This short guide explains what an AI visibility audit is and how it checks whether major platforms like ChatGPT, Claude, Perplexity, and Gemini recommend your brand or cite your site when buyers ask category questions.

Think of this as a baseline test for brand presence in generative search. The process captures mentions, source citations, sentiment, and a prioritized plan covering entity work, content, structured data, and technical fixes.

The how-to structure shows exact steps: design prompts, run tests, capture citation data, score share-of-voice, and map gaps to a roadmap that helps business and marketing teams make decisions.

We explain the difference between being mentioned and being cited, why both affect credibility and clicks, and how you can re-run this measurement to track progress over time in the India market.

Key Takeaways

• Learn the step-by-step method to test prompts and capture citations.
• Understand mention vs. citation and why both drive trust and clicks.
• Get a clear structure for scoring and translating results into fixes.
• Use the output to prioritize work across content, entity, and tech.
• Re-run the baseline to measure progress and improve search retrieval.

Why AI search visibility matters for brands in India right now

Brands in India must act now as answer engines reshape how buyers discover products and services. Buying moments like research and comparison are shifting toward concise recommendations, so early measurement creates a compounding advantage.

AI referral traffic is concentrated, and it’s growing fast

Most referral traffic from these answer systems comes from a single dominant source. Current data shows 87.4% of such traffic originates from ChatGPT, and overall referral volume is rising rapidly.

• Growth: AI referral traffic up 1,200% year-over-year.
• Concentration: 87.4% from one platform.
• Baseline: Google still drives 345x more traffic than all answer platforms combined.

AI-referred visitors can convert at higher rates than traditional search

Answer-driven visits often follow narrowed recommendations. Reports show these visitors convert at about 4.4x the rate of traditional search, making each referral more valuable for business outcomes.

SEO is still the foundation, AI visibility is the growth layer

Indexability, authority, and clear content remain essential. Use cross-platform measurement to avoid false confidence from one engine, and map the data so reports and audits guide priorities across platforms.

What an AI visibility audit actually measures

A clear measurement plan starts with real buyer queries. A practical audit tests whether your brand appears in actual responses and which URLs are cited as sources when people ask product or service questions.

Three measurement pillars guide the work:

• Recommendation or mention presence — whether your brand is named in answers.
• Citation behavior — which pages the systems pull from and how often.
• Competitive inclusion/exclusion — where competitors show up instead of you.

Testing is prompt-driven, so every query reflects buyer intent. Results are recorded per query: cited position, mention context, sentiment, and which competitor brands appear.

Platform differences matter. A brand can be recommended on one platform but omitted on another, creating uneven opportunity across platforms.

URL-level insight is key. Knowing the exact page cited lets you improve that content and replicate the pattern. That gap analysis then feeds scorecards, gap multipliers, and prioritized actions for the next sections.

Core metrics and signals to include in a visibility audit

A focused set of metrics turns raw query results into an actionable scorecard for your brand. Capture the numbers that link mentions and sources to real work: overall visibility score, share of voice, mention rate, citation rate, and average citation position by platform.

How to segment and score results

Segment citations by URL and by content type so teams see whether educational, comparison, or commercial pages drive sourcing. Break data down by topic and query pattern to reveal repeatable weaknesses like “best in city” or “vs competitor.”

Signals that map to actions

• Missed questions: prompts where competitors appear and your brand does not—turn these into content briefs.
• Sentiment: note endorsement versus neutral or cautionary language; tone affects conversion.
• Technical readiness: check robots access, schema, semantic HTML, performance, and internal linking on the site.

Each metric should tie to a lever: technical fixes, content upgrades, entity consistency, or off‑site authority building. That mapping makes the audit practical and ready for prioritization across platforms.

Define scope and build a prompt list that reflects buyer intent

Start by setting a clear scope so prompts map directly to the buyer journeys you care about. Pick the category, priority products or services, key cities in India, and 3–5 direct competitors before you write prompts.

Local intent prompts for India-specific discovery

Use location-first queries like “best invoicing software in Bengaluru” or “top digital marketing agency in Mumbai.”

These show how well your site appears for local search and whether purchase-ready users can find you.

Discovery prompts that map to early research behavior

Include “how to choose,” “what features matter,” and “what mistakes to avoid.”

These queries often trigger educational citations and reveal content gaps you can fill.

Comparison prompts that reveal shortlist dynamics

Test “Brand A vs Brand B,” “best alternatives to X,” and “agency vs freelancer.”

Comparison results highlight where your brand and competitors land in shortlists.

Problem-based prompts tied to pain points

Add troubleshooting queries like “why is GST invoice failing” or “how to fix payment reconciliation.”

Being the cited solution on problem prompts can drive high-intent clicks.

Governance note: Keep the prompt list consistent across runs so you measure progress over time. Build prompts from sales calls, support tickets, and Search Console queries rather than chasing unverifiable volume. Run a core set of 15–20 queries for a baseline and expand to 20–30+ for deeper work.

Platform differences that change your visibility story

Different answer systems sort and cite sources in unique ways. A single-platform check can hide risk because each system uses different retrieval logic and trust signals.

Why top-mentioned sources are often unique to a single platform

Research shows about 86% of top-mentioned sources can be unique to one platform. That means a page that ranks well on one model may not be recognized elsewhere.

This uniqueness makes cross-platform testing mandatory. Without it, teams can mistake a narrow win for broad success.

How citation preferences vary by ChatGPT, Perplexity, Claude, and Gemini

Each platform favors different signals. Perplexity often displays explicit citations and research-style links. Gemini tends to align with Google-indexed pages and structured answers. ChatGPT referrals drive most traffic in many markets, so performance there matters early. Claude may surface niche or specialist sources more often.

How to prioritize platforms when presenting findings to stakeholders

Start with where referrals concentrate, then map where your audience researches and compares. For India, begin with the largest referral source, then expand to platforms used for research and comparison.

• Show platform-by-platform scorecards in your report so non-technical stakeholders see strengths and gaps at a glance.
• Remember: a strong mention does not always equal a citation or a top position. Measure all three.

Run citation testing and capture a real-time snapshot

Record each platform’s reply in real time to snapshot which pages are cited and which are omitted. Live tests give you defensible data for the report and make timing notes essential.

Build a citation matrix for position and “not cited” outcomes

Method: run each prompt on every platform, save the full response, and note whether your brand is mentioned and whether a site URL is cited.

Track brand context, competitor inclusions, and response patterns

Log whether mentions are endorsements, neutral, or cautionary. When your brand is absent, record which competitors appear and their order.

Document the exact cited URLs powering answers

Paste the exact cited pages into the matrix so content teams can replicate what’s rewarded. Note repeated domains to spot small authority sets and emerging patterns.

• Matrix format: rows = prompts, columns = platforms; cells = position 1–6, “not cited,” and cited source URLs.
• Include timestamps, screenshots, or exports so results stand up over time.
• Use the data to prioritize pages for updates and to feed your next round of testing with the same tool and time window.

AI visibility audit scorecards that decision-makers understand

Start the report with a one‑page executive summary. Leaders skim, so this page must state where you stand, who is winning, and what to do next in plain language.

Executive summary elements that make the data skimmable

Keep the summary to a single page. Include the overall AI visibility score (0–100 with a letter grade), a short plain-language assessment, and counts for prompts tested, competitors analyzed, and platforms included.

AI visibility score and platform-by-platform scorecards

Show an overall score plus platform cards for ChatGPT, Perplexity, Gemini, and Claude. Platform cards reveal uneven performance and guide platform-specific work.

Citation gap shown as percentage and multiplier versus top competitor

Present the citation gap both as a percent and as a multiplier versus the top competitor. A 25‑point swing or a 2x multiplier is an easy point to raise in meetings.

• Above the fold: overall score, top competitor comparison, and three high‑impact fixes.
• Baseline note: this is a sampling of prompts, not the full universe; re-running creates trendlines.
• Delivery best practice: present live with the citation matrix to show context and make findings persuasive.

Tie each scorecard to the underlying data and the recommended fixes so decision-makers can move from score to action.

Analyze the citation gap and identify who is winning

Map each cited source by rank and prompt to identify real winners across platforms. Start with a simple matrix that records position, platform, prompt type, and the exact URL cited. This gives a clear picture of which domains hold top slots and where the real gaps are.

How to interpret citation position and why top slots matter

Positions 1–2 are primary visibility: these slots drive most clicks and trust. Treat mid positions as secondary opportunities that still convert but need reinforcement.

Not cited means a true gap and should be flagged for immediate action. Use consistency across runs to confirm patterns before you prioritize fixes.

Competitive breakdown by prompt, platform, and cited page type

Read “who’s winning” beyond raw counts. Look at position, how often a domain appears across queries, and where it shows on the most important platform for your market.

• Local queries: service pages and listings often lead.
• Discovery prompts: blog posts and explainers win repeats.
• Comparison and problem-based queries: product pages, comparison guides, and tool pages commonly earn citations.

Non-competitor sites cited in your niche as authority and backlink targets

Audits often surface others like Reddit threads, YouTube videos, G2, Quora, and industry directories. These sources shape answers and can be high-leverage PR or partnership targets.

SEO leverage: prioritize outreach, listings, or content placements on repeat-cited domains to strengthen authority signals and close gaps. Map each gap to a fix type—content upgrade, new content, entity consistency, or technical access—so work is actionable and trackable.

Map citations to your site architecture and content types

Start by matching each cited URL to its place in your site. This exposes which content types earn recommendations and where to focus work.

Why educational and comparison content often earns more citations

Explanatory and comparative pages provide neutral, structured answers. Models prefer these when they must explain options or trade-offs.

This means blog explainers, comparison posts, and glossaries often get cited more than raw product listings.

How to compare cited pages to your SEO top pages

Export cited URLs and cross-check them against top organic pages in Search Console and your analytics. If a cited page already drives traffic, it’s a fast route to better brand inclusion.

Use that overlap as a baseline: prioritize pages that prove relevance in SEO and show up in citations.

Spot “cited but not mentioned” pages and convert them into brand wins

“Cited but not mentioned” means your content powers answers without brand credit. This is high leverage because the page has authority but lacks attribution.

“When the page is used but the brand isn’t named, you are giving away conversion potential.”

• Write short definitional lines that include your brand naturally.
• Strengthen author and organization schema on cited pages.
• Use internal links from cluster posts to commercial pages so users and models see intent paths.
• After edits, re-run the same prompt list to measure mentions, position, and traffic changes against your baseline.

Next step: convert patterns into prioritized action items and test again to confirm improvement.

Find topical gaps and missed questions your brand should own

Map the queries that name competitors while omitting your brand to spot repeatable topic gaps. This process turns empty recommendation slots into a prioritized plan you can act on.

Identify topics where competitors are mentioned but you are omitted

Build a simple table: prompt, platform, cited URL, and whether a competitor appears. Group prompts by topic and flag those that repeatedly omit your brand.

Turn missed prompts into content briefs and clusters

Create briefs with required headings, a concise canonical answer up front, one or two supporting data points, and internal links to related pages.

• Headings: question-style H2/H3 that match common queries.
• Lead: 30–50 word summary that answers the query.
• Evidence: stats, examples, and links to authoritative sources.

Use Q&A formatting and concise summaries for extraction

Structure matters: short definitions, bullet lists for criteria, and clear stepwise answers help systems and readers extract the answer fast.

Cover the full journey: educational, comparison, and problem-solving pieces. Then map each new page back to the original prompt and re-run tests to measure change and guide next action.

Measure sentiment and the AI narrative about your brand

Capture the language platforms use about your brand to turn qualitative signals into metrics. This step classifies whether platform responses endorse, list neutrally, or use cautionary language. The goal is to make sentiment a measurable part of your visibility scorecard.

Endorsement versus neutral listing versus cautionary language

Endorsed: the response recommends your brand and uses positive language. Label examples and save the exact response text as evidence.

Neutral option: your brand appears among peers with factual phrasing. Capture the snippet so teams can compare phrasing across platforms.

Caution/negative: the reply warns or flags problems. Flag these quickly—negative framing can harm conversion more than omission.

Key sentiment drivers and how to act

Trackable drivers include reviews, third-party reputation, claim clarity, transparency, and consistent entity data. Store each response snippet and tag the driver that explains the tone.

• Define labels operationally so scoring is consistent.
• Keep the exact response text to make findings auditable.
• Fixable items: add case studies, surface reviews, and correct third-party listings.
• Report differences across platforms to show where messaging or PR is needed.

Tie sentiment to marketing: hand these findings to brand and PR teams so they can prioritize messaging, reputation fixes, and content that improves citation phrasing and overall visibility.

Audit off-site sources shaping AI answers across platforms

External domains frequently set the narrative buyers see in generated answers. These sources matter because models and retrieval tools draw trust from repeat citations on third‑party sites.

Identify influential third‑party domains

Compile the most‑cited domains from your prompt matrix and classify them into UGC, media, directories, review sites, and industry resources.

Prioritize UGC and media that repeat

Focus on domains that appear across platforms. Repeat citations indicate a broad narrative effect and higher chance of shaping buyer decisions.

Decide where to invest: directories, communities, video, thought leadership

Translate citations into an authority plan: claim listings, boost review profiles, publish on community threads, and create videos where your audience looks for answers.

• Match channel to intent: YouTube for demos, Quora/Reddit for troubleshooting, LinkedIn for B2B credibility.
• Prioritize India‑specific publications and local directories for regional business impact.
• Use high‑frequency sources as backlink and entity reinforcement targets to improve both SEO and broader visibility.

“Repeat citations on trusted domains become the scaffolding of category authority.”

Connect AI visibility to real performance using analytics baselines

Translate citation patterns into sessions and conversions to make the case for prioritized fixes. Start with a clear baseline so teams can see which pages already drive traffic and which ones to test first.

Use Google Search Console to surface non-branded queries

Filter out branded terms and export top non-branded queries, landing pages, impressions, CTR, and average position. These queries become your test set and guide content upgrades.

Use Google Analytics to isolate organic and referred traffic

Segment organic search traffic, then build a channel view for known referrers and platform landing pages. Tag and track sessions so you can compare pre- and post-change performance.

Set expectations on attribution and reporting

Note: some visits may show as Direct when referrers are hidden. Treat reported referral numbers as a conservative floor rather than the full total.

• Why baselines matter: visibility metrics are strongest when tied to sessions, engagement, leads, or revenue.
• Quick wins: prioritize pages that already perform in SEO or show early referral traffic for faster uplift.
• Cadence: track referrals monthly and re-test prompts quarterly to measure change over time.

“Connect the report data to traffic and conversions so every recommended step maps to business outcomes.”

AI visibility audit technical checklist for crawlability and trust

A practical technical pass ensures your site and content are reachable, reliable, and easy for systems to parse. Use the checklist below to confirm crawl access, markup quality, and performance so your pages can be cited and trusted.

AI crawler access in robots.txt and indexation

Confirm major bots are not blocked: GPTBot/OAI-SearchBot, Google-Extended, PerplexityBot, ClaudeBot. Ensure key pages are accessible without logins or heavy scripts.

Schema markup coverage and validation quality

Prioritize Organization, Article, FAQ, Product, HowTo, and Review schema. Validate JSON-LD with Google’s Rich Results Test to avoid malformed structured data.

Semantic HTML, performance, and rendering

• Use clear heading hierarchy, descriptive anchor text, and consistent templates for machine parsing.
• Check Core Web Vitals, HTTPS, and mobile usability as trust foundations.
• Ensure JavaScript-rendered content is server-side rendered or pre-rendered where possible.
• Keep XML sitemaps current and confirm indexation of priority pages.

llms.txt as a guided tour

Not mandatory, but useful: llms.txt can point crawlers to high-trust pages (About, authors, case studies, reviews, services) and reduce ambiguity about where to look for E-E-A-T signals.

Priority point: fix crawler access and schema first — they unlock downstream gains in performance, structure, and content testing.

Strengthen your entity profile and E-E-A-T signals for AI verification

Strong entity signals help systems cross‑check your brand across the web and trust your content as a source. Consistent public profiles reduce ambiguity and increase the chance your site or page is recommended.

Consistency across LinkedIn, Google Business Profile, directories, and your website

Match your brand name, descriptions, category, and contact details across all profiles. Inconsistent names or differing addresses create verification friction and lower recommendation rates.

Organization schema, SameAs links, and brand name alignment

Add complete Organization schema to key pages and include SameAs links to official profiles. Use an exact name string that matches LinkedIn and Google Business Profile so systems can unify your entity footprint.

Content trust assets AI looks for: authors, credentials, case studies, and reviews

E-E-A-T assets increase citation confidence. Publish named authors with short bios, list credentials, add case studies with measurable outcomes, and surface authentic reviews and testimonials.

• Consistency checklist: align name usage, category, and core positioning across site and profiles.
• Schema needs: accurate fields + SameAs links to official profiles.
• Trust content: author bios, editorial notes, case studies, and verified reviews.

“Entity fixes often improve mention likelihood even without new pages because they reduce verification friction.”

India-specific guidance: highlight local certifications, client logos, compliance notes, and regional proof points to build credibility with buyers in India.

Track progress by recording mentions, sentiment, and citation frequency before and after changes. Tie each change back to the baseline so teams see how entity work moves the needle on overall visibility and SEO.

Turn findings into a prioritized action plan and report deliverables

Convert the findings into a short, sequenced plan that ranks tasks by impact and effort. Start with a Week 1 list of immediate technical fixes, then define near-term content updates and mid-term topic expansion. Each entry should name an owner, a due date, and the metric it aims to move.

Immediate technical fixes that unblock access

Week 1: fix robots.txt blocks, repair broken schema, resolve indexation blockers, and ensure key pages render without heavy client-side delays.

Near-term content upgrades to improve citation readiness

Weeks 2–4 focus on pages most likely to be cited. Add concise summaries, Q&A sections, comparison tables, and stronger internal linking so systems and readers find canonical answers fast.

Mid-term topic expansion to close buyer journey gaps

Months 2–3 build clusters that target missed prompts and competitor gaps across awareness, consideration, and decision stages. Prioritize topics that tie to conversions.

How to present the report

Deliver a stakeholder-ready PDF with scorecards and the citation matrix. Pair that with a live walkthrough or a short video so marketing teams can align quickly.

When to re-run audits to track progress

Run monthly quick checks for analytics and referral shifts. Re-test the full prompt set quarterly or after major site changes to measure movement across platforms.

Action tip: attach the original prompts and target KPIs to every task so each change can be measured against the baseline.

Conclusion

Treat the final step as a launch: pick a small prompt set, run a quick visibility audit snapshot this week, and use the results to prioritize fixes.

This guide gives you a simple workflow: build buyer‑intent prompts, test across each platform, capture a citation matrix, and turn the data into scorecards and a prioritized report.

Remember: keep SEO as the foundation and add the generative search layer to grow brand reach in India. Re‑test periodically—platform behavior and information sources change fast.

Start small, act on the pages the data shows, and scale your work each quarter. That practical loop is the fastest path from insight to measurable business impact.