B2B Keyword Research: Finding Terms With Buyers Behind Them

B2B keyword research breaks the consumer playbook in one specific way: the terms worth ranking for often have monthly volumes low enough that tools report them as zero. A page ranking first for a 40-search-a-month term used only by buyers beats a page ranking fifth for a 9,000-search term used mostly by students.

This is for marketers whose keyword tool keeps suggesting terms that bring traffic and no pipeline.

Volume Is the Wrong Primary Filter

Work an example. "Marketing automation" has enormous volume and is searched by students, job seekers, consultants, journalists and the occasional buyer. "miEdge alternatives" has almost none and is searched by exactly one kind of person: a benefits broker currently paying for a tool and considering switching.

One of those converts. Twenty terms like the second one outperform one term like the first, and they are individually far easier to rank for because nobody has written a serious answer.

So filter on who searches it, not on how many. The question to ask about any keyword: can I describe the person typing this, and are they someone who could buy?

Where the Real Terms Come From

Not from a keyword tool first. Tools are good at expanding a seed list and bad at generating one, because they only know terms that already have measurable volume.

Five sources that produce better seeds:

• Your own sales calls. The words prospects use to describe the problem, which are almost never the words your marketing uses. Transcripts are a keyword goldmine nobody mines.
• Support tickets and inbound questions. A question asked three times is a page.
• Competitor names, in every combination: "X alternatives", "X vs Y", "X pricing", "X reviews". These are the highest-intent terms in any B2B category.
• The mechanism, not the category. Buyers search for the thing they are trying to do ("how to read a Form 5500 for prospecting") more often than for the category name.
• Search Console, filtered to queries where you rank 8 to 20. Those are terms Google already thinks you are relevant for, and moving from 12 to 4 is far cheaper than ranking something new.

Judging Difficulty Honestly

Difficulty scores are a proxy for the backlink profile of current results and they miss the thing that matters most in B2B: whether anyone has actually written a good answer.

Search the term and read the top five results. If they are directory listicles, thin vendor pages, or articles that clearly do not understand the mechanism, the term is winnable regardless of what the difficulty score says.

We found exactly this on "miEdge alternatives": the SERP is G2 and Capterra pages recommending Tableau as a substitute for benefits broker prospecting software, which tells you no human in the category reviewed it. A real answer wins that.

Conversely, a low difficulty score on a term where the top results are genuinely excellent is a trap.

Group by Intent, Not by Topic

Terms sort into four intents and each needs a different page:

• Problem-aware, "why do cold emails go to spam". Educational guide.
• Solution-aware, "cold email deliverability tools". Comparison or category page.
• Vendor-aware, "X alternatives", "X vs Y". Comparison page, written honestly including what the competitor does better.
• Ready, "X pricing". Your pricing page, with an actual number on it.

Most B2B sites have plenty of the first and almost none of the third and fourth, which is backwards: the last two are where the buyers are and where the competition is weakest, because writing them requires admitting competitors exist.

One Keyword, One URL, Written Down

The discipline that prevents the most common failure in B2B content: a file that assigns exactly one primary keyword to each URL, consulted before commissioning rather than after publishing.

Without it you get what this blog had: twelve posts about LinkedIn Events, seven about a feature LinkedIn discontinued, all competing with each other so none ranked. The failure mode is always the same: someone briefs a writer on a topic instead of a keyword.

Ours is a module the build reads, so a duplicate assignment fails the build. A spreadsheet works just as well as long as somebody opens it.

Write for Extraction Now

Buyers increasingly start with an AI assistant rather than a search results page, and what gets cited is a self-contained passage: a section that answers one question completely, with a specific number and a named source.

That changes keyword research slightly. Question-form keywords matter more than they used to, because they map directly onto the shape of an extractable answer, which is also why an FAQ block with literal questions is now the cheapest ranking asset you can add to a page.