A Reddit user recently asked a question that more consumer technology CMOs should probably be asking:
How can I get my company mentioned in ChatGPT answers and Google AI Overviews?
The Reddit discussion touches on Wikipedia, structured data, blog content, press coverage, directories, SEO and llms.txt.
There is some good advice in the thread. There is also plenty that oversimplifies how AI search visibility actually works.
For a growth-stage consumer technology company, the bigger question is:
How do you optimize PR and content for AI search visibility in consumer tech?
The short answer is to make your brand and products easy to understand, create genuinely useful content around the questions consumers ask, build independent authority through earned media and measure whether those signals translate into citations, mentions and recommendations.
This requires PR, content, SEO and Generative Engine Optimization to work together.
Here is how we approach it.
1. The Reddit thread gets the fundamental question right
The most useful part of the Reddit discussion is the question itself.
How does a company become part of an AI-generated answer?
Several commenters recommend creating clear content around the questions customers ask, strengthening SEO, earning third-party coverage and examining which sources AI platforms already cite.
Those are sensible starting points.
The important distinction for consumer technology companies is that AI search is highly contextual.
Someone searching Google for “robot vacuum” may be at a very different point in the buying process from someone asking:
“What is the best robot vacuum for a two-storey house with a dog?”
The second query contains the buyer’s problem, product category, environment and an implied set of evaluation criteria.
That creates a different kind of search environment.
Research from Pew Research Center found that longer and question-based Google searches were considerably more likely to produce AI summaries. In its March 2025 dataset, 60% of searches beginning with question words generated an AI summary, while 53% of searches containing 10 or more words did so.
That matters for consumer tech because product research naturally produces these kinds of detailed questions.
The fix: Build a prompt universe around the problems, categories, comparisons, features and purchasing decisions that matter to your customers. Then establish whether your brand appears today.
Our GEO Buyer Journey framework provides one way to organize those prompts across the entire customer journey.
2. Be skeptical of GEO shortcuts
This is where the Reddit discussion becomes more complicated.
Several commenters recommend llms.txt. Others focus heavily on schema or individual technical tactics.
Google’s own guidance is much less exotic.
According to Google Search Central’s guidance for AI features, there are no additional technical requirements for appearing in AI Overviews or AI Mode beyond the requirements for appearing in Google Search.
Google specifically says publishers do not need to create new machine-readable AI files or special schema to appear in these experiences.
Instead, Google points back to fundamentals including crawlability, internal linking, page experience, textual content, accurate structured data and useful information.
That should temper some of the more enthusiastic GEO advice circulating online.
Technical accessibility matters. It simply does not give Google a reason to cite you.
Google reinforced this in May 2026 when it published additional guidance emphasizing valuable, unique and non-commodity content for generative search.
For a CMO, that is the more important takeaway.
The fix: Get the technical foundation right, but do not mistake technical accessibility for authority.
3. Build a foundation AI systems can understand
Before producing another 50 blog posts, make sure the basic facts surrounding the company and its products are clear.
For consumer technology companies, we look at five areas:
Company: What does the company make? Where does it operate? Which category does it belong to?
Products: What are the primary products, specifications, features, prices and use cases?
Category: What established product category does the company compete within?
Differentiators: What legitimately separates the product from alternatives?
Evidence: What reviews, testing, awards, research or independent reporting substantiate those claims?
The answers should be reasonably consistent across your website, retailer listings, product feeds, media materials and important third-party sources.
You are creating an understandable information environment around the company.
Google recommends making important information available in textual form, ensuring pages are internally discoverable and keeping structured data consistent with the content users actually see.
For consumer technology brands, that last point is particularly important. Specifications change. Prices change. Products get replaced. Features are added through software updates.
Outdated information can easily become part of the AI search environment.
The fix: Audit how your company, products, specifications and positioning are represented across owned and important third-party sources. Correct contradictions and fill obvious information gaps.
For a broader look at how we structure this work, see our guide to AI Search and GEO for technology brands.
4. Stop building the content strategy around keywords alone
Traditional keyword research still matters.
We add another layer: prompt research.
Think about the questions consumers ask before buying your type of product.
They tend to move through several recognizable stages:
| Stage | Example consumer question | What the brand needs |
| Education | What is a mechanical keyboard? | Educational authority |
| Discovery | What are the best mechanical keyboard brands? | Brand visibility |
| Evaluation | Keychron vs Logitech for Mac? | Competitive context |
| Validation | Is Keychron reliable? | Independent evidence |
| Purchase | Best mechanical keyboard under $150? | Recommendation visibility |
| Post-purchase | How do I remap my Keychron keyboard? | Useful support content |
This produces a much more useful communications map than a spreadsheet containing hundreds of loosely related keywords.
We explore this more deeply in our GEO Buyer Journey, which looks at AI search across education, discovery, evaluation, validation, purchase and post-purchase use.
The objective is to understand where AI enters the buying decision and what information the customer needs at each stage.
The fix: Create a prompt map covering the full purchase journey. Establish your current visibility before deciding what content to create.
5. Create information worth citing
This is where content strategy becomes important.
Google’s 2026 guidance for generative search specifically emphasizes unique, valuable and non-commodity content.
That should change the content brief.
For consumer technology companies, citation-worthy information can include:
- Original research
- Product testing
- Technical explainers
- Buying guides
- Comparison tables
- Proprietary data
- Surveys
- Benchmarks
- Expert commentary
- Detailed FAQs
- Original images and video
- Clearly documented methodologies
A generic article called “The Ultimate Guide to Smart Home Technology” probably adds very little to the information already available online.
A controlled study testing the battery performance of 15 smart-home devices under identical conditions creates new information.
That distinction matters.
Recent academic research into citation behaviour across ChatGPT, Google and Perplexity also points toward the value of structured, semantically relevant pages containing extractable evidence such as definitions, numerical facts, comparisons and procedural information.
That does not mean every page needs to become an academic paper.
It means you need to give an AI system something useful to extract.
The fix: Before approving a content brief, ask: What information does this page contribute that does not already exist in the search results?
If the answer is nothing, reconsider the brief.
6. Structure content so Google can extract the answer
Good information can still be presented badly.
If your goal includes visibility in Google AI Overviews, important answers should not be buried under 800 words of throat-clearing.
Make the information easy to find.
Use:
Descriptive headings. Tell the reader exactly what the section answers.
Direct answers. Answer important questions near the beginning of the relevant section.
Tables. Use them for genuine comparisons, criteria and structured data.
Lists. Use them for processes and clearly defined groups.
Definitions. Explain terminology directly.
Evidence. Put credible sources beside the claims they support.
Consistent terminology. Do not describe the same product, category or technology five different ways across your website.
There is an interesting piece of supporting evidence here.
Pew found that 88% of the Google AI summaries in its study cited three or more sources.
AI Overviews are therefore often synthesizing information rather than simply choosing one page and reproducing it.
Your job is to make your information a useful component of that synthesis.
The fix: Review high-value pages and determine whether someone can quickly identify the question, answer and supporting evidence.
7. PR is part of the AI search strategy
This is where we would push the Reddit discussion much further.
A company can publish endless information about itself.
It remains information published by the company about itself.
Consumer technology purchasing decisions frequently rely on independent validation.
Reviews, product tests, comparisons, buying guides, interviews and news coverage create third-party evidence around a product.
This makes PR increasingly relevant to AI search.
We discuss this extensively in Why PR Is the Engine Behind AI Search Visibility.
Consider a keyboard company claiming:
“Our keyboard is one of the best keyboards for Mac users.”
That is marketing.
Now imagine that reputable technology publications independently review the keyboard, discuss its Mac compatibility and include it in relevant buying guides.
The proposition now exists independently of the brand.
That is a much more useful information environment.
This is why consumer technology PR should now consider more than the direct readership of a media placement.
We increasingly ask:
Does this publication have authority around our topic?
Does the article associate the brand with a category we need to own?
Does it validate an important product claim?
Does the page rank for relevant searches?
Does it appear as a citation across important AI prompts?
The media placement still has an audience.
It can now have a machine audience too.
The fix: Add AI citation relevance to media planning. Determine which publications repeatedly appear as sources for your priority prompts and incorporate those insights into outreach.
We maintain a data-backed list of technology media frequently appearing in AI citations for exactly this reason.
8. Give journalists something they can validate
This also changes the PR brief.
Another product announcement is rarely enough to establish meaningful category authority.
Consumer technology brands should create evidence journalists can investigate, test and reference.
That could include:
- Review units
- Independent product testing
- Performance benchmarks
- Original company data
- Customer research
- Expert access
- Product demonstrations
- Transparent technical specifications
- Useful category research
The stronger the evidence, the easier it becomes for journalists to produce substantive coverage.
That coverage creates independent information about the product outside the company’s own website.
For product launches specifically, this means thinking beyond launch-day coverage. Reviews, buying guides, creator content and useful post-launch media can continue influencing discovery long after the announcement itself.
We explain that process in our complete PR guide to launching a consumer tech product.
The fix: Before deciding what you want journalists to say, ask what you can prove, demonstrate, test or quantify.
9. Connect PR and content instead of running them separately
Many growth-stage companies still separate PR, SEO and content into different operational silos.
That creates unnecessary gaps.
Your PR team learns which questions journalists repeatedly ask.
Your SEO team sees what people search.
Customer service knows what buyers are confused about.
Sales knows which objections keep appearing.
Product knows which features require explanation.
Your GEO program should connect those signals.
If journalists repeatedly ask whether a smart-home product works with Apple HomeKit, for example, that question could produce:
- A clear answer on the product page.
- A detailed compatibility resource.
- Inclusion in reviewer materials.
- Outreach to relevant smart-home journalists.
- Monitoring across relevant AI prompts.
One recurring question now influences owned content, earned media and AI-search measurement.
That is a considerably more efficient communications system.
The fix: Maintain one shared list of priority topics and prompts across PR, content, SEO and product marketing.
10. Understand which sources actually matter to your brand
There is a temptation in GEO to find a universal list of websites that AI systems like.
Reddit.
Wikipedia.
Forbes.
YouTube.
Certain media publications.
There is some aggregate evidence for these patterns. Pew, for example, found Wikipedia, YouTube and Reddit among the most frequently cited sources in its study of Google AI summaries.
But aggregate citation data only gets you so far.
Your citation environment is determined by your category and your prompts.
A mechanical keyboard company can have a completely different citation ecosystem from an e-bike company or a smart-home security brand.
That is why we argue in What We Believe About Generative Engine Optimization that brands should examine their own prompt-level citation data rather than blindly applying aggregate GEO statistics.
Search your priority prompts.
Record the sources.
Identify which domains appear repeatedly.
Then investigate why.
You may find major technology publications. You may also find niche review sites, Reddit threads, retailer pages, specialist blogs and sources you have never encountered before.
Those findings should influence both your content and PR strategy.
The fix: Build a citation map for your actual prompt universe rather than relying exclusively on generic lists of websites that AI platforms supposedly prefer.
11. Measure AI visibility as a communications outcome
Occasionally searching ChatGPT for your company name is not measurement.
You need a repeatable prompt set.
For consumer technology brands, we typically look at:
Share of Answer: How frequently does your brand appear across relevant prompts compared with competitors?
Brand Citation Rate: How frequently are your owned properties or brand-related sources cited?
Prompt Coverage: Across how many strategically important questions does the brand appear?
Product Position: Where does the product appear within recommendations and comparisons?
Citation Sources: Which publications and websites are influencing the answers?
Recommendation Accuracy: Are the features, prices, positioning and product details accurate?
These metrics become meaningful when tracked over time.
A company moving from appearing across 8% of relevant discovery prompts to 24% tells us something useful.
One flattering ChatGPT screenshot does not.
We applied this approach to ourselves beginning in 2025. Our Proper Propaganda GEO case study documents how we defined a prompt universe, established a baseline and then used content, technical work and external authority-building to improve our own AI search presence.
The fix: Establish your baseline before doing the work. Keep the core prompt set, competitors and measurement methodology consistent enough to identify actual movement.
12. Use a six-part GEO framework
For a growth-stage consumer technology company, we organize this work into six stages.
1. Audit: Understand how customers use AI and where your brand currently stands.
2. Strategy: Determine the prompts, audiences, competitors and topics you need to win.
3. Foundation: Make your website and brand information easy for AI and search systems to understand.
4. Content: Create useful, authoritative and citation-worthy information.
5. Authority: Build external signals that increase trust in the brand.
6. Measurement: Track performance and use those insights to continuously improve the program.
The order matters.
Publishing content before understanding the prompts can produce a lot of content nobody needs.
Running PR without understanding the citation environment can generate coverage in places that have little influence on the questions you care about.
Measuring without establishing a baseline makes it difficult to know whether anything changed.
The framework gives each activity a reason to exist.
13. So, how do you optimize PR and content for AI search visibility in consumer tech?
Start with the questions consumers ask when researching your category. Make sure Google and other search systems can access and understand accurate information about your products. Create original content that directly answers those questions with useful evidence. Earn credible third-party coverage that independently validates the brand and its products. Then measure whether those signals translate into citations, mentions and recommendations across the prompts that influence purchasing decisions.
The Reddit thread gets the fundamental question right.
Where we would push the conversation further is the assumption that there is one tactic that gets a company “into ChatGPT” or Google AI Overviews.
There isn’t.
Google itself says there is no special AI markup required for AI Overviews. Research into AI citations suggests structured, relevant and evidence-rich information matters. Our own work shows that the sources influencing answers vary considerably by company, category and prompt.
For consumer technology brands, PR creates independent authority. Content creates depth. SEO creates discoverability. GEO connects and measures the system.
For a growth-stage CMO, that is the bigger opportunity.
AI search visibility should not sit in a separate experimental bucket.
It should become part of how the company manages discovery, reputation and demand.