Most SaaS growth is bought. Paid acquisition scales linearly with spend, and the moment you stop, pipeline stops. Organic is the only channel where the cost per acquisition falls over time instead of rising.
I run search programs for SaaS companies directly, so a senior specialist does the work rather than an account manager relaying it. Every recommendation is judged on trials, demos and revenue, not rankings.
Agencies publish high-volume top-of-funnel content aimed at people who will never buy, then report on traffic growth. Meanwhile the comparison, alternative and use-case searches that actually convert sit unclaimed.
Recurring revenue means acquisition cost is judged against lifetime value, so one customer justifies a lot. Buyers are also research-heavy and compare relentlessly, and much of that research now happens inside AI assistants.
Target the searches attached to buying decisions — comparisons, alternatives, integrations, specific use cases and problems — and make sure AI tools name your product when someone describes what they need.
Software buying follows a well-worn path. Coverage is built at each point, in Google and in the AI tools now answering these questions.
Someone realises their current process or tool isn't working and looks for options. This is now heavily AI-mediated, with assistants shortlisting before any site is visited.
“best tools for [job]”, “how to [solve problem] software”
They shortlist products. Comparison content, alternatives pages, reviews, integrations and whether an AI tool names you decide who makes the list.
“[competitor] alternative”, “[product] vs [product]”
One product gets the trial or demo. Clear pricing, obvious fit for their use case and credible proof convert the sign-up.
“[product] pricing”, “[product] review”
Scope follows your business, your market and your service mix. These are the components a program draws on.
Working out which use cases, segments and comparison searches carry the most revenue, then building coverage around those first rather than chasing volume.
The highest-converting content in SaaS and the most commonly neglected: honest comparisons, alternatives pages and integration content.
Pages that match how buyers describe their problem rather than how you describe your features, which is also how AI tools match you to a query.
Crawling, indexing, site architecture and speed, plus handling app subdomains, docs, changelogs and programmatic pages properly.
Structured data and consistent, corroborated facts so AI assistants name your product when someone describes their requirements.
Coverage, review platforms, directories and mentions on the sources both buyers and AI models draw on when shortlisting software.
A business doesn't run on traffic. It runs on the work that gets won and what that work is worth.
LeadSight, my own attribution software, ties enquiries and closed work back to the channel that produced them, so your monthly report shows what SEO returned in dollars rather than which keywords moved.
How LeadSight works →I keep my client list small, and SaaS SEO works best where lifetime value justifies building a compounding channel.
Where you know who you sell to and what problem you solve, which makes targeting far sharper.
Where CAC keeps climbing and pipeline stops the day spend does.
Where buyers actively compare and there are established competitors whose alternatives searches are winnable.
That's the version that mostly stopped working, and AI Overviews have finished it off. High-volume informational content now gets summarised without a click. What still converts is comparison content, alternatives pages, use-case pages and integration content — lower volume, dramatically higher intent, and rarely done well.
It will reduce your informational traffic, and you should plan for that. What it doesn't reduce is the value of being the product an assistant names when someone describes their requirements. That's now a distinct channel, and it depends on clear positioning, consistent facts and third-party corroboration.
Sometimes, and carefully. Programmatic works when each page genuinely answers a distinct query with real data. It fails, expensively, when it generates thousands of near-identical templated pages, which Google has been discounting for years. I'll tell you honestly which side of that line your idea falls on.
They're complementary, and organic should reduce your dependence on paid over time rather than replace it overnight. The useful comparison is trajectory: paid CAC tends to rise as you scale, organic CAC falls as the work compounds.
Yes, and that's often the best arrangement. If you have marketers and developers who can execute, a consulting engagement gives them senior direction without you hiring a specialist you may not need full-time.
Expect early movement in two to three months on technical and comparison content, with meaningful pipeline building from there. B2B sales cycles then add their own lag, so judge it over two to three quarters.
Send your domain through and I’ll review your site, your competition and your AI visibility before we speak. No obligation, and a straight answer on whether it’s worth the spend.