Industries · SaaS and technology
Software buyers research in search and, more and more, in AI assistants before they book a demo. We build the pages and site structure that put your product in both, the same approach we run in our ongoing program with Constant Contact's growth team.
The search problem
Most software research happens in search results and AI answers. If your product is not in them, it is not on the shortlist.
01
Broad top-of-funnel posts bring visitors who never touch the product, while pages that match buying intent never get written.
02
Review sites and competitors own the alternatives and versus searches, so buyers hear your story from someone else.
03
Documentation and integration pages answer real questions, but often sit apart from the main site with no structure or internal links.
What we do
We start with the pages buyers read right before they choose, then build the content that feeds them.
One page per job your product does, written for the team that does it.
Honest alternatives and versus pages that explain where each product fits.
A page for each integration that explains what it does and who it is for.
Structure, linking and crawl access for help centers and developer docs.
Scaled pages built only where there is real data to make each one useful.
Tutorials and guides that show the product solving the problem being searched.
AI search for software
Buyers ask AI assistants which tool to use for a job. The answers draw on your site, review platforms and what others say about you.
Clear, quotable pages on what your product is best for and who it suits.
Matching product facts across your site, review profiles and partner listings.
Docs structured so AI coding tools read current documentation, not stale guesses.
Category and comparison prompts tracked monthly across the major AI tools.
FAQ
Pages that match buying intent: use-case, comparison and integration pages. They sit closer to a signup or demo than general blog posts, and they give later content something to link to.
Yes, when they are honest. Buyers search for alternatives late in their research, and a fair page that explains where each product fits earns trust and links.
Either can work. What matters is that docs get clear structure, crawlable content and links to product pages. For developer products, an llms.txt file at the docs root helps AI coding tools find the right pages.
We track a fixed set of category and comparison prompts in ChatGPT, Perplexity and Google AI Overviews each month, and record whether the product is mentioned, cited and linked.
SaaS
Tell us your category and your main competitors. We will show you where buyers find them and not you.