Oct 19, 2026
How Does Your Brand Appear in ChatGPT and Gemini Shopping Recommendations?
A 12-step digital visibility guide for brands in the age of AI.
E-commerce
SEO
AI
Context
Visibility is a tool. The goal is sustainable customer acquisition and profitable growth.
When a consumer types “best men's perfumes” into Google, brands have been fighting for years to appear in the search results.
So what happens when the same consumer asks ChatGPT:
“Recommend five men's perfumes that suit an office environment, last long, aren't too heavy and offer good value for money.”
Would you want your brand to appear in the answer?
Of course.
But there is an important distinction here.
In traditional search engine optimisation, one of the core goals was to gain visibility for specific queries.
In AI-assisted product discovery, it also becomes important that the brand can be correctly associated with the customer's need.
That is why SEO work needs to be approached from a broader perspective.
First, let's separate two concepts.
SEO (Search Engine Optimization) covers work aimed at increasing visibility in search engines.
GEO (Generative Engine Optimization) is the approach of creating content that generative AI systems can discover, understand and represent reliably.
That said, it is not right to treat GEO as a new technique completely independent of SEO or one that produces guaranteed results.
Google's official statements published in 2026 also note that core SEO practices remain important for AI-assisted search features and that no special AI file or separate schema type is required.
So what should brands do?
Analysis
1. Don't introduce your products by their names alone
Imagine a product title on an e-commerce site looks like this:
“MEN'S PERFUME E-125 50 ML”
This title may be understandable inside the company.
But it does not sufficiently describe the customer's real need.
Which fragrance family does the product belong to?
Is it suitable for daily use?
How intense is it?
What settings is it designed for?
This information is important for understanding the product.
Instead of filling product descriptions with a few marketing adjectives, structure them around concrete features.
For example:
“A 50 ml men's Eau de Parfum with a woody, aromatic character, designed for daily wear.”
Of course, such statements must match the product's real features.
The aim is not to repeat keywords, but to explain clearly what the product offers.
2. Answer customer questions on product pages
Customers don't just want to learn product features.
They want to understand whether the product suits them.
That is why product pages should answer real, frequently asked customer questions.
For a perfume:
“What is the character of the scent?”
“Is it suitable for daily use?”
“Which fragrance notes does it contain?”
“What are the product's volume and concentration?”
For a clothing item:
“How does it fit?”
“What fabric is it made of?”
“What are the care instructions?”
“What conditions is the product suitable for?”
This information both improves the customer experience and can make it easier to associate the product with different search intents.
But producing hundreds of questions that are never actually asked, purely for search engines, is not right.
Content should be useful to the customer.
3. Use Product schema
Structured data should be used so that the information on product pages can be interpreted more clearly by search engines.
On e-commerce sites, one of the most important types of structured data is the Product schema.
Within this structure, fields such as product name, description, image, brand, price and availability can be included.
When the required conditions are met, this information can be used in Google's product-focused search experiences.
But adding structured data does not mean the product will definitely be shown in a particular result.
What matters is that the marked-up information matches what the customer sees on the product page.
Google's official Product and Offer documentation should be taken as the core reference here.
4. Keep your Google Merchant Center data up to date
Google Merchant Center is one of the core tools for presenting product information to Google's shopping ecosystem.
Consistency in product catalogues is especially important.
Price, stock status, product title, variant information and images must be managed correctly.
For example, a product that is out of stock on the product page but shows as in stock in the data feed can harm the customer experience.
Similarly, prices not matching across systems can cause problems.
That is why, instead of preparing product data once and leaving it, it should be checked regularly.
Up-to-date product data is not just SEO work.
It is also an indicator of the quality of commercial operations.
In Depth
5. Make your brand's digital identity consistent
If a brand is described with different information on different platforms, building a reliable and consistent digital identity can become difficult.
Core information should be consistent across the brand description on the corporate website, social media accounts, marketplace profiles and other official channels.
Which categories the brand operates in, which customer needs it meets and which features differentiate it should be explained clearly.
This distinction is especially important for companies that manufacture, offer private label services or have more than one sales channel.
Because the same company may have its own brand while also producing for other brands.
Defining these activities correctly online makes it easier to tell the brands apart.
6. Produce content that contains real expertise
In the world of AI-assisted search, producing content does not mean simply repeating certain words.
Original information, real experience and explanatory analysis matter.
Instead of only describing its products, a cosmetics brand could benefit from content that explains fragrance families, product selection criteria or usage habits.
A retail consultancy, on the other hand, should explain real commercial problems and its approach to solving them, rather than just listing the services it offers.
For example:
“Why does store conversion rate fall?”
“How can stock turnover be improved?”
“How is like-for-like sales growth analysed in retail?”
Content like this makes expertise visible while also answering potential customers' questions.
Especially in B2B services that require expertise, credibility must be built not only through advertising but through knowledge and experience.
7. Check technical accessibility
No matter how good the content on a website is, if search engines cannot access it, visibility problems can arise.
That is why technical SEO checks should not be neglected.
Robots.txt settings should be reviewed.
It should be confirmed that important pages are not accidentally blocked.
The sitemap should be kept up to date.
Canonical tags should be checked.
The mobile experience of pages should be evaluated.
It is also important that product and content information does not remain only inside complex visual components, but is presented in appropriate text fields.
Additional files such as llms.txt can be considered optionally. But using them does not guarantee visibility in AI systems and does not replace core SEO work.
8. Improve your category pages
In e-commerce, category pages are often designed simply as areas where products are listed.
Yet a well-prepared category page can make the purchase decision easier.
For example, instead of only showing products in a “Men's Perfumes” category, scent characters, purposes of use and selection criteria can be explained.
Similarly, in a “Premium Women's Clothing” category, the material features, collection approach or areas of use of the products can be described.
This content should provide real information to the user and should not make the product-listing experience harder.
The aim is not to fill the page with text.
It is to help the customer choose the right product more easily.
9. Make product images part of the information architecture
Product images do not serve only an aesthetic purpose.
They help the customer understand the product.
That is why showing products from different angles and explaining size and usage details is important.
Alternative texts for images should also be prepared properly.
Instead of stuffing alt texts with irrelevant keywords, describe what the image actually shows.
For example:
“50 ml men's Eau de Parfum in an amber glass bottle, front product view.”
This improves both accessibility and the clarity of product information.
10. Manage customer reviews properly
Real customer reviews can be an important reference in the purchase decision.
But credibility is essential here.
Producing fake reviews or presenting real reviews in a misleading way can damage brand trust in the long run.
Reviewing comments regularly and answering customers' questions is a healthier approach.
Recurring complaints about a product, in particular, can provide valuable information for category and product development teams.
The aim here is not just to look better, but to genuinely create a better customer experience.
Roadmap
11. Test your brand with real customer questions
To understand AI visibility, tests can be run at regular intervals using questions that reflect customer intent.
For example, for a cosmetics brand:
“Which perfume brands in Turkey offer good value for money?”
“Which perfumes are recommended for daily use?”
“What product features should people with sensitive skin look for?”
These tests can be repeated across different AI tools.
But it should be remembered that results may vary because of personalisation, location, model updates and response variability.
So the brand not being recommended in a single query does not prove a definite visibility problem.
Likewise, being recommended once does not mean lasting success.
Measurement needs to be systematic and comparable.
12. Connect visibility to sales performance
In the final stage, we come to the real commercial question.
How does this work affect the company's performance?
Organic search traffic.
Product page visits.
Conversion rate.
New customer acquisition.
Average order value.
Repeat purchase rate.
These are among the core indicators of digital performance.
Referrals from AI sources can also be tracked separately with suitable analytics tools.
But it should not be assumed that all AI interactions are fully visible within standard web analytics.
Data visibility may be limited, especially in discovery and purchase journeys that take place through third-party systems.
That is why brands need to focus not just on traffic growth, but on commercial outcomes.
Visibility is a tool. The goal is sustainable customer acquisition and profitable growth.
Conclusion
30-day implementation plan
You don't have to do all of the above at the same time.
For a more practical start, a four-week programme can be applied.
Week 1 — Digital visibility analysis
Evaluate current product pages, technical SEO issues, the consistency of brand information and product data quality.
Identify the gaps in your best-selling products and strategic categories.
Week 2 — Product and content optimisation
Improve the titles and descriptions of priority products.
Complete missing technical information.
Make the necessary structured data adjustments.
Improve category content according to user needs.
Week 3 — Search and AI tests
Review Google Search Console data.
Run AI-assisted search tests using real customer questions.
Compare how your brand and your competitors are represented.
Identify recurring information gaps.
Week 4 — Measurement and improvement
Check the first effects of the changes on indexing and visibility.
Monitor the conversion performance of product pages.
Set the priorities for the second month based on the findings.
The aim here is not to guarantee definite results in 30 days, but to start a sustainable optimisation process.
Frequently asked questions
How can I make my brand stand out in ChatGPT?
You can support your discoverability by presenting your brand's official information consistently, describing your products in detail and accurately, producing content that answers real user needs and improving technical accessibility. However, there is no guaranteed way to appear in a particular AI answer.
Will AI replace SEO?
While AI-assisted search experiences are growing, traditional SEO remains important. Technical accessibility, content quality, correctly structured data and user experience also matter for new forms of search.
Can products be bought through AI in Turkey?
The possibilities in this area vary by platform and country. For example, Google's current official documentation on certain UCP-supported checkout experiences covers eligible products and participating merchants in the US, Canada and Australia. So it should not be assumed that new features can be used in the same way in Turkey.
Is it mandatory to prepare an llms.txt file?
No. Google states that a special AI text file is not required to appear in AI-assisted search results. The priority should be quality content, a sound technical structure and up-to-date product information.
How are sales from AI searches measured?
Measurable referral traffic, conversions and new customer acquisition can be tracked with analytics tools. However, not every stage of an AI-assisted purchase journey can always be tracked directly. That is why channel data and controlled visibility tests should be evaluated together.
Conclusion: the SEO work of the future won't be just keyword management
For many years, digital marketing focused on understanding the words customers search for.
Now we face systems that interpret the needs customers express more comprehensively.
This change can create new opportunities for brands.
In particular, brands that have a strong product but cannot gain enough visibility in traditional advertising competition can become considered options in new discovery channels with the right digital information architecture and original content.
But new technology does not solve a brand's fundamental problems by itself.
If the product isn't right, if it doesn't deliver the value it promises to the customer or if the after-sales experience is inadequate, AI visibility alone will not create sustainable commercial success.
That is why companies need to think about SEO, content, product management and customer experience together.
Because in the coming period, the decisive question will not only be:
“What position are we on Google?”
This question will also gain importance:
“When the customer describes their need, is our brand considered one of the right options?”
Sources
Related reading
Let's strengthen your company's commercial decision and growth system together. Let's talk on WhatsApp or review the consulting approach.
Author: Gökhan Akdağ — Commercial Growth Architect; commercial growth, marketing and management consultant; founder of GA Consulting.
My Recent Posts
(Gökhan Akdağ)
©2026
What Is Marketing Consulting? How to Build a Marketing Strategy, Plan, Budget and Management Discipline
Oct 9, 2026
Marketing
What Is Retail Consulting? Store Management, Sales Growth, KPIs, Profitability and Retail Math
Oct 9, 2026
Retail
What Is Commercial Growth Consulting? How to Manage Sales, Marketing, B2B, Export, Organisation and Profitable Growth
Oct 9, 2026
Strategy
FAQ
01
What does GA Consulting do?
02
What is your approach?
03
How do projects progress?
04
What is your focus?
05
Which areas do you work in?
06
What value does it create for companies?
07
Which companies is it right for?
08
How long until a project delivers results?
Oct 19, 2026
How Does Your Brand Appear in ChatGPT and Gemini Shopping Recommendations?
A 12-step digital visibility guide for brands in the age of AI.
E-commerce
SEO
AI
Context
Visibility is a tool. The goal is sustainable customer acquisition and profitable growth.
When a consumer types “best men's perfumes” into Google, brands have been fighting for years to appear in the search results.
So what happens when the same consumer asks ChatGPT:
“Recommend five men's perfumes that suit an office environment, last long, aren't too heavy and offer good value for money.”
Would you want your brand to appear in the answer?
Of course.
But there is an important distinction here.
In traditional search engine optimisation, one of the core goals was to gain visibility for specific queries.
In AI-assisted product discovery, it also becomes important that the brand can be correctly associated with the customer's need.
That is why SEO work needs to be approached from a broader perspective.
First, let's separate two concepts.
SEO (Search Engine Optimization) covers work aimed at increasing visibility in search engines.
GEO (Generative Engine Optimization) is the approach of creating content that generative AI systems can discover, understand and represent reliably.
That said, it is not right to treat GEO as a new technique completely independent of SEO or one that produces guaranteed results.
Google's official statements published in 2026 also note that core SEO practices remain important for AI-assisted search features and that no special AI file or separate schema type is required.
So what should brands do?
Analysis
1. Don't introduce your products by their names alone
Imagine a product title on an e-commerce site looks like this:
“MEN'S PERFUME E-125 50 ML”
This title may be understandable inside the company.
But it does not sufficiently describe the customer's real need.
Which fragrance family does the product belong to?
Is it suitable for daily use?
How intense is it?
What settings is it designed for?
This information is important for understanding the product.
Instead of filling product descriptions with a few marketing adjectives, structure them around concrete features.
For example:
“A 50 ml men's Eau de Parfum with a woody, aromatic character, designed for daily wear.”
Of course, such statements must match the product's real features.
The aim is not to repeat keywords, but to explain clearly what the product offers.
2. Answer customer questions on product pages
Customers don't just want to learn product features.
They want to understand whether the product suits them.
That is why product pages should answer real, frequently asked customer questions.
For a perfume:
“What is the character of the scent?”
“Is it suitable for daily use?”
“Which fragrance notes does it contain?”
“What are the product's volume and concentration?”
For a clothing item:
“How does it fit?”
“What fabric is it made of?”
“What are the care instructions?”
“What conditions is the product suitable for?”
This information both improves the customer experience and can make it easier to associate the product with different search intents.
But producing hundreds of questions that are never actually asked, purely for search engines, is not right.
Content should be useful to the customer.
3. Use Product schema
Structured data should be used so that the information on product pages can be interpreted more clearly by search engines.
On e-commerce sites, one of the most important types of structured data is the Product schema.
Within this structure, fields such as product name, description, image, brand, price and availability can be included.
When the required conditions are met, this information can be used in Google's product-focused search experiences.
But adding structured data does not mean the product will definitely be shown in a particular result.
What matters is that the marked-up information matches what the customer sees on the product page.
Google's official Product and Offer documentation should be taken as the core reference here.
4. Keep your Google Merchant Center data up to date
Google Merchant Center is one of the core tools for presenting product information to Google's shopping ecosystem.
Consistency in product catalogues is especially important.
Price, stock status, product title, variant information and images must be managed correctly.
For example, a product that is out of stock on the product page but shows as in stock in the data feed can harm the customer experience.
Similarly, prices not matching across systems can cause problems.
That is why, instead of preparing product data once and leaving it, it should be checked regularly.
Up-to-date product data is not just SEO work.
It is also an indicator of the quality of commercial operations.
In Depth
5. Make your brand's digital identity consistent
If a brand is described with different information on different platforms, building a reliable and consistent digital identity can become difficult.
Core information should be consistent across the brand description on the corporate website, social media accounts, marketplace profiles and other official channels.
Which categories the brand operates in, which customer needs it meets and which features differentiate it should be explained clearly.
This distinction is especially important for companies that manufacture, offer private label services or have more than one sales channel.
Because the same company may have its own brand while also producing for other brands.
Defining these activities correctly online makes it easier to tell the brands apart.
6. Produce content that contains real expertise
In the world of AI-assisted search, producing content does not mean simply repeating certain words.
Original information, real experience and explanatory analysis matter.
Instead of only describing its products, a cosmetics brand could benefit from content that explains fragrance families, product selection criteria or usage habits.
A retail consultancy, on the other hand, should explain real commercial problems and its approach to solving them, rather than just listing the services it offers.
For example:
“Why does store conversion rate fall?”
“How can stock turnover be improved?”
“How is like-for-like sales growth analysed in retail?”
Content like this makes expertise visible while also answering potential customers' questions.
Especially in B2B services that require expertise, credibility must be built not only through advertising but through knowledge and experience.
7. Check technical accessibility
No matter how good the content on a website is, if search engines cannot access it, visibility problems can arise.
That is why technical SEO checks should not be neglected.
Robots.txt settings should be reviewed.
It should be confirmed that important pages are not accidentally blocked.
The sitemap should be kept up to date.
Canonical tags should be checked.
The mobile experience of pages should be evaluated.
It is also important that product and content information does not remain only inside complex visual components, but is presented in appropriate text fields.
Additional files such as llms.txt can be considered optionally. But using them does not guarantee visibility in AI systems and does not replace core SEO work.
8. Improve your category pages
In e-commerce, category pages are often designed simply as areas where products are listed.
Yet a well-prepared category page can make the purchase decision easier.
For example, instead of only showing products in a “Men's Perfumes” category, scent characters, purposes of use and selection criteria can be explained.
Similarly, in a “Premium Women's Clothing” category, the material features, collection approach or areas of use of the products can be described.
This content should provide real information to the user and should not make the product-listing experience harder.
The aim is not to fill the page with text.
It is to help the customer choose the right product more easily.
9. Make product images part of the information architecture
Product images do not serve only an aesthetic purpose.
They help the customer understand the product.
That is why showing products from different angles and explaining size and usage details is important.
Alternative texts for images should also be prepared properly.
Instead of stuffing alt texts with irrelevant keywords, describe what the image actually shows.
For example:
“50 ml men's Eau de Parfum in an amber glass bottle, front product view.”
This improves both accessibility and the clarity of product information.
10. Manage customer reviews properly
Real customer reviews can be an important reference in the purchase decision.
But credibility is essential here.
Producing fake reviews or presenting real reviews in a misleading way can damage brand trust in the long run.
Reviewing comments regularly and answering customers' questions is a healthier approach.
Recurring complaints about a product, in particular, can provide valuable information for category and product development teams.
The aim here is not just to look better, but to genuinely create a better customer experience.
Roadmap
11. Test your brand with real customer questions
To understand AI visibility, tests can be run at regular intervals using questions that reflect customer intent.
For example, for a cosmetics brand:
“Which perfume brands in Turkey offer good value for money?”
“Which perfumes are recommended for daily use?”
“What product features should people with sensitive skin look for?”
These tests can be repeated across different AI tools.
But it should be remembered that results may vary because of personalisation, location, model updates and response variability.
So the brand not being recommended in a single query does not prove a definite visibility problem.
Likewise, being recommended once does not mean lasting success.
Measurement needs to be systematic and comparable.
12. Connect visibility to sales performance
In the final stage, we come to the real commercial question.
How does this work affect the company's performance?
Organic search traffic.
Product page visits.
Conversion rate.
New customer acquisition.
Average order value.
Repeat purchase rate.
These are among the core indicators of digital performance.
Referrals from AI sources can also be tracked separately with suitable analytics tools.
But it should not be assumed that all AI interactions are fully visible within standard web analytics.
Data visibility may be limited, especially in discovery and purchase journeys that take place through third-party systems.
That is why brands need to focus not just on traffic growth, but on commercial outcomes.
Visibility is a tool. The goal is sustainable customer acquisition and profitable growth.
Conclusion
30-day implementation plan
You don't have to do all of the above at the same time.
For a more practical start, a four-week programme can be applied.
Week 1 — Digital visibility analysis
Evaluate current product pages, technical SEO issues, the consistency of brand information and product data quality.
Identify the gaps in your best-selling products and strategic categories.
Week 2 — Product and content optimisation
Improve the titles and descriptions of priority products.
Complete missing technical information.
Make the necessary structured data adjustments.
Improve category content according to user needs.
Week 3 — Search and AI tests
Review Google Search Console data.
Run AI-assisted search tests using real customer questions.
Compare how your brand and your competitors are represented.
Identify recurring information gaps.
Week 4 — Measurement and improvement
Check the first effects of the changes on indexing and visibility.
Monitor the conversion performance of product pages.
Set the priorities for the second month based on the findings.
The aim here is not to guarantee definite results in 30 days, but to start a sustainable optimisation process.
Frequently asked questions
How can I make my brand stand out in ChatGPT?
You can support your discoverability by presenting your brand's official information consistently, describing your products in detail and accurately, producing content that answers real user needs and improving technical accessibility. However, there is no guaranteed way to appear in a particular AI answer.
Will AI replace SEO?
While AI-assisted search experiences are growing, traditional SEO remains important. Technical accessibility, content quality, correctly structured data and user experience also matter for new forms of search.
Can products be bought through AI in Turkey?
The possibilities in this area vary by platform and country. For example, Google's current official documentation on certain UCP-supported checkout experiences covers eligible products and participating merchants in the US, Canada and Australia. So it should not be assumed that new features can be used in the same way in Turkey.
Is it mandatory to prepare an llms.txt file?
No. Google states that a special AI text file is not required to appear in AI-assisted search results. The priority should be quality content, a sound technical structure and up-to-date product information.
How are sales from AI searches measured?
Measurable referral traffic, conversions and new customer acquisition can be tracked with analytics tools. However, not every stage of an AI-assisted purchase journey can always be tracked directly. That is why channel data and controlled visibility tests should be evaluated together.
Conclusion: the SEO work of the future won't be just keyword management
For many years, digital marketing focused on understanding the words customers search for.
Now we face systems that interpret the needs customers express more comprehensively.
This change can create new opportunities for brands.
In particular, brands that have a strong product but cannot gain enough visibility in traditional advertising competition can become considered options in new discovery channels with the right digital information architecture and original content.
But new technology does not solve a brand's fundamental problems by itself.
If the product isn't right, if it doesn't deliver the value it promises to the customer or if the after-sales experience is inadequate, AI visibility alone will not create sustainable commercial success.
That is why companies need to think about SEO, content, product management and customer experience together.
Because in the coming period, the decisive question will not only be:
“What position are we on Google?”
This question will also gain importance:
“When the customer describes their need, is our brand considered one of the right options?”
Sources
Related reading
Let's strengthen your company's commercial decision and growth system together. Let's talk on WhatsApp or review the consulting approach.
Author: Gökhan Akdağ — Commercial Growth Architect; commercial growth, marketing and management consultant; founder of GA Consulting.
My Recent Posts
(Gökhan Akdağ)
©2026
What Is Marketing Consulting? How to Build a Marketing Strategy, Plan, Budget and Management Discipline
Oct 9, 2026
Marketing
What Is Retail Consulting? Store Management, Sales Growth, KPIs, Profitability and Retail Math
Oct 9, 2026
Retail
What Is Commercial Growth Consulting? How to Manage Sales, Marketing, B2B, Export, Organisation and Profitable Growth
Oct 9, 2026
Strategy
FAQ
01
What does GA Consulting do?
02
What is your approach?
03
How do projects progress?
04
What is your focus?
05
Which areas do you work in?
06
What value does it create for companies?
07
Which companies is it right for?
08
How long until a project delivers results?
Oct 19, 2026
How Does Your Brand Appear in ChatGPT and Gemini Shopping Recommendations?
A 12-step digital visibility guide for brands in the age of AI.
E-commerce
SEO
AI
Context
Visibility is a tool. The goal is sustainable customer acquisition and profitable growth.
When a consumer types “best men's perfumes” into Google, brands have been fighting for years to appear in the search results.
So what happens when the same consumer asks ChatGPT:
“Recommend five men's perfumes that suit an office environment, last long, aren't too heavy and offer good value for money.”
Would you want your brand to appear in the answer?
Of course.
But there is an important distinction here.
In traditional search engine optimisation, one of the core goals was to gain visibility for specific queries.
In AI-assisted product discovery, it also becomes important that the brand can be correctly associated with the customer's need.
That is why SEO work needs to be approached from a broader perspective.
First, let's separate two concepts.
SEO (Search Engine Optimization) covers work aimed at increasing visibility in search engines.
GEO (Generative Engine Optimization) is the approach of creating content that generative AI systems can discover, understand and represent reliably.
That said, it is not right to treat GEO as a new technique completely independent of SEO or one that produces guaranteed results.
Google's official statements published in 2026 also note that core SEO practices remain important for AI-assisted search features and that no special AI file or separate schema type is required.
So what should brands do?
Analysis
1. Don't introduce your products by their names alone
Imagine a product title on an e-commerce site looks like this:
“MEN'S PERFUME E-125 50 ML”
This title may be understandable inside the company.
But it does not sufficiently describe the customer's real need.
Which fragrance family does the product belong to?
Is it suitable for daily use?
How intense is it?
What settings is it designed for?
This information is important for understanding the product.
Instead of filling product descriptions with a few marketing adjectives, structure them around concrete features.
For example:
“A 50 ml men's Eau de Parfum with a woody, aromatic character, designed for daily wear.”
Of course, such statements must match the product's real features.
The aim is not to repeat keywords, but to explain clearly what the product offers.
2. Answer customer questions on product pages
Customers don't just want to learn product features.
They want to understand whether the product suits them.
That is why product pages should answer real, frequently asked customer questions.
For a perfume:
“What is the character of the scent?”
“Is it suitable for daily use?”
“Which fragrance notes does it contain?”
“What are the product's volume and concentration?”
For a clothing item:
“How does it fit?”
“What fabric is it made of?”
“What are the care instructions?”
“What conditions is the product suitable for?”
This information both improves the customer experience and can make it easier to associate the product with different search intents.
But producing hundreds of questions that are never actually asked, purely for search engines, is not right.
Content should be useful to the customer.
3. Use Product schema
Structured data should be used so that the information on product pages can be interpreted more clearly by search engines.
On e-commerce sites, one of the most important types of structured data is the Product schema.
Within this structure, fields such as product name, description, image, brand, price and availability can be included.
When the required conditions are met, this information can be used in Google's product-focused search experiences.
But adding structured data does not mean the product will definitely be shown in a particular result.
What matters is that the marked-up information matches what the customer sees on the product page.
Google's official Product and Offer documentation should be taken as the core reference here.
4. Keep your Google Merchant Center data up to date
Google Merchant Center is one of the core tools for presenting product information to Google's shopping ecosystem.
Consistency in product catalogues is especially important.
Price, stock status, product title, variant information and images must be managed correctly.
For example, a product that is out of stock on the product page but shows as in stock in the data feed can harm the customer experience.
Similarly, prices not matching across systems can cause problems.
That is why, instead of preparing product data once and leaving it, it should be checked regularly.
Up-to-date product data is not just SEO work.
It is also an indicator of the quality of commercial operations.
In Depth
5. Make your brand's digital identity consistent
If a brand is described with different information on different platforms, building a reliable and consistent digital identity can become difficult.
Core information should be consistent across the brand description on the corporate website, social media accounts, marketplace profiles and other official channels.
Which categories the brand operates in, which customer needs it meets and which features differentiate it should be explained clearly.
This distinction is especially important for companies that manufacture, offer private label services or have more than one sales channel.
Because the same company may have its own brand while also producing for other brands.
Defining these activities correctly online makes it easier to tell the brands apart.
6. Produce content that contains real expertise
In the world of AI-assisted search, producing content does not mean simply repeating certain words.
Original information, real experience and explanatory analysis matter.
Instead of only describing its products, a cosmetics brand could benefit from content that explains fragrance families, product selection criteria or usage habits.
A retail consultancy, on the other hand, should explain real commercial problems and its approach to solving them, rather than just listing the services it offers.
For example:
“Why does store conversion rate fall?”
“How can stock turnover be improved?”
“How is like-for-like sales growth analysed in retail?”
Content like this makes expertise visible while also answering potential customers' questions.
Especially in B2B services that require expertise, credibility must be built not only through advertising but through knowledge and experience.
7. Check technical accessibility
No matter how good the content on a website is, if search engines cannot access it, visibility problems can arise.
That is why technical SEO checks should not be neglected.
Robots.txt settings should be reviewed.
It should be confirmed that important pages are not accidentally blocked.
The sitemap should be kept up to date.
Canonical tags should be checked.
The mobile experience of pages should be evaluated.
It is also important that product and content information does not remain only inside complex visual components, but is presented in appropriate text fields.
Additional files such as llms.txt can be considered optionally. But using them does not guarantee visibility in AI systems and does not replace core SEO work.
8. Improve your category pages
In e-commerce, category pages are often designed simply as areas where products are listed.
Yet a well-prepared category page can make the purchase decision easier.
For example, instead of only showing products in a “Men's Perfumes” category, scent characters, purposes of use and selection criteria can be explained.
Similarly, in a “Premium Women's Clothing” category, the material features, collection approach or areas of use of the products can be described.
This content should provide real information to the user and should not make the product-listing experience harder.
The aim is not to fill the page with text.
It is to help the customer choose the right product more easily.
9. Make product images part of the information architecture
Product images do not serve only an aesthetic purpose.
They help the customer understand the product.
That is why showing products from different angles and explaining size and usage details is important.
Alternative texts for images should also be prepared properly.
Instead of stuffing alt texts with irrelevant keywords, describe what the image actually shows.
For example:
“50 ml men's Eau de Parfum in an amber glass bottle, front product view.”
This improves both accessibility and the clarity of product information.
10. Manage customer reviews properly
Real customer reviews can be an important reference in the purchase decision.
But credibility is essential here.
Producing fake reviews or presenting real reviews in a misleading way can damage brand trust in the long run.
Reviewing comments regularly and answering customers' questions is a healthier approach.
Recurring complaints about a product, in particular, can provide valuable information for category and product development teams.
The aim here is not just to look better, but to genuinely create a better customer experience.
Roadmap
11. Test your brand with real customer questions
To understand AI visibility, tests can be run at regular intervals using questions that reflect customer intent.
For example, for a cosmetics brand:
“Which perfume brands in Turkey offer good value for money?”
“Which perfumes are recommended for daily use?”
“What product features should people with sensitive skin look for?”
These tests can be repeated across different AI tools.
But it should be remembered that results may vary because of personalisation, location, model updates and response variability.
So the brand not being recommended in a single query does not prove a definite visibility problem.
Likewise, being recommended once does not mean lasting success.
Measurement needs to be systematic and comparable.
12. Connect visibility to sales performance
In the final stage, we come to the real commercial question.
How does this work affect the company's performance?
Organic search traffic.
Product page visits.
Conversion rate.
New customer acquisition.
Average order value.
Repeat purchase rate.
These are among the core indicators of digital performance.
Referrals from AI sources can also be tracked separately with suitable analytics tools.
But it should not be assumed that all AI interactions are fully visible within standard web analytics.
Data visibility may be limited, especially in discovery and purchase journeys that take place through third-party systems.
That is why brands need to focus not just on traffic growth, but on commercial outcomes.
Visibility is a tool. The goal is sustainable customer acquisition and profitable growth.
Conclusion
30-day implementation plan
You don't have to do all of the above at the same time.
For a more practical start, a four-week programme can be applied.
Week 1 — Digital visibility analysis
Evaluate current product pages, technical SEO issues, the consistency of brand information and product data quality.
Identify the gaps in your best-selling products and strategic categories.
Week 2 — Product and content optimisation
Improve the titles and descriptions of priority products.
Complete missing technical information.
Make the necessary structured data adjustments.
Improve category content according to user needs.
Week 3 — Search and AI tests
Review Google Search Console data.
Run AI-assisted search tests using real customer questions.
Compare how your brand and your competitors are represented.
Identify recurring information gaps.
Week 4 — Measurement and improvement
Check the first effects of the changes on indexing and visibility.
Monitor the conversion performance of product pages.
Set the priorities for the second month based on the findings.
The aim here is not to guarantee definite results in 30 days, but to start a sustainable optimisation process.
Frequently asked questions
How can I make my brand stand out in ChatGPT?
You can support your discoverability by presenting your brand's official information consistently, describing your products in detail and accurately, producing content that answers real user needs and improving technical accessibility. However, there is no guaranteed way to appear in a particular AI answer.
Will AI replace SEO?
While AI-assisted search experiences are growing, traditional SEO remains important. Technical accessibility, content quality, correctly structured data and user experience also matter for new forms of search.
Can products be bought through AI in Turkey?
The possibilities in this area vary by platform and country. For example, Google's current official documentation on certain UCP-supported checkout experiences covers eligible products and participating merchants in the US, Canada and Australia. So it should not be assumed that new features can be used in the same way in Turkey.
Is it mandatory to prepare an llms.txt file?
No. Google states that a special AI text file is not required to appear in AI-assisted search results. The priority should be quality content, a sound technical structure and up-to-date product information.
How are sales from AI searches measured?
Measurable referral traffic, conversions and new customer acquisition can be tracked with analytics tools. However, not every stage of an AI-assisted purchase journey can always be tracked directly. That is why channel data and controlled visibility tests should be evaluated together.
Conclusion: the SEO work of the future won't be just keyword management
For many years, digital marketing focused on understanding the words customers search for.
Now we face systems that interpret the needs customers express more comprehensively.
This change can create new opportunities for brands.
In particular, brands that have a strong product but cannot gain enough visibility in traditional advertising competition can become considered options in new discovery channels with the right digital information architecture and original content.
But new technology does not solve a brand's fundamental problems by itself.
If the product isn't right, if it doesn't deliver the value it promises to the customer or if the after-sales experience is inadequate, AI visibility alone will not create sustainable commercial success.
That is why companies need to think about SEO, content, product management and customer experience together.
Because in the coming period, the decisive question will not only be:
“What position are we on Google?”
This question will also gain importance:
“When the customer describes their need, is our brand considered one of the right options?”
Sources
Related reading
Let's strengthen your company's commercial decision and growth system together. Let's talk on WhatsApp or review the consulting approach.
Author: Gökhan Akdağ — Commercial Growth Architect; commercial growth, marketing and management consultant; founder of GA Consulting.
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