AI SEO Case Study: How a Bangalore B2B SaaS Brand Went From 0 to 34% Citation Rate in 14 Weeks

A complete breakdown of one Generative Engine Optimization engagement โ€” the starting position, what we changed, the exact timeline, and the numbers at week 14. Nothing rounded up, including what didn’t work.

14 weeks

Engagement length

0% โ†’ 34%

Citation rate across 40 prompts

โ‚น95,000/mo

Retainer (Growth plan)

11ร—

Return on retainer by week 14

Quick Answer

What does an AI SEO case study show?

This AI SEO case study documents a 14-week Generative Engine Optimization engagement for a Bangalore-based B2B SaaS company. Starting from zero citations across 40 target prompts, the brand reached a 34% citation rate in ChatGPT, Claude, Gemini and Perplexity, generated 47 qualified leads from AI referral traffic, and returned roughly 11ร— the โ‚น95,000 monthly retainer by week 14.

01 โ€” The starting point

Client background and the problem

The client is a mid-sized B2B SaaS company in Bangalore selling compliance software to Indian manufacturing firms. Roughly 40 employees, โ‚น9 crore ARR, six-year-old domain. Client name withheld under NDA; all figures verified from their GA4 and CRM.

They ranked well on Google โ€” positions 3 to 8 for their main commercial keywords. But their sales team kept hearing the same thing on discovery calls: “we asked ChatGPT for options in this category and you weren’t on the list.”

Metric Before (Week 0)
Citation rate โ€” 40 target prompts 0%
Pages indexed in Bing 12 of 340
AI crawler hits per month (server logs) 0
AI referral sessions per month (GA4) 3
Schema types implemented None
Google organic sessions per month 14,200
Leads from organic per month 62

02 โ€” What we did

The 14-week implementation

A complete generative-search stack โ€” built to make your brand the answer AI tools give, and the link Google ranks.

/01

Weeks 1โ€“2 ยท Unblock and index

Removed AI crawlers from the Cloudflare bot-fight ruleset and explicitly allowed GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot and Google-Extended in robots.txt using the current user-agent strings from OpenAI's crawler documentation. Submitted the full sitemap to Bing Webmaster Tools and requested indexing on 60 priority URLs. Result by week 2: first GPTBot hits appeared in server logs on day 9. Bing indexation went from 12 pages to 214.

/02

Weeks 2โ€“3 ยท Baseline and prompt research

Interviewed four salespeople and read 90 days of chat transcripts to build a list of 40 questions buyers actually type into AI tools. Tested all 40 across ChatGPT, Claude, Gemini and Perplexity and logged the result in a Google Sheet. Result: 0 out of 40. Competitors appeared in 31. This became the scoreboard for the entire engagement.

/03

Weeks 3โ€“6 ยท Restructure the top 12 pages

Rewrote the 12 highest-value commercial and comparison pages. Each got a 50-word direct answer block at the top, at least one comparison table, short paragraphs, and a 6-question FAQ at the bottom. Moved three product pages off client-side rendering into server-rendered HTML. Result by week 6: first citation โ€” Perplexity, on a long-tail comparison prompt, week 5, day 4.

/04

Weeks 4โ€“5 ยท Schema layer

Implemented Organization schema with sameAs links, FAQPage on every FAQ block, SoftwareApplication on product pages, Article with author and dates on 40 blog posts, and BreadcrumbList sitewide. Validated everything through Google's Rich Results Test. Result: three days of dev time. Cheapest high-leverage work in the engagement.

/05

Weeks 6โ€“11 ยท Authority and original data

Published an original survey of 180 Indian manufacturing compliance managers โ€” the only primary data in the category. Created author bio pages with real credentials for their two subject-matter experts. Claimed a Wikidata entry. Answered 14 relevant questions on Reddit and Quora without link-dropping. Result: the survey page alone accounted for 9 of the eventual 14 cited prompts. Original data is the highest-ROI asset in AI SEO.

/06

Weeks 8โ€“14 ยท Track, iterate, kill what fails

Re-tested all 40 prompts monthly. Doubled down on the comparison and "best tools for X" formats that were winning. Killed a planned glossary project after eight weeks of zero citations from similar pages.

03 โ€” Investment

What this engagement cost

Plus roughly โ‚น40,000 in one-off costs on their side โ€” the survey incentives and three days of their developer’s time.

PLAN BEST FOR WHAT'S INCLUDED MONTHLY (INR)
Starter Local & small brands Technical SEO + 4 GEO pages + schema โ‚น45,000
Authority Market leaders End-to-end AI SEO + PR + link building โ‚น1,80,000+

04 โ€” What didn't work

The honest list

A repeatable system that gets Bangalore brands from invisible to cited.

01

Glossary pages

22 definition pages published in week 6. Zero citations by week 14. AI tools already know what the terms mean; they don't need your page.

02

llms.txt

Added in week 3. No measurable change in crawler behaviour or citations. Costs an hour, does no harm, but don't expect anything.

03

Press release distribution

โ‚น18,000 spent on a syndicated release in week 7. No citations traced back to it. Cut from the plan.

04

Gemini

Slowest surface to move. Only 3 citations by week 14 against Perplexity's 8. If Gemini is your priority, budget longer.

05 โ€” Why Beta

Why this engagement worked

We diagnosed before we sold

The Cloudflare block was found in the free audit, before any contract was signed.

We measured from day zero

The 40-prompt baseline made every claim on this page verifiable.

We killed what failed

Glossary pages and press releases were cut mid-engagement rather than defended.

India-first economics

โ‚น95,000 a month against a โ‚น37 lakh pipeline is the kind of maths that works for Indian mid-market budgets.

"The first thing they found was a setting we'd had switched on for a year and a half. That was in the free audit, before we paid anything. Fourteen weeks later we're the answer ChatGPT gives for our category."
VP Marketing
B2B compliance SaaS ยท Bangalore

06 โ€” Questions

Frequently asked questions

Are these AI SEO case study results typical?

This was a strong result, helped by an existing six-year domain, decent Google authority and a client willing to fund original research. A newer domain in a competitive consumer category would more realistically reach 10โ€“15% citation rate in the same window.

A fixed list of 40 buyer questions, tested manually across ChatGPT, Claude, Gemini and Perplexity on the first Monday of each month, logged in a shared Google Sheet. A prompt counted as cited only if the brand was named or linked in the answer.

Under NDA. All metrics were pulled directly from their GA4 property, Bing Webmaster Tools and CRM, and the case study was approved by their marketing leadership before publication.

First crawler hits within 10 days of unblocking. First citation typically weeks 5โ€“8. Meaningful citation rate at weeks 12โ€“16. Technical fixes move fastest; authority work is the long tail.

Yes, and often faster โ€” local categories are less crowded in AI answers. The tactics shift towards LocalBusiness schema, Google Business Profile consistency and location-specific Q&A content.

Most of the technical and schema work, yes โ€” our 42-point AI SEO checklist covers it with free tools. The parts that are hard to DIY are original research production and disciplined monthly measurement.

This client moved to a maintenance retainer โ€” monthly prompt re-testing, quarterly content refresh and new page production. Citations decay if content goes stale, so the tracking never stops.

Want a case study like this one?

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