Be the tool AI names when buyers ask what to use.
Software buyers now ask AI assistants to shortlist tools, compare pricing models and explain trade offs. BrandWater shows whether your product is on that shortlist, how it is described, and which sources put it there.
Quick answer: SaaS and Technology
For SaaS and technology companies, BrandWater AI measures whether Gemini, Google AI Overview, Google AI Mode, ChatGPT and Perplexity name your product when buyers ask for a tool, how they describe it, and which sources they rely on. It then turns the gaps into recommended fixes to docs, comparison and integration pages.
Where AI meets your buyer
Three moments in a software purchase, the question asked at each, and what we measure and change.
- 1
Discover
“What is the best tool for [job to be done]?”
- We measure
- Mention rate and position on category prompts
- You act on
- Clarify the category and use case language on your homepage and docs
- 2
Evaluate
“How does [your product] compare with [competitor]?”
- We measure
- Sentiment, co-mentions and which attributes get repeated
- You act on
- Publish factual comparison and integration pages the answer can cite
- 3
Decide
“Is [your product] secure, and what does it cost?”
- We measure
- Accuracy of pricing, security and compliance claims
- You act on
- Correct outdated claims at the source and re-check after publishing
The challenge
- 01
Shortlists form before your site is visited
Buyers get a handful of names from an AI answer first. If you are not among them, you may never enter the comparison.
- 02
Feature detail gets flattened
Answers compress a product into one or two attributes, often the wrong ones or out of date ones.
- 03
Docs and reviews carry the weight
For technical products, documentation, integrations pages and independent reviews often decide what AI repeats.
The questions your buyers ask
Prompts mirror how real customers phrase things. Yours are built from your own topics.
Example prompts
What is the best project management tool for a 20 person engineering team?
Alternatives to [competitor] with a good API
Which tools integrate with Slack and Jira?
How do [product A] and [product B] compare for security reviews?
What should a startup use for customer support?
How teams work with it
A repeatable cycle, from confirming the facts to verifying the result.
- 1
Confirm your product facts
Brand Intelligence records what you do, who it is for and the capabilities you want understood, with evidence from your site.
- 2
Track evaluation style prompts
Prompts mirror how buyers ask: best tool for a use case, X versus Y, alternatives to a named product.
- 3
Find what is missing
Omissions shows which confirmed capabilities and use cases AI leaves out.
- 4
Act on documentation and pages
Recommendations point to the docs, comparison and integration pages worth clarifying, for your team to approve and publish.
What to track
Mention rate on evaluation prompts
How often you appear when buyers ask for tools in your category.
Capability coverage
Whether your confirmed features and integrations are mentioned.
Documentation citation rate
How often your docs are shown as a source.
Who uses it, and what each person gets
- Head of product marketing
- A view of how positioning survives compression into a two line AI answer, with the sources behind each claim.
- Developer relations and docs
- A list of which documentation and integration pages get cited, and which are ignored.
- Growth and SEO lead
- Share of voice against named competitors on evaluation prompts, tracked over time.
- Founder or CEO
- One plain readout of whether buyers meet your product at the moment they ask for a shortlist.
A sensible first month
From first audit to a verified fix in four weeks.
Week 1
Confirm the facts
A reviewed brand record: what you do, who for, key capabilities, with evidence from your site.
Week 2
Build the prompt set
Evaluation, comparison and alternatives prompts grouped by buyer stage and platform.
Week 3
Run the first audit
Baseline mention rate, sources and omissions across the three launch engines.
Week 4
Choose the first actions
A short list of recommended doc and page changes, each with an owner and a re-check date.
A suggested sequence, not a guarantee of results. Timing depends on your approvals.
Platforms to watch
Technical buyers use several assistants. Claude shows a high share of software focused use in India per Anthropic's data, and Perplexity exposes the sources behind each recommendation.
Three mistakes to avoid
Tracking only your own name
Buyers rarely type your brand. Measure category and alternatives prompts, where the shortlist is formed.
Treating one answer as the truth
Answers vary by run and platform. Look at rates over many runs, not a single screenshot.
Fixing the site but not the sources
AI often leans on reviews, directories and documentation. A change that ignores them may not move the answer.
Common questions
Does this replace product marketing?
No. It shows how your existing positioning is being reflected in AI answers, so marketing can act on evidence.
Can I track integrations and use cases separately?
Yes. Topics and intents are configurable, so integrations, use cases and comparisons can each be measured.
Which platforms matter most for software buyers?
It depends on your buyers, so measure several. Perplexity shows sources openly, Claude is widely used for technical work, and Google AI Overviews reach people who never open an assistant.
How do we track us versus a named competitor?
Add the competitor as a tracked brand. You then see co-mentions, share of voice and which sources favour each of you.
Do we need to change our product docs?
Only where the audit shows a gap. Recommendations name the specific page and the claim to clarify, and nothing is published without your approval.
Can this show pricing accuracy?
Yes. Pricing and plan claims can be tracked as facts, so wrong or outdated figures in answers are flagged for review.
See how it works for saas and technology.
Start with a first audit. We show where you appear, who is named instead, and what to fix first.