# How to Choose Long-Tail Keywords for a B2B SaaS Site > A way to pick long-tail keywords for B2B SaaS by buyer fit, page fit and sales value, plus what changes when those searches move into AI answers. Source: https://comppound.com/blog/long-tail-keywords-for-b2b-saas-how-to-choose-them (published 2026-10-30) The best long-tail keywords for B2B SaaS are specific searches that name a job, a role, an industry or a constraint your product actually serves, so choose them by how closely they describe a likely buyer rather than by how low their volume is. Low volume alone tells you very little. A rare search can come from a student writing an essay, and a rare search can come from a head of legal who has budget this quarter. The tool shows both as small numbers. Say you run a 25-person SaaS selling contract management software to in-house legal teams. "Contract management software" is the head term, and every large vendor wants it. "Contract approval workflow for legal teams under ten people" is long-tail. Few people type it, but the person who does has told you their team size, their problem and roughly what they want to buy. That second search is what this post is about. ## What makes a keyword long-tail Long-tail describes demand, not word count. The name comes from the shape of search demand: a small number of queries get searched often, and a very long list of queries each get searched rarely. Most long-tail searches happen to be several words long because specificity takes words, but a short product category with barely any demand also sits in the tail, and a four-word phrase can be fiercely contested. For a SaaS team, the useful distinction is between two kinds of tail query. Some are specific versions of a buying problem. Others are specific versions of a curiosity. "What is a redline in a contract" is long-tail and easy to rank for, and it may never produce a customer. "How to track redlines across outside counsel" is also long-tail, and it describes a process your product may replace. Both would pass a low difficulty filter, so the filter cannot be what decides. ## Where to find the ones worth writing Tools are the last place to start, because they are weakest exactly here. Keyword databases are built from samples and estimates, and very rare queries are the ones most likely to be missing or shown as zero. Google's own [Keyword Planner help page](https://support.google.com/google-ads/answer/7337243) warns that very low-volume keywords may not return results at all. A zero in a tool means the tool has no number, which is different from nobody searching. Better sources sit inside your company. Sales call recordings contain the phrases buyers use before they know your category's vocabulary. Support tickets hold the exact wording of problems. Lost-deal notes name the competitor and the missing feature. For the contract software company, a rep's notes might repeatedly mention "approvals stuck in email", which is a phrase no marketer would invent and a buyer might well type. Search Console is the second source, with one limit worth knowing. Google [leaves anonymized queries out of the table](https://developers.google.com/search/blog/2022/10/performance-data-deep-dive), meaning queries not issued by more than a few dozen users over two to three months. That removes a good part of the tail, and it explains why the rows do not add up to the chart total. What remains is still useful, since it shows the specific phrasings Google already connects to your pages. Our walkthrough of [the Search Console reports that matter for SaaS founders](/blog/google-search-console-for-saas-founders-the-reports-that-matter) shows where to look. Competitor pages are the third source. Read their integration pages, comparison pages and customer stories for the specifics they mention, then take those phrases to the search box and see what autocomplete and the results page offer. [Free keyword research tools for SaaS teams](/blog/free-keyword-research-tools-for-saas-teams) can then fill in whatever estimates exist, as a rough check rather than a verdict. ## Three questions that choose between them Once you have a list, run each phrase through three questions, in this order. First, would someone searching this ever buy from you? Read the results page. If the top results are definitions and university pages, the searcher probably wants an explanation. If they are vendor pages and comparisons, the searcher is shopping. Our guide to [reading search intent for SaaS keywords](/blog/search-intent-for-saas-keywords-how-to-read-it-and-match-it) covers this in more depth. Second, can you say something a competitor cannot? A long-tail page wins by being exact. If the contract company has a real opinion on how a small legal team should structure approvals, along with screenshots of how that works, the page has a reason to exist. If it would be a rewrite of the top three results, skip it even when the keyword looks easy. Third, does it deserve its own page? Many tail queries are the same question in different words, and each one getting a separate page is how sites end up competing with themselves. Group them first using [keyword clustering](/blog/keyword-clustering-for-saas-group-keywords-into-pages-that-dont-compete). One thorough page can pick up dozens of variations without being written for any of them individually, and a thin page per variation tends to do the opposite. ## How to write a long-tail page that earns its place Answer the specific question at the top, in the words the searcher used. Then give the reader what a generic page would leave out: the decision they face, the trade-off, the steps for their situation, and an honest note on when your product is the wrong fit. Google says plainly that it has [no preferred word count](https://developers.google.com/search/docs/fundamentals/creating-helpful-content), so write until the question is answered and stop. Link from the page to the product or feature it supports, using anchor text that describes where the link goes. Link to it from the related pages too. A long-tail page with no internal links is hard for people and crawlers to find, and it cannot pass any of its readers along to a page that sells. ## What changes for long-tail in AI answers Specific, multi-part questions are the type of thing people bring to AI search. Google describes AI Mode as especially useful for complex questions needing exploration or comparison, and says [AI Overviews and AI Mode may run several related searches](https://developers.google.com/search/docs/appearance/ai-features) across subtopics while building a response. In practice, a page clearly answering one narrow sub-question has a plausible route into an answer to a broader one, though nobody outside Google can tell you how that selection works for a given query. Two cautions keep this in proportion. The same Google page states that there are no special requirements or optimizations for appearing, beyond being indexed and eligible for a snippet, so "AI long-tail" is not a separate craft. And be skeptical of prompt-volume numbers from third-party tools: ask the vendor how the figures are gathered, and treat them as estimates. Clear, specific answers to real buyer questions are the sound bet for both channels. ## How to check whether a long-tail page worked Total traffic is the wrong test, since these pages were never going to bring much. Look at three things after the page has had time to be indexed and settle. In Search Console, filter by the page and read which queries it receives impressions for. A good page shows a spread of related phrasings you never targeted. In your analytics, check whether readers go on to a product page, a pricing page or a demo form. In your CRM, look at whether any opportunities touched the page. If the page brings impressions and no onward movement, the query was probably more curious than commercial, and that is worth feeding back into how you pick the next batch. If several tail pages in one topic produce conversations, write more in that topic. Decide by the pattern across a group of pages, because any single low-volume page will be too noisy to judge alone. Keeping that list [mapped against your other keywords](/blog/keyword-mapping-for-saas-sites-with-template) stops the next batch from overlapping the last. If you would rather have a team pick and write these against your actual sales conversations, [see how our managed SEO and GEO service works](/services/seo-growth). ## Frequently asked questions ### How long should a long-tail keyword be? There is no required length. Long-tail describes low search demand and high specificity. Most are three words or more because specificity takes words, but length alone does not make a keyword long-tail. ### Should I target keywords showing zero search volume? Sometimes. Tools estimate from samples and often have no figure for rare queries. If the phrase comes from real buyer conversations and the results page looks commercial, a zero should not rule it out. ### How many long-tail keywords should one page target? Choose one main query and let the page pick up its close variations naturally. If two phrases need different answers, they need different pages; if they need the same answer, one page is enough. ### Do long-tail keywords help with AI search? They can, since Google says its AI features may run several related searches on subtopics. Google also says no special optimization is required, so the practical work is writing clear answers to specific questions on indexable pages. ## About Comppound Comppound runs SEO and AI search for B2B SaaS companies: a person sets the plan and reviews samples and every high-risk page, and AI speeds up production. - [See SEO Growth](https://comppound.com/services/seo-growth): Buyers compare before they book a demo. Are your pages there when they do? - [See pricing](https://comppound.com/pricing): Want the content written, reviewed and published for you?