Building an AI answer channel for an EOR platform in a crowded category

Wisemonk was publishing consistently and still not compounding on the query that decided its category. We stopped optimising for volume and built for the two places its buyers were actually forming opinions, AI answers and community threads.

Company

B2B SaaS, Employer of Record

Problem

Wisemonk sells Employer of Record services for India, the mechanism companies use to hire Indian staff without registering a local entity. It is a considered, high-value purchase, and buyers research it hard before they ever fill in a form.

The content engine was working. Posts went out consistently, the blog grew, and almost none of it was converting into authority on the query that decided the category. Larger competitors held the positions that mattered on EOR India, and Wisemonk's topical relevance was not compounding at anything close to the rate the publishing effort deserved.

The commercial symptom was lumpy lead flow. Organic produced conversations in unpredictable bursts rather than a dependable weekly cadence, which makes a pipeline impossible to plan against. Underneath that sat a shift nobody had measured. A growing share of EOR research had already moved into ChatGPT, Perplexity and Google's AI surfaces, where Wisemonk appeared in a small fraction of answers and was completely absent from AI Overviews and AI Mode.

Baseline

We fixed the measurement before changing anything. Citations were counted across seven AI answer engines, alongside link and ranking data, as a single September 2025 snapshot. Reading it made the strategy fairly obvious.

123

AI citations across seven answer engines

4 of 7

engines that cited the brand at all

pages any engine would quote

citations in Google AI Overviews or AI Mode

Engines tracked: ChatGPT, Perplexity, Gemini, Google AI Overviews, Google AI Mode, Copilot and Grok. ChatGPT alone accounted for more than half of all citations. On the two Google AI surfaces, where the highest-intent category research happens, the brand did not appear once.

Strategy

The brief was never more content. The question was narrower and harder: what would make an answer engine, or a buyer inside a research thread, cite this brand ahead of four larger competitors selling the same service? Three moves.

Win the one page the category turns on

Rebuild the EOR India page for two readers at once. A buyer scanning to make a decision, and an engine looking for a clean, liftable answer to a specific question. Most pages serve one and quietly fail the other.

Set the format standard before publishing more

Heading structure, question-led sections and answer placement became the house standard, so everything published from then on arrived already shaped for retrieval instead of needing to be retrofitted later.

Own a room, not just a link

A dedicated Reddit community built on genuinely useful answers about hiring in India. Community threads carry unusual weight inside AI answers, and it placed the brand exactly where buyers were already comparing providers.

And what we deliberately did not do

No volume push, no assault on the head term with more blog posts, no paid spend to paper over the gap. Publishing rate was never the constraint. Raising it would only have produced more pages that engines still had no particular reason to quote.

Execution

SearchAxe delivered the work across the page rebuild, the content standard and the community. Sequencing mattered more than usual here: the landing page and the formatting standard went first, so that everything published afterwards compounded instead of joining a backlog of work to redo.

Rebuilt the EOR India landing page around the exact questions buyers ask, structured for AI snippet extraction as well as human evaluation.
Set and applied a content formatting standard covering heading structure, question-led sections and where the direct answer sits on the page.
Built topical relevance into the content plan so new posts compounded category authority rather than sitting adjacent to it.
Founded and grew a dedicated Reddit community for companies hiring in India, run on helpfulness rather than promotion.
Ran participation in the threads where buyers were already comparing EOR providers.
Built brand mentions and topically relevant placements to strengthen the authority signals engines read.
Made citation counts across seven answer engines the primary success measure, tracked monthly alongside rankings.

Results

The channel Wisemonk needed turned out not to be the one it had been optimising. Citations across AI answer engines grew more than fivefold, both Google AI surfaces opened from a standing start, and the community turned lead flow from unpredictable bursts into a weekly cadence.

Metric

Sept 2025

July 2026

Citations across seven AI engines

123

632

Pages cited in AI answers

299

AI engines citing the brand

4 of 7

7 of 7

Google AI Overviews citations

Google AI Mode citations

Copilot citations

209

Perplexity citations

135

Referring domains

329

784

Domain Rating

Source: Ahrefs. July 2026 used as the last complete month for link figures; AI citation counts captured August 2026. Ahrefs widened its AI citation coverage over this period, so some platform breadth reflects broader tracking. The engagement was scoped to AI and community discovery rather than classical traffic volume, and classical organic sessions declined over the same window.

06 · The part that transfers

Lessons for other B2B categories

Rankings stopped describing reality

Wisemonk's classical search performance and its AI visibility moved in opposite directions across the same eleven months. If rankings are the only number you watch, you will misread your own position in your category, in either direction.

Volume was never the constraint

Consistent publishing built a bigger blog, not a more citable one. Whether an engine can lift a clean answer off a page matters far more than how many pages exist to choose from.

Community threads are citation infrastructure

Answer engines lean heavily on community sources. A room built on genuine usefulness became a lead channel and a citation source at once, which no amount of conventional link building would have delivered.

One page can carry a category

For a considered purchase with a single dominant query, rebuilding that one landing page for both readers, human and machine, moved more than any batch of supporting content around it.

What clients say

Our content was getting published but not landing anywhere. Amit reworked how we format it for AI engines and our citations across all seven engines are up over 400%. The Reddit community he built now brings us leads weekly.

Aditya Nagpal Founder, Wisemonk Read the Wisemonk case study

We had thousands of pages going nowhere. Amit cleaned that up and rebuilt our landing pages. Our top three rankings are up 362% and our citations across AI engines have grown more than a hundred times.

Nan Ha Product Growth Lead, Viggle AI Read the Viggle AI case study

We came to Amit with a good product and almost no search presence. He gave our team a plan we could actually follow. Referring domains are up 183% and our first page rankings have more than tripled.

George Kurdin Co-Founder, Monk Read the Monk case study

We launched with a homepage and nothing else. Amit built the search foundation, the landing pages, the blog, the schema. Our domain rating is up 70% and we went from zero AI citations to being quoted by six of the seven AI engines.

Ahad Shams Founder, HeyOz Read the HeyOz case study

We had multiple pages fighting each other for the same terms. Amit mapped it all out, consolidated what needed consolidating, and rebuilt our service pages. Organic traffic is up 147% and our top three rankings have more than doubled.

Manjunath Thandu CEO, Zivoke Read the Zivoke case study

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