This headline captures one clear comparison: AI assistants are driving search-like visits, while the incumbent search engine still funnels far more outbound clicks to the open web.
Why this matters to Indian SEO and content teams: budgets are tight, attribution is messy, and leadership asks whether AI search will replace traditional search engines.
The numbers come from two lenses: a Mar 2025 clickstream snapshot (Similarweb) and Jan 2026 cohort analytics (Ahrefs Web Analytics). Each lens measures different denominators — queries, visits, or outbound clicks — so the same story can show both 12% share and a 190x difference depending on the metric.
What to expect in this article: a clear decision framework for marketers: keep search engine SEO as the foundation, then add AI optimization for incremental, qualified sessions and conversions. The analysis focuses on trends from Mar 2024–Mar 2025 (with Jan 2026 context), and offers practical guidance on publishing, citing sources, and measuring AI referrals in GA4 and Search Console.
Key Takeaways
- AI assistants are growing in search-like use but send fewer outbound clicks per visit.
- Two datasets (clickstream and cohort analytics) reduce single-source bias.
- Indian SEO teams should prioritise core SEO, then layer AI-focused tactics.
- Focus on trends and growth rates, not exact counts from any single month.
- Expect actionable steps for content, technical SEO, and correct referral measurement.
Why this ChatGPT vs Google traffic comparison matters for SEO in India
Before reacting to the numbers, clarify whether they describe queries or measurable site visits. That distinction shapes what Indian marketers should optimise.
What “search volume” vs “referral” means
Search volume is about queries or sessions generated on a platform. It signals attention and top-funnel demand.
Referral means measurable clicks that land on your site. Referrals map more directly to sessions, leads, and revenue.
Where AI assistants sit in the channel mix
Ahrefs cohort data shows search accounts for ~40.65% of tracked visits while AI assistants are ~0.26% (ChatGPT ~0.23%).
In real analytics, AI is a small slice compared with traditional search, Direct, Paid, and Social. Yet small share can grow fast.
How to read the headline without misreading the data
- Confirm geography and device coverage.
- Check what counts as an outbound click and whether self-referrals are excluded.
- Map metrics to business outcomes: volume ≠ conversions; referrals matter most for pipeline.
Practical strategy: protect core SEO wins, then test AI-focused formats and citation-ready assets. Treat multi-surface journeys as a single user path when assigning attribution.
Reach and audience size: Google still sets the ceiling
Audience size sets the ceiling for how many users a platform can steer to your site.
Unique visitors (Mar 2025, U.S.): Google 269.6M, chatgpt 39.6M — about a 6.8x difference. This snapshot shows the maximum possible people you can influence on each surface in a given month.
The reach gap matters for planning in India. Even with rapid percentage growth, a smaller audience starts from a lower number. Small ranking moves on the larger engine can still yield bigger absolute returns than big gains on the challenger.
At the same time, chatgpt grew +47% year-over-year in the same period. That growth compounds, so plan a 6–12 month runway for experiments and content that is citation-ready for AI assistants.
- Use reach first: it sets the upper bound when forecasting influence and conversions.
- Allocate resources: prioritise core commercial pages and technical SEO for larger engines; reserve a smaller budget for AI-citable assets.
- Remember: reach ≠ referrals. A platform with fewer users can still send quality clicks if its interface nudges verification.
| Metric | Google (Mar 2025, U.S.) | chatgpt (Mar 2025, U.S.) |
|---|---|---|
| Unique visitors (monthly) | 269.6M | 39.6M |
| Reach ratio | ~6.8x larger for Google | |
| YoY growth | — | +47% |
| Implication for India | Primary allocation for core SEO | Targeted investment for informational, citation-ready pieces |
Next: outbound clicks are where attention converts to measurable site sessions, and that’s where these platforms diverge most.
Total outbound clicks: the open-web “firehose” vs the fast-growing challenger
A platform’s real influence is clearer when we count clicks that end on external pages.
Outbound clicks comparison (Mar 2025): 175.5M vs 57.7M. Google remains the open‑web firehose, sending the highest absolute volume of clicks to third‑party sites.
Growth rates that change the story
Year‑over‑year change: Google +66%, ChatGPT +558%. The faster rate shows why teams must watch the challenger even if absolute numbers are smaller.
Why both claims can be true
Google pushes ~3x more clicks, yet the challenger’s steep rise means it is not a rounding error. Different baselines and growth curves make both strategic points valid.
How clicks translate to business outcomes
- Clicks → sessions → engaged sessions.
- Engaged sessions → conversions like lead forms, demo requests, or ecommerce purchases.
- Your actual referral share depends on brand strength and topical authority.
| Metric | Open‑web platform (Mar 2025) | Challenger (Mar 2025) |
|---|---|---|
| Outbound clicks | 175.5M | 57.7M |
| YoY change | +66% | +558% |
| Practical take | Primary source for volume | High growth; monitor and test |
Efficiency per user: why ChatGPT can send more clicks per visit
Efficiency per user is the chance a single visit leads to an outbound click. This metric matters when a platform with fewer users can still drive meaningful referrals.
Clicks-per-visit gap
Measured data shows ~1.4 external links per visit on the challenger versus ~0.6 on the larger engine. In practice, that means a session is more likely to produce multiple clicks on the smaller surface.
Why users click: faith-check behaviour
Faith-check happens when a user wants to validate an answer. Inline links and summaries nudge users to open sources to confirm claims or pull exact figures.
Content, citations and trust signals
For Indian SEO teams, this suggests prioritising clear claims, original data, and easy-to-scan sections that are citation-ready.
- Trust elements: named authors, updated dates, and primary-source links.
- Optimization: schema markup, strong internal linking, and useful tables or definitions.
- Practical tip: create pages designed to be referenced in an AI overview or summary.
“When answers provide a source, a portion of users will click through to verify.”
Stickiness and zero-click risk: Google’s in-platform behavior is increasing
User behaviour on search platforms is shifting toward longer in‑platform sessions, and that changes who gets clicks.
Define stickiness: it is the tendency for users to keep interacting inside the results page—refining queries, opening modules, and using richer answers—rather than clicking out. Higher stickiness raises the risk of zero‑click outcomes for publishers and brands.
Pages-per-visit climbs and what it means
Desktop pages-per-visit climbed to 10.1 in Apr 2025, up from 8.4 two years earlier.
This trend signals a structural shift: one session can now contain many queries and interactions, and the page often surfaces answers without sending users away.
How SERP features and AI interfaces reduce organic clicks
Richer modules, answer boxes, and AI overviews can satisfy intent on-platform. That lowers the available click volume even when rankings remain steady.
Events and algorithm changes can swing referrals quickly
Major Core+Spam updates (Mar–Apr 2024), the AI Overviews launch (May 14), and high-interest events in May–Jul 2024 caused measurable month-to-month swings.
Even if your site did nothing different, referral output can change with product rollouts or cultural events like sports and shopping peaks.
Practical mitigation: focus on queries that need depth—comparisons, pricing nuance, specs, policy detail, and complex how-tos. These are less likely to be fully answered in an overview and more likely to earn a click.
- Monitor macro product changes and event calendars.
- Prioritise depth pages that satisfy post-click intent.
- Measure month-level shifts to separate algorithm noise from real growth.
Next: even when platforms send clicks, distribution is uneven—brand strength and domain concentration determine who captures those rare outbound visits.
Where referrals actually go: winners, concentration, and brand effects
Referral clicks concentrate heavily on a small set of domains, and that shapes who benefits from assistant citations.
Measured data shows 64% of external clicks land on only 120 domains. Major destinations include YouTube, Wikipedia, Amazon, and NIH PubMed. That level of concentration matters for Indian marketing teams.
Who wins and why
The dominant sites are technology, health, and news publishers. These categories get cited often because they publish frequent updates, long-form explainers, and verifiable sources.
Implication: the web rewards reference material and depth more than short blog posts that chase keywords.
Practical playbook for brands
- Publish explainer pages, documentation, and original research that act as sources for summaries.
- Make pages easy to cite: clear claims, named authors, and primary-source links.
- Prioritise a few cornerstone resources over many shallow posts.
Branded-search lift and measurement
When an assistant cites your brand but provides no link, people often perform a branded search next. That follow-up shows as organic branded queries and can drive measurable sessions to your website.
“Being cited increases demand even when a direct outbound click is not provided.”
Tracking tip: monitor brand query share in Search Console and correlate spikes with PR, citations, or blog mentions. Validate concentration metrics before shifting budgets—tracking gaps and self-referral exclusions can skew results.
Methodology and data limitations you should know before changing strategy
Measurement methods shape the story; know what each dataset can and cannot capture.
Browser-only gaps and app attribution
The single biggest limitation is browser-only measurement. Similarweb’s panel tracks desktop and mobile browsers, not app activity.
In India, app-first behaviour is common. App referrals often lack referrers and show up as direct in GA4, which undercounts assistant-origin sources.
Expected variance and excluded referrers
Treat third‑party numbers as directional. Typical variance is about ±10%, and it can widen to ±30% in edge cases.
OpenAI and Google self-referrals were removed. That adjustment matters: ~27.7% of one assistant’s clicks in March went to OpenAI subdomains before stripping.
How to validate your numbers
In GA4, open Acquisition > Traffic acquisition. Create a segment for known assistant referrers where available, and compare browser vs app landing patterns over a full month.
Use Search Console query and page trends to confirm whether branded and non‑brand demand moved at the same time.
| Issue | Impact | Practical step |
|---|---|---|
| Browser-only panel | Underrepresents app-origin sessions | Compare panel data with GA4 app+web and server logs |
| Missing referrers | Shows as direct, misattributing channel | Implement UTM on share links and monitor landing pages |
| Measurement variance | Directional numbers, not exact | Use ±10–30% range and validate across 4–8 weeks |
| Self-referrals removed | Outbound click totals change materially | Document exclusions and report both raw and cleaned numbers |
“Run a 4–8 week content test (citation-rich updates + new resources), then measure lifts in assisted conversions, branded queries, and engaged sessions.”
Conclusion
This comparison leads to one clear recommendation for India: protect your core search wins while running targeted experiments on assistant-driven referrals. Google leads in reach (269.6M vs 39.6M) and outbound clicks (175.5M vs 57.7M), but chatgpt shows higher clicks per visit and faster growth.
Prioritise technical SEO and commercial rankings first. Then add AI-aware content updates that improve citation readiness and source quality without replacing foundational work.
Practical checklist: audit top 20 revenue pages for citation readiness, strengthen internal linking, add schema, show authorship, and publish unique data. Track assisted conversions, branded-search lift, and small incremental gains rather than big forecasts.
Frame this as portfolio risk management for stakeholders: core acquisition is the base; AI is the growth option. Start a quarterly roadmap that pairs classic optimisation with measured discovery experiments.
