Retail · Industry benchmark
Stage 0 · Framework live · benchmark pending

'Which grocery app is cheapest/fastest in my city?' — AI answers this thousands of times a day.

CiteRank measures who AI engines recommend in grocery & quick commerce — across ChatGPT, Gemini and Claude, in both grounded and ungrounded modes — and fixes why it isn't you.

3 × 2
Engines × modes (grounded + ungrounded)
250+
Grocery & Quick Commerce buyer prompts per run
Weekly
Re-runs · 95% confidence bands
Who AI recommends today

The grocery & quick commerce leaderboard, measured.

Top-5 brand mention rate, first-mention rate and Share of Voice — straight from the citerank-bench scoring tables, recomputed weekly.

Benchmark for Grocery & Quick Commerce runs with our first founding customer in this vertical. The leaderboard below is an illustrative sample built from the blueprint's brand registry — numbers are placeholders, not measurements.

#
Brand
Mention rate
First-mention
Share of Voice
01
BigBasket
62%
31%
34%
02
Blinkit
48%
22%
24%
03
Zepto
39%
14%
18%
04
Swiggy Instamart
27%
9%
14%
05
DMart Ready
18%
5%
10%

Illustrative sample — benchmark not yet completed.

Sample prompt set

Real grocery & quick commerce prompts, three engines, one question: did you get cited?

Buyer prompt
ChatGPT
Gemini
Claude
You cited?
"best grocery delivery app in Bangalore"
Not yet
"Blinkit vs Zepto vs Instamart — which is cheaper?"
Not yet
"fastest grocery delivery in Whitefield right now"
Not yet
"no-membership grocery app with free delivery"
Not yet
Where the citations leak

Three failure modes specific to retail.

01

Marketplace capture: AI cites Amazon/Flipkart/Myntra instead of your D2C site.

02

'Is it safe to buy from {brand}.com?' — AI answers from forum scraps, not your trust signals.

03

Category-page SEO collapses inside AI Overviews; PLP traffic moves to the answer panel.

Methodology

How a grocery & quick commerce benchmark gets built.

01
Onboard

URL, competitors, prompt seed list. 5 minutes.

02
Audit

250+ prompts × 3 engines × 2 modes, 10–30 replays each.

03
Fix

Schema, llms.txt, entity hygiene, content briefs — shipped.

04
Re-run

Weekly re-runs, deltas with 95% confidence bands.

Illustrative pattern

What a 90-day citation delta looks like.

Illustrative pattern based on our methodology — first cohort results publish Q4 2026.

Before
1 / 25

Cited in 1 of 25 high-intent grocery & quick commerce prompts across 3 engines (4%).

After · 90 days
9 / 25

Cited in 9 of the same 25 prompts (36%) — schema, llms.txt and entity fixes shipped over 3 weekly re-runs.

Founding cohort

Grocery & Quick Commerce case study publishes after the first 90-day window.

We don't ship anonymous success stories. Every case study card on this page becomes a real logo, real prompts and real deltas after the customer's 90-day window closes.

Founding seats · openApply for a founding seat
Insights

Coming in the Grocery & Quick Commerce visibility report.

Article · in the grocery & quick commerce report

Quick-commerce share of voice in AI answers, city by city

Notify me when published
Article · in the grocery & quick commerce report

Fee hallucinations: what AI gets wrong about delivery pricing

Notify me when published
Article · in the grocery & quick commerce report

Winning the 'cheapest' prompt without racing to the bottom

Notify me when published
FAQ

Grocery & Quick Commerce questions, answered.

How is CiteRank different from marketplace listings?+

Those surfaces optimise for their own funnel. CiteRank measures how often ChatGPT, Gemini and Claude actually name your brand for grocery & quick commerce buyer prompts, then fixes the schema, entity and content gaps so the engines have something to cite besides the aggregator.

Which segments / cities do you cover for this vertical?+

We start with your 250+ highest-intent buyer prompts — segmented by city, persona and price band as relevant — and expand the prompt graph weekly. Coverage scope is set during the 5-minute onboarding.

How fast to first new citation?+

First measurable citation lift is typically 3–5 weeks after the first fix pass (schema, llms.txt, entity, content briefs). Re-runs are weekly with 95% confidence bands so you can attribute deltas to specific fixes.

Is our data sent to LLMs?+

Only the public buyer prompts we run on your behalf reach the engines — exactly what a prospective customer would type. We do not send your CRM, customer data, or internal documents to any LLM.

Pricing

Start with one snapshot. Scale into weekly monitoring.

Snapshot Audit
₹14,999One-time

250+ prompts × 3 engines × 2 modes. Brand-mention report and gap analysis.

Monitor
₹7,999/ month

Weekly re-runs, deltas with confidence bands, alerting on rank/citation changes.

Visibility + Fixes
₹29,999/ month

Monitor + shipped fixes: schema, llms.txt, entity, content briefs and re-measurement.

Keep exploring

See the depth model and adjacent verticals.