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How B2B software buyers research vendors in Google and ChatGPT

Buyers shortlist software before they talk to sales. What they search in Google and ChatGPT at each stage, and what your content should do there.

Key takeaways
  • Buyers move through five stages before they ask for a demo: problem, approach, shortlist, comparison and validation.
  • Most SaaS content covers only the problem stage. Comparison, pricing and security pages sit closer to revenue and are often missing.
  • AI assistants compress the research into one conversation, drawing on review sites, comparison articles, forums and vendor pages.
  • Build the plan from real buyer questions from sales and support, sort them by stage, and start at the bottom of the funnel.
  • Measure each stage differently, and ask buyers how they heard about you to catch what analytics misses.

B2B software buyers research in stages. They name the problem, weigh the ways to solve it, build a shortlist, compare vendors and check the risks, and they do most of it on their own in Google and in AI assistants like ChatGPT before anyone talks to sales. Your content has to meet them at each of those stages with a page that answers that stage's question better than anything else they'll find, or you won't make the shortlist.

That sounds obvious. In practice, most SaaS content sits at one stage, usually the first, and leaves the rest to review sites and competitors. Here's how I map the stages, what buyers type at each one, and what your content should do there.

The research happens before the demo request

By the time someone books a demo, they've usually read the comparisons, the how-to guides and the reviews. The demo request is the end of the research, not the start. If your company wasn't in the material they read, it wasn't on the list they brought to the call.

Two things make this harder than it used to be.

  • More than one person is researching. A software purchase usually involves a small group: the person with the problem, the person who owns the budget, and someone from IT or security. Each of them searches for different things.
  • Research is split across two kinds of tools. Buyers still use Google to scan options, visit vendor sites and read reviews. More and more, they also ask ChatGPT, Perplexity or Gemini to summarize a category, suggest vendors or compare two products. Google's AI Overviews now do some of that summarizing inside the search results too.

Your content needs to work in both places, for more than one reader.

The five stages and what buyers type at each

Say a SaaS company sells payroll software to mid-sized Canadian companies. Here's what its buyers search for as they move from problem to purchase, and what the company's content should do at each step.

1. Problem: "something isn't working"

The buyer doesn't know they need new software yet. They know payroll takes too long, or errors keep reaching employees. They search for things like "how to reduce payroll errors" or "why does payroll take so long every month".

What your content should do: explain the problem accurately and give practical help, whether or not the reader ever buys. Explain what causes the problem and how teams fix it. Mention your product where it's genuinely part of the answer, not in every paragraph. That's also what Google says its ranking systems are designed to prioritize: content created to benefit people, not content created to manipulate rankings.

2. Approach: "what are my options?"

Now the buyer is weighing ways to solve it. "Outsourced payroll vs payroll software." "Do we need a PEO or just better software?" This is where they decide which kind of vendor to look for.

What your content should do: compare the approaches honestly, including when yours isn't the right fit. A page that admits a very small company may be fine with a spreadsheet and an accountant earns more trust than one that pretends every company needs software.

3. Shortlist: "who should I look at?"

The buyer searches the category: "best payroll software for mid-sized companies" or "payroll software for companies with staff in several provinces". In ChatGPT, they ask something like "What payroll software should a 200-person company in Ontario consider?" and get a handful of names back.

What your content should do: make it obvious who you're for. Category, use-case and industry pages should state plainly what you do and for whom. Just as important, you need to appear on the third-party lists and review sites that rank for these searches, because that's where buyers and AI assistants both look.

4. Comparison: "how do these stack up?"

With a shortlist in hand, the buyer compares. "Vendor A vs Vendor B." "Vendor A alternatives." "Vendor A pricing." "Does Vendor A integrate with QuickBooks?"

What your content should do: answer the comparison questions yourself, and fairly. Build comparison and alternatives pages that are specific about the differences. Explain your pricing model, even if you don't publish numbers. Give each important integration its own page. If you leave these questions to competitors and review sites, they'll answer them for you.

5. Validation: "what could go wrong?"

Before signing, the buyer and their colleagues check the risks. "Vendor A reviews." "Vendor A implementation time." "Is Vendor A SOC 2 compliant?" "Vendor A problems."

What your content should do: remove doubt. Publish a security page that answers the questions IT will ask. Explain what implementation involves and who does what. Write case studies with real detail about the customer's situation. Keep your help docs public and indexable, because buyers read them to see what using the product is actually like.

How ChatGPT changes the picture

AI assistants compress the stages. A buyer can go from "why does payroll keep going wrong" to a shortlist of vendors in a single conversation. That conversation draws on sources: review sites, comparison articles, forums, documentation and a few vendor pages. If those sources don't mention you, the answer won't either, however well you rank in the blue links.

That changes a few priorities:

  • Third-party mentions matter more. Being named on the review sites and comparison articles that assistants draw on for your category is part of the job, not a PR extra.
  • Pages need to answer one question clearly. A page that says who the product is for, how pricing works and what it integrates with, in plain sentences, is easier to quote than a page built around a slogan.
  • Facts need to match everywhere. If your site, your review profiles and your partner listings describe you differently, the answer gets muddled.

This is the focus of my AI search optimization work, which starts by running the prompts buyers are likely to use and recording what each assistant cites.

Map your content to the stages

Here's the process I use to turn all of this into a content plan.

  1. Collect real buyer questions. Sales call notes, win-loss reasons, support tickets and onboarding questions are better inputs than a keyword tool on its own.
  2. Sort each question by stage. Problem, approach, shortlist, comparison or validation. Some questions fit more than one, so pick the stage where the answer matters most.
  3. Check who answers it today. Search each question in Google and ask it in ChatGPT or Perplexity. Note which pages rank and which sources get cited.
  4. Pick the right page type. Problem questions suit guides. Shortlist questions need category and use-case pages. Comparison questions need comparison pages. Validation questions need security, implementation and pricing pages.
  5. Start at the bottom. Comparison and validation pages sit closest to revenue, and they're often the ones missing. Fill those gaps before adding more top-of-funnel posts.
  6. Refresh before you create. If a page already half-answers a question, improving it is usually faster than starting a new one.

Where most SaaS content falls short

  • Nearly everything targets the problem stage, so the blog gets traffic that rarely turns into demos.
  • There are no comparison pages, because someone worried that naming competitors looks aggressive. Buyers compare anyway, just on someone else's site.
  • The pricing page says "contact us" and nothing else, so buyers can't tell whether you're in range.
  • Case studies are all praise and no specifics, so they don't help anyone judge fit.
  • Product pages are written for people who already understand the product.
  • Structured data is missing or generic, so search engines and assistants have to guess what each page is. Schema markup written for each page type fixes that.

What to measure at each stage

One number won't tell you whether this is working. I look at different signals for different stages.

  • Problem and approach: impressions, new ranking terms and engaged visits. These tend to move first.
  • Shortlist and comparison: rankings for category and comparison searches, and how often you're mentioned or cited when a consistent set of prompts is run in AI assistants.
  • Validation: visits to your pricing, security and implementation pages, and demo or trial sign-ups from organic search.

Add a "How did you hear about us?" field to your demo form, too. Analytics can't always see that a buyer first met you in a ChatGPT answer, but the buyer can tell you.

Where to start

List the comparison, pricing and security questions your sales team hears every week, then check whether your site answers each one clearly. Those gaps are usually the shortest route from search to pipeline. If you'd like help building the full plan, from buyer questions to briefs to published pages, that's what my B2B SaaS SEO and content strategy retainer covers. Get in touch and tell me where your content stands today.

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