---
title: "Rootly's AI citation rate rose from 3% to 30% in AthenaHQ case"
url: https://seomadman.com/studies/rootly-athenahq-ai-citation-rate-case-study
section: studies
published: 2026-09-25T00:00:00.000Z
modified: 2026-09-25T00:00:00.000Z
author: Adam Hafez
topics: ["AI search"]
---

# Rootly's AI citation rate rose from 3% to 30% in AthenaHQ case

## The short answer

AthenaHQ reports that incident management vendor Rootly grew its citation rate across tracked AI prompts from 3% to 30%, and its mention rate from 7.5% to 18.3%, within months. The figures come from AthenaHQ's own tracking tool, published by the vendor, with no control group and no list of the prompts or AI assistants tracked.

## Key takeaways

- AthenaHQ reports Rootly's citation rate across its tracked prompts rose from 3% to 30%, a tenfold increase.
- The same page reports Rootly's mention rate rising from 7.5% to 18.3%, a gain of 10.8 percentage points.
- The changes were shipped across documentation, content, messaging and third-party sources, guided by AthenaHQ's recommendations.
- The case is vendor-published and self-reported, with no control group, so the lift cannot be separated from other marketing.
- The page calls the mention gain a 2.5x lift on non-branded prompts but never labels which prompts the 7.5% to 18.3% figure covers.

AthenaHQ, a vendor of AI search tracking software, published a case study on Rootly, an AI-native
on-call and incident management platform. It reports that Rootly's citation rate rose from 3% to 30%
across the prompts it tracked. This is a write-up of that vendor's own account, not independent
research, and the limits below matter as much as the numbers.

## What problem was Rootly trying to solve?

Rootly already captured demand through SEO, comparison pages, integration content and documentation.
Its head of marketing, Adam Frank, says the shift was in where buyers started: with AI assistants,
asking questions such as "best incident management for Slack", "PagerDuty alternatives" or "how to
run incident retros". In his words, discovery is moving "from 'search to click' to 'ask to decide.'"

The team found that ranking in search did not guarantee presence in AI answers. Before the project,
AI discovery was mostly anecdotal: win-loss notes, sales calls and the occasional prospect who
mentioned finding Rootly through ChatGPT or another assistant. The team could not see how Rootly was
described, where it was missing from shortlists, or which sources the models drew on.

## What did Rootly change?

The team set a baseline by adding its top competitors to AthenaHQ, then aligned tracking with the
prompts that most closely mirror buyer evaluation. AthenaHQ's recommendations were turned into a
short list of improvements across documentation, content, messaging and third-party sources, which
the team shipped. The page names five steps: competitive baseline, revenue-mapped prompt selection,
authority content and docs alignment, a weekly operating rhythm, and a monthly re-baseline that
expands the prompt set.

The page does not itemise which individual edits moved the numbers, and it does not name the AI
assistants that were tracked.

## What results did AthenaHQ report?

The page reports a citation rate rising from 3% to 30% across tracked prompts, and a mention rate
rising from 7.5% to 18.3%. It separately claims a 2.5x lift in mention rate on non-branded prompts.
The timeframe is given only as "within months".

It also reports $126,076 of incremental equivalent media value, from $87,832 to $213,907 a year, and
an annual equivalent ad value of $1,169,532. AthenaHQ calculates these itself as the value of the
extra visibility. They are not revenue, pipeline or ad spend saved.

Beyond the numbers, the page says AI answers began describing Rootly more accurately and
consistently, and that AI search now sits beside SEO and paid acquisition in its demand strategy.

## Can this case be trusted as proof?

Treat it as a documented claim, not a controlled result. The figures are self-reported by the
vendor that sells the tracking tool, and no control group, prompt list or engine list is published.
AI answers vary between runs, so a tracked-prompt rate can move without any site change. The prompt
set was also expanded monthly, so later measurements may not cover the same prompts as the
baseline. Rootly's other marketing in the period is not accounted for.

The mention figures are loosely labelled. The page never says whether 7.5% to 18.3% covers all
tracked prompts or only non-branded ones. That rise is about 2.4 times, close to the 2.5x claimed
for non-branded prompts, so they may be the same measure, but the page does not confirm it.

## What should a site owner take from it?

The direction is plausible and the method is concrete: baseline against competitors, track
buyer-style prompts, fix documentation and the third-party sources models cite, then re-measure on
a fixed schedule. Keep your own prompt list stable so before and after compare like with like.

For Google specifically, its documentation on AI features says there are no additional requirements
or special optimizations to appear in AI Overviews or AI Mode. A page must be indexed and eligible
to show with a snippet, and clicks from those features are counted in the Search Console
Performance report under the Web search type, not a separate channel. The
[AI answer readiness checker](/tools/ai-answer-readiness-checker) covers page-level basics, and
[Ahrefs' 75,000-brand study](/research/ai-brand-visibility-factors-ahrefs-75k-brands) looks at which
signals correlate with brand mentions across AI assistants. Related coverage sits in the
[AI search topic hub](/topics/ai-search).

## Sources

1. [Rootly: 10x Citation Growth in AI Search with AthenaHQ](https://www.athenahq.ai/case-studies/10x-citation-rate-rootly-geo-case-study) - AthenaHQ (primary)
2. [AI features and your website](https://developers.google.com/search/docs/appearance/ai-features) - Google Search Central (primary)