Research · August 2026

Twenty Indian brands. Six hundred AI answers. Who gets named.

In August 2026 we ran fifteen buyer questions for each of 20 Indian brands, through ChatGPT and Perplexity. That is 600 answers in all, and we counted which brands each one named. The median brand was named in 55% of its own category's answers. 9 of the 20 were named in fewer than half of them, and 7 in one answer in three or fewer.

Method

For each brand we wrote fifteen questions a buyer in its category asks. Most carry no brand name at all. A few carry the brand's own name, such as is it good or what does it cost. Each question was sent once to ChatGPT and once to Perplexity on 18 August 2026, from India, through their search-grounded APIs. We saved the full answer text and every cited URL.

A mention is the brand's name, or a known alias, appearing as a whole word in the answer text. The share is simple: the number of answers that named the brand, divided by the thirty answers we ran for it. The same match was run for each brand's tracked competitors. An answer that named none of them counts as naming no brand.

Two engines were measured. Gemini and Google AI Overviews were not part of this sweep, and nothing here estimates them. Our separate payroll and HRMS study covers all four engines for one category. That study ran 40 questions and produced 159 answers, read by hand in the consumer apps.

The table

Answers naming the brand, out of thirty. Then out of fifteen on each engine. The last column is the competitor named most often in the same answers.

Answers naming the brand. Fifteen buyer questions per brand, one run each on ChatGPT and Perplexity, 18 August 2026.
BrandCategoryNamedShareChatGPTPerplexityNamed most in the same answers
PetpoojaRestaurant POS26 of 3087%13 of 1513 of 15Restroworks (20)
StayVistaLuxury villa stays24 of 3080%14 of 1510 of 15SaffronStays (14)
VyaparSMB billing and GST software24 of 3080%10 of 1514 of 15Tally (20)
AiSensyWhatsApp marketing SaaS23 of 3077%10 of 1513 of 15WATI (22)
KekaHRMS and payroll23 of 3077%14 of 159 of 15greytHR (24)
DittoInsurance advisory20 of 3067%11 of 159 of 15Policybazaar (11)
SupertailsPet care and pet food20 of 3067%11 of 159 of 15Heads Up For Tails (16)
BlissClubWomen's activewear19 of 3063%12 of 157 of 15Decathlon (17)
HROneHRMS and payroll19 of 3063%6 of 1513 of 15greytHR (23)
The Whole TruthProtein and health food17 of 3057%8 of 159 of 15MuscleBlaze (16)
VaareeHome decor16 of 3053%9 of 157 of 15Pepperfry (23)
All Things BabyBaby products11 of 3037%4 of 157 of 15FirstCry (16)
NutrabaySports nutrition11 of 3037%3 of 158 of 15MuscleBlaze (17)
FoxtaleD2C skincare10 of 3033%5 of 155 of 15Minimalist (22)
ZimyoHRMS and payroll10 of 3033%5 of 155 of 15greytHR (21)
Man MattersMen's health9 of 3030%4 of 155 of 15Traya (7)
Leverage EduStudy abroad counselling7 of 3023%5 of 152 of 15IDP (21)
RAS Luxury SkincareLuxury ayurvedic skincare7 of 3023%4 of 153 of 15Forest Essentials (18)
EarthfulMenopause nutrition3 of 3010%1 of 152 of 15OZiva (7)
PropertyPistolReal estate brokerage2 of 307%1 of 151 of 15Housing.com (8)

Finding 1: the two engines disagree about the same brand

6 of the 20 brands were named at least four answers more often on one engine than the other, out of fifteen. HROne was named in 13 Perplexity answers and 6 ChatGPT answers. Keka scored 14 on ChatGPT against 9 on Perplexity. BlissClub scored 12 on ChatGPT against 7 on Perplexity. Nutrabay scored 3 on ChatGPT against 8 on Perplexity. StayVista scored 14 on ChatGPT against 10 on Perplexity. Vyapar scored 10 on ChatGPT against 14 on Perplexity.

The direction is not fixed. In HRMS, ChatGPT cited vendor pages and Perplexity cited listicles and LinkedIn posts. So a vendor with a strong site and a thin third-party record did better on ChatGPT. Elsewhere it ran the other way. The strong engine is the one that reads the kind of page the brand's category publishes.

Finding 2: being cited is not being named

Vaaree's own domain was the second most cited source in its category's answers, ahead of ikea.com. The brand was still named in 16 of 30 answers, and Pepperfry in 23. Supertails's site was the most cited source in pet care. The brand was absent from 10 answers, several of which cited the site and then recommended Royal Canin.

Crawlability is necessary. It is not what puts a brand in the shortlist. The engines rank by how often a name recurs across everything they read. A brand's own site is one source among many.

Finding 3: some categories have no winner yet

In 5 categories a large share of answers named no tracked brand at all. The counts: men's health 17 of 30, menopause nutrition 17 of 30, real estate brokerage 14 of 30, insurance advisory 8 of 30, study abroad counselling 7 of 30. These are answers with an empty shortlist. The engine described the category and recommended nobody.

An empty shortlist is the cheapest position to take. Whichever brand becomes quotable first on the pages these engines read will hold it.

Finding 4: the headline number can hide the real one

Zimyo was named in 10 of 30 answers. All of those came from questions that contained its name. The other questions are the ones a buyer asks before they have a shortlist. On those, it was named in 2 of 22. So branded and unbranded questions have to be scored apart. The unbranded share is the one that describes discovery.

Finding 5: a competitor's pages can be the category's source

In study-abroad counselling, idp.com was the single most cited domain across Leverage Edu's fifteen questions. IDP was named in 21 answers, against Leverage Edu's 7. In HRMS, one vendor's blog was cited in nearly half of the pooled answers to three competitors' buyer questions. When a rival's pages are what the engine reads to answer your category, its name comes with them.

Finding 6: positioning, price and trust are all quoted, not inferred

  • Best free billing software went to Zoho Invoice. One sentence on its site says 100% free for Indian businesses forever. A competitor's real free tier went unnamed, because no page states it that plainly.
  • A restaurant POS vendor publishes no rupee price. One engine quoted its price from a US dollar listing on G2, the other from a third-party estimate. It lost the cheapest-POS question to an unknown vendor with a published price of one hundred rupees a month.
  • A SaaS brand is rated above four on G2, from more than a hundred reviews. Asked whether it is any good, both engines quoted a thirteen-review Trustpilot profile at 1.9 out of 5 instead.
  • A premium skincare brand was named in every answer to questions phrased in its own vocabulary. In the words buyers actually use, it was named in 3 of 26.

Limits

  • Two engines. Gemini and Google AI Overviews were not measured in this sweep.
  • One run per question per engine. Answers vary between runs; the shares are a reading, not a constant.
  • API answers. The consumer apps add personalisation and memory that the API does not, so what a given buyer sees can differ.
  • Fifteen questions per brand, written by us. A different question set would move individual numbers, though we have not seen it move the pattern.
  • 20 brands chosen because we were looking at them, not sampled from a population. The median is the median of this set.

Questions

Which Indian brands appear most often in AI answers?

We measured 20. Named most often in their own categories' answers: Petpooja (26 of 30), StayVista (24 of 30), Vyapar (24 of 30). The category leaders were named more often still. greytHR and Keka lead in HRMS, Pepperfry in home decor, Minimalist in skincare.

Is ChatGPT or Perplexity more likely to name an Indian brand?

Neither, consistently. 6 of 20 brands scored at least four answers apart on the two engines, in both directions. Which engine favours a brand depends on which kind of page its category publishes.

Can I use these numbers?

Yes, with attribution to AccessAegis and the date. They describe one run on one day; if you need a current reading for a brand, run the questions again.

Fifteen minutes. We'll run ten of your buyers' questions live.

No deck. You see who gets named today, per engine, and leave with the baseline whether or not we work together.

Or write to harsh@accessaegis.com