For SaaS marketing teams
What ChatGPT tells buyers before your demo call
Your category gets summarised by assistants every day, out of review profiles and forum threads you do not control. hyperank reads those answers in full and shows which sources produced them.
What changed
A software buyer used to arrive with a shortlist built from ten open tabs. Now the shortlist arrives already made. Someone types a question about their team size, their budget and the stack they are stuck with, and an assistant returns three product names with a sentence of reasoning for each. The evaluation you thought began on your pricing page began somewhere you cannot see.
The failure mode in SaaS is rarely absence. It is a description that was true two releases ago. An assistant quotes the per seat price you moved off last year, names a free tier you retired, or lists an integration you deprecated, and the buyer takes all of it as current because the sentence carries no date. Your pricing page is correct. The answer is not.
What your buyers ask
SaaS
“best applicant tracking system for a 50 person company”
ChatGPTAnswer stored in fullThree names get shortlisted, the rest disappear
“help desk software that doesn't charge per agent”
PerplexityAnswer stored in fullPricing model quoted from an old review
“is anyone actually happy with their project management tool”
GrokAnswer stored in fullPublic complaint threads become your product summary
“which marketing automation tools are soc 2 type 2”
GeminiAnswer stored in fullA compliance answer buyers rarely check twice
Illustration, not a recorded answer
The sources behind the answer
You cannot edit an answer, so you edit what it is built from
Where the answer comes from
Where a SaaS answer usually comes from
- G2 and Capterra profiles
- Subreddit and Hacker News threads
- Alternatives and versus articles
- Your own docs and changelog
- YouTube demos and teardowns
Most of that list is written by other people, on a cadence you do not set. Citations are aggregated per domain per engine with the position they appeared in, so you can see which of those pages is doing the work and which one is still repeating a claim you stopped making.
Read
Read the answer, not a score
Every response is stored in full, with its timestamp and the sources it cited. You can open a question from six weeks ago and read it beside today's, which is how you tell a reworded sentence from a real shift in how the engines describe your product.
- Full answer text, kept with its timestamp
- Sentiment scored per answer, clustered weekly into themes
- Coverage across twenty six countries
Fix
Catch the version that is stale
Claim checking compares what an engine said against the facts your team has approved, and returns a verdict of correct, incorrect, outdated, unverifiable or misattributed. Where the claim can be traced, it names the cause: your own content, a third party page, or the model's own prior.
- Verdicts on pricing, tiers and feature claims
- Root cause named, not just the error
- Approved brand facts sit behind every check
Publish
Write the comparison page you lack
Query fan-out shows the sub-questions behind a tracked prompt and scores your coverage of each one as covered, partial or gap. Drafts for the gaps are generated from your own material and routed to a named approver, then published to your CMS.
- Gap list you can hand to a writer
- Reddit monitoring runs every fifteen minutes
- Nothing reaches your blog without approval
Nothing publishes on its own
A person on your team approves every word
In SaaS the person who has to sign off is usually the one who owns the pricing page. Anything naming a tier, a limit or a compliance certificate routes to a named approver and waits there until they accept it. Product marketing approves the claim, not the tool, and the publish step stays blocked until they do.
Read what an assistant tells your next buyer, in the words it used.
SaaS questions, answered
We changed our pricing months ago and assistants still quote the old tiers. Can you tell where that is coming from?
Often, yes. Every cited domain is aggregated per engine with its position, so you can see which pages keep carrying the old number. Where a claim is traceable, the check names the root cause as your own content, a third party page, or the model's own prior, and that decides whether you fix a page or go and ask someone else to.
Which engines do you actually read for a SaaS account?
The platform reads ChatGPT, Gemini, Perplexity, Claude, Grok and Google AI Overviews. How many of those run on your account depends on your plan, and Google AI Overviews is a scraped search feature rather than a model, so we list it separately. The pricing page states what each tier includes.
How do I know the answers you show me are real?
Because we keep them. Every response is stored as raw text with its timestamp and the sources it cited, and every figure in a report opens into the answer it was taken from. Nothing gets compressed into a score you cannot audit. If a number looks wrong, ask us and we will show you the stored response behind it.
Can you tell me which competitor got recommended instead of us?
Not today, and we would rather say so than imply it. You can see every tracked question where your brand was not named, read the full text of what the engine did say, and see the domains it cited, which usually makes the pattern obvious on reading. Automatic competitor extraction is not something we ship on the engines your plan runs.
Do you publish content for us automatically?
No. Drafts are generated from your own documents and approved facts, then routed to a named approver on your team. When they approve, it publishes to WordPress, WordPress.com, Ghost, Webflow, Shopify, Wix or a custom API. Until then it sits in review. Unattended publishing is how a product blog ends up describing a plan you no longer sell.
We already have an SEO tool. What does this add?
Your SEO tool tells you where a page sits in a list of links. This tells you what an assistant says when a buyer asks about your category, which sources it built that answer from, and whether the description is accurate. The technical side overlaps on purpose: crawler access, schema, llms.txt and indexing submission live here too.
Other industries
- FintechRates, fees and licensing, with an evidence trail compliance can read.
- EcommerceWhich products get named, and where an old price still survives.
- News and mediaWho gets credited for your reporting, and which stories read as current.
- Travel and lifestyleClosed venues, changed entry rules, and the threads answering on your behalf.
Ready when you are
Before your next buyer asks AI about you, ask AI about yourself
One check, four engines, about twenty seconds. We show you the answers before we ask for anything.