that can help your store attract more qualified traffic. When optimized correctly, variants can make your product pages richer, more discoverable, and more engaging.
Increase in keyword targeting
Variants allow you to target a wider range of long-tail keywords that reflect real customer search behavior. For example, instead of only competing for ‘men’s wallet,’ you can rank for ‘men’s black leather wallet’ or ‘slim men’s brown wallet.’ These specific keywords usually carry higher purchase intent and face less competition
Levi’s product page for jeans uses long-tail keywords in the product description for keyword targeting
Richer content for search engines and AI engines
Each variation allows you to add unique attributes, descriptions, and specifications. This creates a more detailed and content-rich product page that search engines and AI-driven engines (like ChatGPT or Google’s AI Overviews) value when surfacing answers and shaping brand perception.
ChatGPT showing product options for a t-shirt
Improved user engagement and longer sessions
A well-structured page that clearly displays variations keeps users from bouncing to competitor sites when they don’t immediately find their preferred option. Instead, they spend more time exploring, comparing, and interacting with your store, which indirectly supports SEO through stronger engagement signals.
Better structured data for enhanced search results
When product variants are properly marked up with structured data, search engines can display rich snippets that include price ranges, availability, color options, and reviews. This not only makes your listings stand out but also boosts click-through rates (CTRs) from search results.
Yoast SEO’s Structure data feature describes your product content as a single interconnected schema graph that search engines can easily understand. This helps them interpret your product variations more accurately and increases your chances of getting rich results, from product details to FAQs.
In short, optimized product variants make your product pages more keyword-diverse, content-rich, and engaging while also improving how your store is presented in search results and generative AI chat replies.
Blueprint for optimizing your product variations
Here’s the part you’ve been waiting for: how to optimize your product variations for SEO, conversions, and user experience. In this section, we’ll cover the right technical implementation, smart SEO tactics, and the common mistakes you’ll want to avoid.
Technical implementation of product variations
Getting the technical setup right is the foundation for optimizing your product variations for both ecommerce SEO and user experience. Poor implementation can lead to crawl inefficiencies, duplicate content, and a confusing buyer journey.
Here’s how to approach it effectively:
Handling variations in URLs
One of the biggest decisions you’ll make is how to structure URLs for your product variations:
Parameters (e.g., ?color=red&size=12): Good for filtering and faceted navigation, but they can create crawl bloat if not managed properly. Always define URL parameters in Google Search Console and use canonical tags to consolidate signals
Separate pages for each variation (e.g., /red-dress-size-12): This can be useful when specific variations have significant search demand (like ‘iPhone 15 Pro Max 512GB Blue’). However, it requires careful duplication management and unique, optimized content for each page
Single product page with dropdowns or swatches: The most common approach for ecommerce stores, as it consolidates SEO signals into one canonical page while providing users with all available variations in one place
Takeaway: Use a hybrid approach. Keep a single master product page, but only create dedicated variation URLs for high-demand search queries (with unique descriptions, images, and structured data).
Note: only create dedicated variation URLs if you can add unique value (content/images), otherwise, it risks duplication
Internal linking best practices
Internal linking is crucial in helping search engines understand the relationships between your main product page and its variations.
Always link back to the parent product page from any variation-specific pages
Ensure your category pages link to the main product page, not every single variation (to prevent diluting crawl equity)
Use descriptive anchor text when linking internally, e.g., ‘men’s black leather wallet’ rather than just ‘wallet’
The Internal linking suggestions feature in Yoast SEO Premium is a real time-saver. As you write, it recommends relevant pages and posts so you can easily connect variations, parent products, and related content. This not only strengthens your site structure and boosts SEO but also ensures visitors enjoy a seamless browsing experience.
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!
Takeaway: Build a clean hierarchy where category pages → main product pages → variations, ensuring both users and crawlers can navigate easily.
Managing faceted navigation and filters
Filters (like size, color, brand, or price) enhance user experience but can create SEO challenges if every filter combination generates a new crawlable URL.
Use <nofollow or noindex for low-value filter pages (like ‘price under $20’ if it doesn’t add SEO value)
Block irrelevant filter parameters in robots.txt to prevent crawl bloat
For valuable filters (e.g., ‘red running shoes’), allow them to be indexed and optimize the content
Takeaway: Conduct a filter audit in Google Search Console. Identify which filtered URLs actually drive impressions and clicks, and only allow those to be indexable.
Media content optimization for ecommerce product variations
When it comes to product variations, visuals and supporting media play a critical role in both SEO and conversions. Shoppers often make purchase decisions based on how well they can visualize a specific variation. In fact, 75% of online shoppers rely on product images when making purchasing decisions.
Here’s how you can optimize media content for ecommerce product variations:
Use unique images for each variation
Avoid using the same generic image across all variations. Display each color, size, material, or feature with its own high-quality image set. For example, if you sell a t-shirt in six colors, show each color separately to help customers make confident choices.
Unique product images for each variant
Leverage 360° views and videos
Showcase variations with interactive media like 360° spins or short product videos. For example, a ‘black leather recliner’ video demonstrates texture and function more effectively than a static image, leading to higher engagement and conversions.
Use videos and 360-degree media to portray your products
Optimize alt text, file names, and metadata
Every image should have descriptive, keyword-rich alt text that specifies the variation. Instead of writing ‘red shoe,’ use ‘women’s red running shoe size 8.’ File names (e.g., womens-red-running-shoe-size8.webp) and captions should also reinforce the variation for better indexing.
Implement structured data for media
Use the Product schema to explicitly define images and videos for each variation. Including structured data ensures that Google and AI-driven engines like ChatGPT can clearly interpret your variation visuals and display them in rich results or AI summaries.
For instance, assigning images to specific SKUs (via image markup) makes it easier for search engines to show the correct variation in shopping results.
SEO tips for product variations
Optimizing product variations for SEO requires more than attractive visuals and solid descriptions. You need to apply some proven SEO techniques to ensure search engines correctly interpret your product pages and users get the best possible experience.
Here are a few key practices every ecommerce store owner should follow:
Use canonical tags to avoid duplicate content issues
Product variations often generate multiple URLs, which can cause duplicate content problems. Canonical tags help solve this by pointing to the primary version of a page, consolidating ranking signals, and avoiding internal competition.
Yoast simplifies this process by automatically inserting canonical URL tags on your product pages. This ensures search engines know which version to prioritize, prevents diluted link equity, and even consolidates social shares under the original page. For store owners, this means less technical overhead and stronger, cleaner rankings.
Apply global product identifiers (GTIN, MPN, ISBN) where relevant
Global product identifiers like GTINs, MPNs, and ISBNs act as unique fingerprints for your products. They help Google and other search engines correctly match your items in their vast index, which improves the accuracy of search listings and reduces confusion with similar products. They also add credibility, since customers can cross-check these identifiers before purchase.
With Yoast WooCommerce SEO, adding these identifiers becomes much easier. The plugin reminds you to fill in missing SKUs, GTINs, or EANs for each product variation and automatically outputs them in structured data. This not only helps your products qualify for rich results but also ensures that no variant is left incomplete from an SEO standpoint.
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Regularly audit Google Search Console data to track performance
Google Search Console is a goldmine for understanding how product variations are performing. By monitoring which variant pages are driving impressions, clicks, and conversions, you can refine your SEO strategy.
For example, if certain variants attract little traffic but consume crawl budget, it might be better to consolidate them under canonical tags.
Regular audits also help you detect indexing issues, thin content problems, or underperforming structured data. This keeps your product catalogue lean, crawl-efficient, and focused on driving meaningful organic traffic.
Common product variation ecommerce errors to avoid
Even if you’ve implemented the right technical setup, added structured data, and optimized your media content, a few small mistakes can undo all that effort. To make sure your product variations support SEO and conversions instead of hurting them, here are some common pitfalls to avoid:
Duplicate content: Creating separate standalone pages for each variation (like size or color) without consolidation leads to content duplication. This confuses search engines and dilutes rankings across multiple weak pages
Poor user experience: If your variation options are hidden, unclear, or slow to load, users struggle to make choices. This friction reduces conversions and increases bounce rates
Incorrect structured data: Applying schema inaccurately can cause search engines to display the wrong product details in search results, damaging credibility and visibility
Thin content: Not providing unique descriptions, images, or metadata for each variation leaves the page with little value. Search engines tend to down-rank such content, reducing discoverability
Crawl bloat: Generating too many low-value variation URLs (like separate pages for every minor option) wastes crawl budget and prevents high-priority pages from being indexed efficiently. Additionally, it could dilute internal link equity
By keeping these errors in check, you’ll ensure your product variation strategy strengthens your SEO and user experience instead of working against them.
Ready to unfold all variations?
Product variations are not just small details hidden in your catalogue. They play a major role in how both search engines and shoppers experience your store. When done right, they prevent duplicate content issues, improve crawl efficiency, deliver richer search results, and create a seamless journey for your customers.
The key is to treat product variations as part of your overall SEO strategy, not as an afterthought. Every unique image, structured snippet, and clear variation option makes your store more visible, more reliable, and more profitable.
This is where Yoast SEO becomes a game-changer. With automatic structured data, smart handling of canonical URLs, and advanced content optimization tools, Yoast helps you get product variations right the first time.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-04 17:05:512025-09-04 17:05:51A detailed guide to optimizing ecommerce product variations for SEO and conversions
“Good SEO is good GEO.” That’s according to Google’s Danny Sullivan, a director within Google Search, and former search liaison
Generative engine optimization (or whatever the new acronym is for optimizing for AI search experiences) is the same core work SEOs have always done: creating unique, valuable content for people and providing a great page experience, he said.
Why we care. You can believe Google if you want. But we’ve tried to consistently say that we believe GEO is an emerging practice. That doesn’t mean it replaces SEO today or tomorrow – because SEO fundamentals matter and SEO is still not dead. But I also agree with Michael King’s assessment that SEO is deprecated. The future of Google and conversational AI search will be answers, not ranking, regardless of what Googlers say publicly today.
What he’s saying. Here’s some of what Sullivan said about SEO/GEO during his keynote at WordCamp US on Aug. 28:
“…If you don’t know what GEO is, it’s like the latest acronym, but like I can’t keep track each day. There’s a different one. But SEO, search engine optimization; GEO, generative engine optimization.
By the way, if you could dig it out when I was like in 2010, back when people were panicking then, I was like, you know, SEO doesn’t mean you get into the blue links on Google. SEO means you understand how people search for content and then you understand how to have your content there. And it could be everything from people asking a question to a voice device to people just opening up something on their phone or whatever.
So, the basic things have not changed. Good SEO is good GEO, or AEO, AIO, LLM SEO, or LMNOPO. So, they’re all fine. What I’m trying to say is don’t panic. What you’ve been doing for search engines generally, and you may have thought of as SEO, is still perfectly fine and is still the things that you should be doing. … Good SEO is really having good content for people.
… Are you saying write things in a clear way that people can understand? Cool. Like that’s just for people. All right.
Are you saying write about things that are unique or interesting? Cool. That’s good for people. And all we [Google] try to do is understand how our signals can align with things that are good for people.”
CTR question. During the audience Q&A, blogger Angie Drake said her organic search click-through rate has plummeted since AI Overviews launched, even though impressions are up (known as the great decouoling of search). She asked Sullivan what Google will do to compensate publishers who are losing clicks. Sullivan’s response:
Google has been unapologetic about zero-click factual answers (e.g., “What time is the Super Bowl?”) because users expect direct facts.
Google is committed to rewarding unique, valuable content and supporting the open web.
He said there will be “bumps along the way,” that feedback is heard within Google, and “it’s still part of what we’re going to be figuring out.”
Other takeaways. Some other data Sullivan shared:
Google AI Overviews have led to a 10% increase in searches in the U.S. and India.
Google does “up to 5,000 launches” (a.k.a., updates) per year. The last figure we had was 4,725, so not much has changed since 2022.
The keynote. Here is the full video. I’ve linked to the takeaways portion of Sullivan’s presentation, where he discusses GEO. Drake asks her CTR question starting at 45:06.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2025/09/zf_sxldftby-KkLY6x.jpg?fit=1280%2C720&ssl=17201280http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-02 14:59:012025-09-02 14:59:01Google’s Danny Sullivan: ‘Good SEO is good GEO’
