# SaaS keyword research

> A repeatable SaaS keyword research process: seed sources, four intent tiers, a pipeline value score per keyword, and a map writers can work from.

Source: https://saas-marketing.net/guides/saas-keyword-research/
Topic: SaaS SEO
Type: guide
Published: 2026-09-11
Last updated: 2026-09-11
Publisher: SaaS Marketing (saas-marketing.net)
License: CC BY 4.0. Quote or republish with attribution and a link to https://saas-marketing.net/guides/saas-keyword-research/

## Short answer

SaaS keyword research starts with seed sources a keyword tool cannot see: G2 and Capterra category taxonomies, competitor navigation links, sales call transcripts, in app search logs and support tickets. Every candidate is sorted into four intent tiers, scored on pipeline value using searches multiplied by click through rate, trial rate, close rate and gross margin adjusted ACV, then screened for cannibalisation. Volume is the last column you sort by, and the highest volume term usually loses the scoring.

## Key takeaways

- Keyword tools only report demand that already exists, which is why SaaS seed lists should start from sales calls and category taxonomies.
- Four intent tiers decide page type and priority: bottom of funnel, jobs to be done, category education and adjacent demand.
- Pipeline value per keyword is searches times CTR times trial rate times close rate times margin adjusted ACV, not volume.
- At a 12,000 dollar ACV, a 90 search vertical term can out earn a 60,000 search category head term by more than two to one.
- Screen the map for cannibalisation before approval, because two pages competing for one query is the most common self inflicted SaaS SEO wound.
- A usable keyword map has thirteen columns and a named owner per row, otherwise writers invent their own interpretation.

---

A keyword tool can only show you demand that already has a name. For a SaaS product, a large share of the terms worth owning have either no measurable volume, a volume figure rounded so hard it is meaningless, or a name your buyers use that nobody has indexed yet. Sorting an Ahrefs export by monthly searches and keeping the top 50 will reliably produce a plan that ranks for things your buyers do not search and misses the things they do.

So build the seed list somewhere else, then use the tool to size and check it.

## Where SaaS seed keywords actually come from

Six sources, in the order we work through them. None of them is a keyword tool, and together they usually produce 200 to 400 raw candidates before any filtering.

**The G2 and Capterra category tree.** Find your category page, then read the sidebar. The related categories, the sub categories and the filter facets are a taxonomy built from what buyers actually shortlist, maintained by people with a commercial incentive to get it right. `Field service management software` sitting next to `work order software` and `dispatch software` tells you those are three separate buyer vocabularies, not synonyms.

**Competitor navigation and footers.** Crawl the header, footer and sitemap of your four closest rivals. Their `/solutions/`, `/use-cases/` and `/integrations/` URL slugs are keyword research someone else paid for. The footer is often more useful than the blog, because footer links reflect deliberate architecture rather than whatever a writer felt like publishing.

**Sales call transcripts.** Pull 20 recordings from Gong, Chorus or whatever records your calls, and search for the moment the prospect describes their current process. The phrase they use is almost never your category name. One payments company we know found buyers saying `chase failed card payments` while the entire marketing site said `involuntary churn recovery`.

**In app search logs.** If your product has a search box, it is a free panel of exactly your users typing exactly their problems. Export a quarter of queries. The top 40 are usually feature names, but the long tail is job phrasing you can build content around.

**Support tickets and the help centre.** Group the last 500 tickets by topic. Anything with a volume spike has a public search equivalent. This source also tells you where the help centre may already be competing with the marketing site for the same query, which matters later.

**Reddit, Slack communities and private forums.** Search the subreddits your buyers use for `recommendations` and `alternatives to`. The threads contain both the vocabulary and the objections, and they double as distribution once the page exists. The same reading habit powers a lot of what works on [X for B2B SaaS](/guides/x-twitter-for-b2b-saas/), where the useful signal is the phrasing rather than the reach.

Export the queries report filtered to positions 11 to 30. Those are terms Google already associates with your site but does not rank you for. They are the cheapest wins on the entire map, and half of them will not appear in any competitor gap export.

## Sort everything into four intent tiers

Every candidate belongs in exactly one tier. The tier decides the page type, the priority and what you are allowed to expect from it in reporting.

| Tier | What the query looks like | Page type | Typical visitor to trial | Time to rank |
| --- | --- | --- | --- | --- |
| 1. Bottom of funnel | `rival alternatives`, `A vs B`, `best category for vertical`, `category pricing` | Comparison, alternatives, vertical page | 4 to 9% | 3 to 6 months |
| 2. Jobs to be done | `reconcile stripe payouts`, `track contractor onboarding` | Use case page, template, free tool | 1 to 4% | 4 to 8 months |
| 3. Category education | `what is revenue recognition`, `category software guide` | Guide, glossary entry | 0.3 to 1% | 6 to 14 months |
| 4. Adjacent demand | `remote team policy template`, broader role queries | Blog, resource, link asset | 0.1 to 0.5% | 6 to 18 months |

Tier 1 is where a company under 5 million dollars of ARR should spend its first two quarters. The patterns and modifiers are catalogued in [bottom of funnel keyword patterns](/guides/bofu-keyword-patterns/), and the case for building those pages before the blog is made properly in [bottom of funnel SEO for SaaS](/guides/bottom-of-funnel-seo-saas/).

Tier 4 is the one people argue about. It earns links and it builds topical association, both of which matter. It also produces almost no pipeline directly, so it should be funded from a link building budget rather than a demand generation one, and judged on referring domains earned rather than trials. Treating it as a pipeline channel is how content programmes get cancelled in month nine.

## Score every keyword on pipeline value, not volume

One formula, applied to every row before anything gets written.

**Modelled monthly value = monthly searches x expected CTR at your realistic position x visitor to trial rate x trial to paid rate x ACV x gross margin**

Then divide by effort. We use a simple effort proxy: months to reach the realistic position, multiplied by the referring domains the current top three hold. It is crude and it is still better than arguing about which term feels important.

Three rules that keep the model honest. Cap expected CTR at 20 percent even at position one, because AI Overviews and SERP features take a variable share. Use your realistic position, which for most sub DR 30 sites means position 8 to 15 on anything competitive rather than position 1. And use gross margin adjusted ACV, because an 85 percent margin and a 45 percent margin produce very different answers on the same traffic.

## A worked example at a 12,000 dollar ACV

Three real keyword shapes for a project management product selling at 12,000 dollars a year with an 80 percent gross margin. One has 672 times the search volume of another. It finishes last.

| | Category head term | Competitor alternatives | Vertical term |
| --- | --- | --- | --- |
| Example query | `project management software` | `rival alternatives` | `project management software for architects` |
| Monthly searches | 60,500 | 2,900 | 90 |
| Realistic position in 12 months | 25 | 4 | 1 |
| CTR at that position | 0.3% | 8% | 25% |
| Monthly visits | 182 | 232 | 23 |
| Visitor to trial rate | 1.2% | 6% | 9% |
| Trials per month | 2.2 | 13.9 | 2.0 |
| Trial to paid rate | 10% | 20% | 28% |
| Customers per month | 0.22 | 2.78 | 0.57 |
| Margin adjusted ARR added per month | $2,112 | $26,688 | $5,472 |
| Referring domains at the current top 3 | 140 | 9 | 2 |
| Months to realistic position | 12 | 5 | 4 |

The head term has the volume, the brand halo and the slide that impresses a board. It produces the least money, takes the longest, and needs a link budget most Series A companies do not have. The vertical term with 90 searches produces more than twice the head term's value on two referring domains and four months of patience. That pattern repeats across almost every B2B SaaS category we have modelled, which is why [vertical SaaS SEO](/guides/vertical-saas-seo/) is usually the fastest route for a company that sells into two or three identifiable industries.

**672x** How much more volume the losing keyword had than the winning one in the example above

Someone will still want the head term, because it is the category name and it feels like the flag you plant. Build it, eventually, as a pillar page that collects internal links from everything else. Just do not fund it as a pipeline play in year one and do not measure it on trials.

Model your own version rather than trusting ours. The [organic traffic forecast calculator](/calculators/organic-traffic-forecast/) takes the same inputs and produces a month by month curve, which is more useful than a steady state number when you need to tell a board when the line moves.

## Screen for cannibalisation before the map gets approved

Two pages chasing one query is the most common self inflicted wound in SaaS SEO, and a keyword map is where it gets designed in. Catch it on the sheet, not six months later in the rankings.

**Pre approval cannibalisation screen**

The help centre clash deserves attention because it is specific to software companies. Docs and support content frequently outrank the marketing page for the product's own feature names, which is fine for a customer and bad for a buyer who lands on an API reference instead of a product page. Decide which surface owns which intent and enforce it in the map.

## The columns a writer can actually work from

A keyword map is a briefing document, not a research artefact. If a writer has to interpret it, two writers will interpret it differently. These are the columns we use.

| Column | Why it exists |
| --- | --- |
| Primary keyword | One per row, exactly. Never a list. |
| Secondary keywords | Three to six variants the page should also answer. |
| Intent tier | Tier 1 to 4, which sets priority and expectations. |
| Page type | Comparison, alternatives, use case, guide, glossary, free tool. |
| Target URL | The final slug, decided now, not by the writer later. |
| Modelled monthly value | The formula output, so priority is not a debate. |
| Realistic position | Sets the CTR input and the reporting expectation. |
| Referring domains at top 3 | The link cost, which decides whether this is viable this year. |
| Search intent evidence | What the top 5 results actually are today, in one line. |
| Internal links in | Which existing pages will link to this one, named. |
| Primary call to action | Trial, demo, template download or newsletter. One only. |
| Owner and due date | A name and a date, or the row will not ship. |
| Last reviewed | For the quarterly refresh pass. |

The `search intent evidence` column does more work than its width suggests. One line saying `top 5 are all listicles from review sites, no vendor pages` stops a writer producing a product page that was never going to rank. A downloadable version with the formulas already in it sits at the [SaaS keyword map template](/templates/saas-keyword-map-template/), and [build your SaaS keyword map](/courses/saas-seo-sprint/01-keyword-map/) walks through filling one in with a real product if you would rather follow along than start from a blank sheet.

## When the tool returns zero

Category creating products get nothing back from a keyword tool, and the standard advice at that point is to give up on SEO. That is half right. You cannot rank for a category name nobody searches. You can rank for four other things.

- **The problem, not the product.** Buyers search their symptom long before they search your solution. Size demand for the symptom phrasing instead.
- **The adjacent category they currently shop in.** If your buyers are solving this with spreadsheets or with an older tool class, that older class has volume and their alternatives queries are open to you.
- **The job title plus task queries.** `How to forecast headcount as a cfo` has demand even where the tool category does not.
- **A free tool that produces the calculation people already search for.** This also earns the links that everything else on the map needs.

Sizing latent demand is genuinely hard and we are not going to pretend a formula solves it. The practical test: if the total modelled value of every viable term is under 2,000 dollars a month, SEO is the wrong first channel and should be deferred until the category name has traction. Spend the quarter on outbound or community instead, and revisit in two.

## Map the whole buying committee, including the people who block deals

Every guide tells you to map the buying committee and then produces four pages for the practitioner. The people who actually block a deal search too, and their queries are cheap because no vendor targets them.

| Role | Query shape they use | Page that answers it | Where it usually lives |
| --- | --- | --- | --- |
| Practitioner champion | `best category for job`, `how to do the job` | Use case page, template, comparison | Marketing site |
| Security reviewer | `vendor soc 2`, `product security`, `data residency` | Trust or security page with the report request form | Marketing site or trust centre |
| IT and integrations | `product api limits`, `connect product to identity provider` | Integration and docs pages | Docs, linked from marketing |
| Finance approver | `category software cost`, `category roi` | Pricing page, cost breakdown, calculator | Marketing site |
| Procurement | `vendor msa`, `category contract terms`, `vendor alternatives` | Comparison page, legal and terms pages | Marketing site |

Two of those rows are usually empty on a B2B SaaS site. Security queries carrying a company name have low volume and enormous intent, since nobody searches for a vendor's SOC 2 status casually. A trust page that ranks for `yourbrand security` saves the sales team a week per enterprise deal and costs an afternoon to build.

Add a role column to the map so this stays visible. If every row says practitioner, the map is incomplete regardless of how well scored it is.

## Three keyword types we stopped building for

Positions, so you can disagree with them deliberately.

**Broad definitional terms outside your category.** `What is project management` sends traffic and produces nothing. It is also the exact shape AI answers absorb most completely. Build glossary entries for terms inside your category where you have a product angle, and skip the rest.

**Salary, job description and certification queries.** They have volume, they rank easily, and the searcher is a job seeker. HubSpot's decline is the cautionary version of this at scale: broad audience content detached from the product stopped earning its place once Google grew stricter about relevance to the site's core subject.

**Competitor brand terms with no switching modifier.** Ranking for a rival's bare brand name brings their existing customers looking for a login page. Target `rival alternatives`, `rival pricing` and `rival vs` instead, where the modifier carries the intent.

## How often to rebuild it

Quarterly refresh, annual rebuild. The quarterly pass takes two hours: add new terms from Search Console, retire rows where the SERP shape has changed, and re-score anything affected by a pricing or conversion rate change. The annual rebuild takes two days and is only worth it after a positioning change, a new product line or a category shift.

One trigger overrides the calendar. If your ACV moves by more than 30 percent in either direction, re-score immediately, because every priority on the sheet was calculated against the old number and the ordering will have changed.

## What to do next

Spend the first hour on Search Console positions 11 to 30 and 20 sales call transcripts, not on a keyword tool. Build 60 rows, score them, and delete everything below the top 25. Then ship the top five before adding anything to the list.

If you want the tooling decisions settled first, [SaaS SEO tools](/tools/saas-seo-tools/) covers what is worth paying for at each stage. Once the map is approved, the constraint shifts to authority rather than planning, which is where [SaaS link building](/guides/saas-link-building/) picks up. The whole sequence, from map to published pages to links, runs as four sessions in the [SaaS SEO Sprint](/courses/saas-seo-sprint/), and the strategic context sits on the [SaaS SEO](/saas-seo/) pillar.

## Frequently asked questions

### How do you do keyword research for a SaaS product with no search volume?

Stop asking the tool and estimate demand from proxies. Count how many people work in the job you serve, look at the search volume for the problem rather than the category, check whether an adjacent category term exists that your buyer currently searches, and read the Reddit and Slack threads where they describe the problem. Then rank for the problem phrasing until the category name catches up.

### What is the best keyword research tool for SaaS companies?

Ahrefs and Semrush are close enough that the choice rarely matters. Ahrefs is better for competitor gap analysis and link data. Semrush is better for paid search overlap and position tracking at scale. Both miss zero volume terms, which is why Google Search Console, your in app search logs and sales call transcripts do more work on a SaaS map than either subscription.

### How many keywords should a SaaS keyword map contain?

Between 40 and 120 rows for a company under 5 million dollars of ARR. Any longer and it stops being a plan and becomes a wish list nobody executes. Each row should map to exactly one page and one owner. If two rows would produce near identical pages, merge them before the map is approved rather than after both pages are live.

### What is keyword cannibalisation and how do you check for it?

Cannibalisation is two or more pages on your site competing for the same query, which splits links and confuses Google about which to rank. Check it by exporting the Search Console queries report, grouping by query, and flagging any query where more than one URL has received impressions in the last 90 days. Fix by consolidating, redirecting or re-targeting the weaker page.

### Should SaaS keyword research prioritise volume or intent?

Intent, by a wide margin, until you pass roughly 5 million dollars of ARR. Volume only converts to revenue through a chain of conversion rates, and bottom of funnel terms convert five to twenty times better than category head terms. Sort the map by modelled pipeline value and let volume be an input to that number rather than a ranking criterion.

### How often should you redo SaaS keyword research?

Refresh the map quarterly and rebuild it from scratch once a year or after a positioning change. The quarterly pass adds new terms from Search Console, retires terms where the SERP has changed shape, and re-scores anything where your ACV or conversion rates have moved. A full rebuild is only worth the two days when the category or the product has genuinely changed.

### What is a jobs to be done keyword?

A query describing the task the buyer is trying to finish rather than the software category, such as reconcile stripe payouts or onboard a remote contractor. These terms convert better than category education terms because the searcher has a live problem, and they are frequently missing from competitor keyword exports, which makes them cheap to win.