We tested whether self‑promotional “best” pages get surfaced as sources and recommendations in ChatGPT responses. The study examined 26,283 source URLs and model answers across 750 top‑of‑funnel prompts to see what patterns repeat.
Why this matters in India: marketers chasing early‑funnel demand need to know if list pages help their brand appear in conversational search results, not just organic rankings.
Across 60,000+ tracked sites, ChatGPT sent 8–9x the referral traffic of the next platform, Perplexity. Sam Altman reports 800M+ weekly users, so appearing in responses can sway discovery at scale.
This article is a data‑backed, long‑form analysis — what we saw most often, which signals correlate with being cited, and a practical publishing playbook. We compare mentions and citations in model answers to classic search outcomes like rankings and clicks.
Note the limits: the data shows correlation patterns, not guaranteed causation for every market or brand. Our throughline: “best X” pages appear disproportionately in model sources, and freshness plus structured, extractable content influences reuse.
Trust tension: self‑rankings can increase being cited, but poorly executed lists can hurt credibility, especially in competitive B2B categories in India.
Key Takeaways
- Data set: 750 prompts and 26,283 source URLs reveal repeat patterns in model mentions.
- “Best” pages show up often as sources, but format and freshness matter more than blunt promotion.
- Appearances in responses differ from organic search rankings and clicks; treat them as a separate channel.
- Well‑structured, extractable content raises the chance of being reused in answers.
- Poorly supported rankings can boost citations short‑term while harming long‑term trust, especially in B2B India.
Why AI Search Visibility Matters Now for Brands in India
ChatGPT drives far more downstream clicks than other conversational platforms, making it a primary referral source for many sites. This shift matters because Indian buyers often begin discovery inside chat interfaces and answer engines, then shortlist vendors before clicking through.
Referral impact: across 60,000+ tracked sites, ChatGPT sent 8–9x the referral traffic of the next platform, Perplexity. Sam Altman has said the service sees 800M+ weekly users, which amplifies the importance of being cited in conversational answers.
How search behavior is changing: classic search returns multiple links for comparison. Chat responses usually give a single synthesized answer and name a short set of brands. If you are not cited, you can be effectively invisible to the buyer at first touch.
Operational implications for brands
Indian brands need both classic SEO and structured content systems. Measurement tools, update workflows, and structured pages help ensure accurate facts show up when a model cites you. Track mentions and the factual details models output about pricing, features, and positioning.
| Metric | Chat-based engine | Other answer engine | Practical action |
|---|---|---|---|
| Average referral multiple | 8–9x | 1x | Prioritize chat-format testing |
| Weekly users (reported) | 800M+ | — | Measure downstream traffic |
| Buyer experience | Synthesized citation | Multi-link results | Publish structured, extractable content |
“Appearances in answers function like a new kind of top‑of‑funnel authority.”
Next: we will define what counts as a list page that models draw from, show sourcing patterns, and outline publishing approaches that protect credibility while capturing this new channel.
What Counts as a “Self‑Promotional Best List” (and Why Models Source Them)
Definition: a “best X” page on a brand’s own site that ranks options and includes that brand among top entries. These pages are framed as comparison resources and often state why an option is “best for” a use case.
Blog listicles are editorial posts with brief reviews, pros, and cons. They explain choices in paragraph form and often include methodology notes.
Non‑blog platforms like G2 and Clutch are directory-style pages with standardized records, ratings, and filters. Their structured entries make it simple to extract names, features, and scores.
First‑party vs third‑party citations
First‑party citation means the brand’s own page is cited as evidence for a recommendation. Third‑party citation is when an aggregator, publisher, or directory is used to justify a claim.
Both types appear in model responses, but first‑party pages must show clear methodology and balanced comparison to avoid looking like pure marketing.
Where these pages sit in the buyer journey
“Best X” pages map to top and mid funnel intent: users want shortlists, trade‑offs, and “best for” context. That matches how models synthesize answers—concise recommendations with a rationale.
“Structured, scannable comparison content is more likely to be reused in concise responses.”
- Why models source them: they contain entity‑rich names, short justifications, and consistent headings that are easy to extract.
- Risk: lists that lack methodology or neutral links can register as biased and harm trust, especially in competitive Indian B2B categories.
- Practical angle: design the page for both humans and machines: clear headings, short bullets, and explicit “best for” blurbs.
Study Design: How 750 Prompts and 26,283 Source URLs Were Analyzed
We built a controlled prompt set to mirror real-world research queries and then traced which pages models used as sources.
The prompt bank included 750 top‑of‑funnel queries across software, consumer and industrial products, and agency recommendations. This mirrors how buyers in India search and shortlist options.
Tagging and validation
We analyzed 26,283 source URLs. Over 10,000 third‑party URLs were classified via semi‑automated filters and a GPT‑5 classifier with custom instructions. Human spot checks pushed overall tagging accuracy to ~95%.
Why page types, not domains
The analytical unit was the page: blog list, landing page, product page, documentation, social posts, etc. Page format shapes extraction by retrieval systems and affects how models form responses more than domain rank alone.
Freshness rules and implications
From a clean subset of 1,100 pages with clear timestamps, 79.1% were updated in 2025, 26% in the past two months, and 57.1% had post‑publication updates. That time‑based signal matters for search and for repeatable SEO tactics.
Method takeaway: the approach surfaces practical insights about format, freshness, and structure that marketers can act on.
What the Data Shows About Self‑promotional lists & AI visibility
Across categories, short, structured comparison posts surfaced repeatedly as evidence in model responses.
Headline finding: recently updated “best X” pages were the single most prominent page type cited for top‑of‑funnel recommendation prompts. These pages show up as supporting links in synthesized answers and often appear alongside other sources.
How prominence works in practice
Prominent means models reuse the page to justify a suggestion. That reuse can look like a direct mention or a supporting citation in the answer.
Ranking correlation and position bias
We found a clear correlation: brands ranked higher in third‑party comparison lists were more likely to receive mentions in responses. Position matters beyond mere inclusion.
- The study hand‑checked 250 “best X” blog lists per category (750 total).
- To avoid overstatement, we normalized by top/middle/bottom thirds.
- Even after normalization, top‑third entries had more citations, suggesting models favor earlier placements or extract earlier segments.
Longer lists dilute the effect
When a list had 10 or more items the trend weakened but remained directionally similar. Longer lists appear to dilute position advantage while preserving some correlation with ranking.
“Publishers that earn higher placement in third‑party lists and format comparisons for quick extraction gain more mentions in synthesized results.”
Category Differences: Software vs Products vs Agencies
When a model recommends a brand, the kind of page it cites depends on query intent and category.
Why landing pages dominate for software and agencies
Software and agency websites often have solution or feature pages that map directly to “best for” queries. These pages list features, use cases, and proof points in a compact way.
Data: software landing pages accounted for 37.2% of first‑party mentions; agency landing pages were 30.4%.
Strategic note: Indian SaaS and agency teams should invest in targeted vertical or use‑case pages with clear claims and recent updates.
Why product brands show more product pages and blog posts
Product research favors detailed product pages. For physical goods, models cited product pages 87.2% of the time.
Brands often support these pages with short editorial content about choosing or using a product. That content feeds comparison signals well.
How platform changes shift agency mentions
Platform behavior evolves. In one version (5.1), agency sidebars appeared less consistently, so mentions tracked via in-text links rose in importance.
This means what counts as a “mention” can change across platforms and versions, altering click patterns and measured referrals.
“Publish the factual page a model can parse: features, proof, and a clear ‘best for’ blurb.”
| Category | Dominant first‑party page type | Top % (from data) | Practical action |
|---|---|---|---|
| Software | General landing pages & solution pages | 37.2% | Build vertical pages with clear features and updated proof |
| Agencies | Service/landing pages | 30.4% | Create use‑case pages and keep case studies current |
| Products | Product detail pages + supporting posts | 87.2% | Prioritize accurate specs, images, and “how to choose” content |
- Planning tip: agencies and SaaS can rely on comparison and solution pages more, while product brands should focus on product pages plus short educational posts.
- Monitor platform changes; a version update can change what gets counted as a mention and how users click through.
Freshness, Authority, and Quality Signals Behind Citations
Recent date stamps on comparison pages sharply raise their chances of being reused in answer engines. From our dated subset, 79.1% of pages were updated in 2025 and 26% were edited in the past two months. That pattern points to a practical playbook: keep key pages current.
Update velocity becomes an operational KPI. Track how often comparison, landing, and product pages receive meaningful edits — not just a new date. A steady cadence of accurate revisions boosts the chance your content is treated as fresh, accurate information.
Why low‑authority domains still appear
About 28% of the most-cited pages show near‑zero organic traction. Retrieval systems can surface pages with weak traditional authority metrics, which creates both risk and opportunity.
Trust here means more than backlinks. Clear authorship, transparent sourcing, consistent facts, and verifiable figures help a website avoid repeating outdated claims when it is cited.
Bing vs Google: why questionable pages surface
Some questionable pages rank better in Bing than in Google. Systems that lean on Bing‑powered retrieval may therefore surface different results than search like google. That split explains why lower authority pages sometimes appear in answers.
| Signal | What we saw | Practical action |
|---|---|---|
| Freshness | 79.1% updated in 2025; 26% within 2 months | Publish change logs; schedule real revisions |
| Authority | Many cited pages have low domain strength | Show provenance, author bylines, and citations |
| Accuracy | 57.1% had post‑publication updates | Prioritize factual checks and price/feature accuracy |
“Make your pages easy to parse: short bullets, explicit ‘best for’ blurbs, and verified facts reduce the risk of mis‑extraction.”
- Create an update velocity dashboard for comparison pages.
- Embed clear sourcing and authorship to strengthen authority signals.
- Audit where your competitors are cited and whether those pages rank like google or in other engines.
Takeaway for Indian brands: freshness plus trustworthy signals improve the odds of being cited. But structure and transparent sourcing are the guardrails that keep human trust intact when your pages are reused in synthesized results.
Traditional SEO vs AI Overviews: Where Self‑Promotional Lists Win (and Where They Don’t)
Structured comparison pages that list use cases and short pros often perform well across both classic search and synthesized overviews. That overlap has practical consequences for publishers and brands in India.
Why Google overviews can favor comparison pieces
Google overviews prefer pages that present multiple entities with concise “best for” blurbs. These pages are easy for summary features to parse and cite, which makes them slightly more prominent in overviews than in chat sources.
How “best X” SERPs normalize self‑ranking for SaaS and agencies
In 250 “best X software” SERPs, 169 (67.6%) showed a company ranking itself first. That pattern has normalized the practice on many platforms and reduces stigma purely from a search standpoint.
Practical crossover: on‑page structure, internal links, and clarity
Traditional seo still matters: crawlability, semantic markup, and clean headings help both ranking and extraction. Use clear headings, short pros/cons, pricing blurbs, and internal links to related landing pages.
“Make pages easy to parse: explicit ‘best for’ lines, named entities, and tidy structure help search and overview systems alike.”
| Focus | Traditional SEO | Overviews & summaries |
|---|---|---|
| Format | Longer, keyworded pages | Short, structured comparisons |
| Needs | Optimization, backlinks, crawlable markup | Clear entities, ‘best for’ blurbs, recent dates |
| Practical action | Improve technical SEO | Structure content for fast extraction |
Next: a practical checklist to publish short comparison pages that protect trust while performing in search and overviews.
How to Publish Self-Promotional “Best” Lists Without Hurting Trust
A practical framework protects trust when a brand publishes a comparison that includes itself.
Start with intent. State who the page is for (best X for Y), list your evaluation criteria, and show methodology up front. Include a clear publisher disclosure so readers know you are the source.
Make it useful and fair
Link out to direct competitor pages and include concise “why it’s best for” blurbs. Use feature comparisons and constraints so the page stands alone as honest information.
Rank decisions and trade‑offs
Ranking yourself first may boost short‑term mentions and perceived leadership. Ranking lower can raise credibility. Choose based on buyer intent and conversion risk.
Formats systems can parse
Prefer tables, short bullets, and consistent subheadings so systems and readers extract accurate answers. Keep pricing, features, and availability current to avoid misinformation.
Maintenance and measurement
Adopt a cadence: quarterly reviews for stable categories, monthly for fast SaaS. Log changes and monitor mentions and, critically, the accuracy of responses with specialized tools.
“Transparent methodology and frequent updates turn a brand page into a useful, trustable reference.”
| Step | Action | Owner |
|---|---|---|
| Intent | Define audience & criteria | Product + Content |
| Accuracy | Verify pricing & features | Product Marketing |
| Audit | Monitor mentions & claims | SEO + Analytics |
Conclusion
Data from 750 prompts and over 26,000 source URLs points to repeatable page formats that models prefer. The primary insight: well‑structured “best X” pages often serve as supporting sources when models generate answers.
What the data suggests: higher placement in third‑party comparison pages correlates with more mentions, and freshness matters—79.1% of cited comparison pages were updated in 2025.
For Indian business and marketing teams, treat search and classic seo together with targeted work to craft extractable pages. Protect brand trust by showing methodology, linking to competitors, and keeping facts current.
Next steps: pick one topic, publish a credible comparison with clear snippets, schedule updates, and use measurement tools to track mentions and answer accuracy. Iterate as platforms and ai-generated answers evolve.
