SaaS marketing teams often build content programs around top of funnel queries because the volume looks good in Ahrefs and the topics are easy to brainstorm.
But top of funnel traffic doesn’t convert well because the people clicking are researchers, students, competitors auditing your content, and prospects who aren’t close to a buying decision.
The LLM shift has made this worse. A buyer used to type "what is field service management software" into Google, land on your blog, learn the basics, and maybe come back later.
Now they type it into ChatGPT and get an answer that names no vendors and links to nothing.
So the user never visits your page. The TOFU keyword you optimized for has stopped sending traffic at all.
This article walks through the method I use to find and write bottom of funnel content for B2B SaaS clients that ranks, is visible in LLMs, and converts. I will also give examples from a project that saw one of my clients go from 35 organic demos a month to 210 in a few months.
Key takeaways
- BOFU keywords are identified through sales calls and internal team conversations first, not keyword tools. The tools come after you have the buyer language.
- Every keyword on your list should pass three filters: search demand, product relevance, and ICP pain-point alignment. Miss one and the content won't convert regardless of volume.
- Content converts when the buyer recognizes their own situation in it. That means writing with their language, their day-to-day pain, and the specific outcomes they care about.
- Track pipeline, not traffic. Add a "how did you hear about us" field to your demo form and set up URL-level conversion events so every BOFU page ties back to revenue.
What bottom of funnel content means for B2B SaaS
A bottom of funnel keyword is one a buyer types when they are actively comparing options or evaluating a specific solution. Here are some examples:
- "Best [category] tool for [industry]." Example: best CMMS for food manufacturing.
- "Best [category] tool for [use case]." Example: best work order software for distributed maintenance teams.
- "[Product A] vs [Product B]." Example: Limble vs UpKeep.
- "[Competitor] alternatives." Example: Fiix alternatives.
- "[Category] software for [vertical]." Example: maintenance software for packaging plants.
- Role or persona modifiers. Example: CMMS for maintenance managers.
These are the bottom of the funnel content examples that actually move pipeline.
How to find bottom of funnel content keywords for B2B SaaS
Every keyword research process I run for B2B SaaS clients follows the same four steps. Most marketing teams skip the first three and jump straight into keyword tools. That's how they miss the bottom of funnel terms that match their product, their ICP, and the language their buyers use.
1. Start with sales call recordings
I pull around ten recent sales call recordings and run them through an AI tool that can transcribe and pattern-match across the set.
I look for:
- Recurring pain points
- Common objections in active deals
- Industries that keep showing up
- Competitor mentions
- The specific words prospects use to describe what they need
For the CMMS SaaS client, this exercise produced authentic buyer language I would never have written on my own. Phrases like "we are still tracking work orders on paper." Or "our techs in the field can’t see a machine's maintenance history until they call back to the office."
That language went straight into the BOFU content. It also surfaced the verticals (food manufacturing, packaging, industrial equipment) that became the basis for industry-specific BOFU pages.
2. Talk to the sales, customer success, and product teams
Internal team conversations give me the context the calls do not capture.
I sit with the sales team and ask questions like:
- What situations or circumstances on a call tell you this lead will close?
- Which competitors keep winning the deals we lose?
- What was the most common reason recent buyers gave for choosing us?
- Out of all product features, which one or two seem to seal the deal?
The answers to these questions surface real buying triggers that keyword tools can't show you.
Then I talk to customer success:
- Who are your best customers and why?
- What are the most used features?
- What problem were those customers trying to solve when they first found the product?
Customer success knows which use cases stick and which ones churn. That information tells me which product angles to lead with in the content and which ones to leave out.
Without these conversations, you end up guessing what buyers care about. Your content sounds reasonable but doesn't resonate with anyone who's actually in a buying cycle.
3. Open the keyword tool with buyer language as seed terms
Only now do I open Ahrefs. The seed terms are the exact words from the sales calls and the competitor names that came up in active deals. From those seeds, I expand into comparison terms, alternatives, "best X for Y" modifiers, industry modifiers, and use-case modifiers.
Every keyword on the final list has to hit three criteria at once:
- Search demand
- Product relevance
- ICP pain-point alignment
If a keyword misses one of the three, I cut it regardless of volume.
A keyword with only 30 monthly searches that hits all three usually outperforms one with 3,000 searches that misses one.
4. Filter by domain authority and start where you can win
Most B2B SaaS clients I work with have a domain authority somewhere between 20 and 45. They can’t rank head-to-head against established category leaders on the highest-volume comparison terms.
So I do not try. I start where they can win fast.
The target is low keyword difficulty, decent intent-rich volume, and comparison or alternative patterns where the SERP is not yet locked down by giants.
For the CMMS SaaS client, the first 20 BOFU pages targeted keyword difficulty scores between 5 and 20. Several ranked in the top three within days. Once the domain has wins behind it, I climb the difficulty ladder.
By month 12 we were ranking on keywords with KD scores in the 40s and 50s, including some that the bigger directory sites used to own.
Writing bottom of funnel content that ranks and converts
If your bottom of funnel content ranks and is visible in LLMs, but conversions are still flat, it’s not doing its job.
A page converts when the buyer recognizes themselves in it. The writing has to layer their language across the problem, the solution they want, the features that matter, the benefits, and the underlying pain points. The more specific the writing, the more the buyer feels you understand their world.
In practice that comes down to four moves:
- Open with their actual situation: Use language that sounds like something they would say themselves, or that they would recognize from their own internal conversations.
- Describe the pain with day-to-day specifics: What the broken workflow looks like, what the current workaround is, and why that workaround stops working past a certain size.
- Position the product as the answer to that specific pain: Connect the feature to the pain, rather than describing the feature on its own terms.
- Layer in benefit language tied to real outcomes: Hours saved or deals closed, the metrics the buyer is on the hook for.
- Give real examples: Walk the reader through a specific scenario where the outcome played out. A story sticks.
I break down how this works in practice across multiple SaaS niches in my piece on SaaS content marketing agencies.
How to get your BOFU content and brand recommended and cited in AI search
The buyers who used to find your comparison post on Google now ask ChatGPT or Perplexity for the same comparison. If your brand and your content don’t show up in those answers, you are invisible to those buyers.
AI search visibility comes down to content and brand work, more than technical SEO. I have written more on how AI is shifting B2B SEO for agencies in a separate piece.
If you want to know how to maximize bottom of funnel content for AI visibility, four things decide whether LLMs pick your page or someone else's.
Specificity matters because buyer prompts are contextual
Some buyers do search broad category terms. But the highest-intent prompts, the ones from buyers closest to a decision, are far more contextual than what most marketers plan for.
The prompt looks like:
"We are a 40-person company that has been tracking maintenance in Excel sheets. We have outgrown it. We need software that handles work order dispatching, has a visual calendar, and integrates with QuickBooks. What should we look at?"
A page built around the marketer's guess can’t answer that prompt. A page built from sales call insights can.
This loops back to step one of the keyword research method. The contextual prompts your buyers use in LLMs come from the same data as the language patterns your sales calls surface, just from a different angle.
Brand mentions on third-party pages drive visibility
LLMs cite the brand names that consistently appear across third-party sources for your category. Review platforms, comparison sites, industry directories, listicles, podcast notes. The model is doing what a buyer would do: triangulating across multiple sources to figure out who is credible in the space.
The work here is two steps:
- Identify which third-party pages LLMs pull from for queries that you want to show up for.
- Get your brand mentioned on those specific pages. This is closer to PR and partnership work than to traditional link building.
Entity clarity decides whether the LLM trusts your positioning
Your brand positioning has to be consistent across the sources LLMs read. For example, If your site says you serve SMBs, and a third-party review site describes you as an enterprise platform, the model sees a contradiction.
This impacts whether an LLM recommends your brand because it doesn’t know which version of your brand to surface.
Measure visibility across angles instead of single prompts
A lot of SEO teams track individual prompts like "best field service management software" in AI visibility tools and obsess over whether they show up. The problem is that one prompt tells you almost nothing.
Real buyers prompt differently depending on where they are in the buying cycle. Some search by category. Some search by use case, like "HVAC dispatching software." Some describe their exact situation: "We're a 150-person HVAC company managing scheduling through spreadsheets. We need software that handles dispatching, route optimization, and invoicing in one place."
That last prompt produces a completely different LLM response than "best field service software." No tracking tool can simulate every version of that conversation. And if you're only tracking category prompts, you're seeing a fraction of your actual visibility.
So how do you build a good prompt list? Take your existing keyword rankings and combine them with transcripts from about 10 sales calls. Your keywords tell you what people search on Google. Your sales calls tell you how buyers describe their problems. The overlap is where your best prompts live.
Once you have that prompt list, the goal is to make sure each BOFU page covers the topic with enough depth that it can answer multiple versions of how a buyer might ask.
For a page targeting "best CMMS for food manufacturing," that means covering:
- The compliance and audit pain points specific to food manufacturing
- What the workflow looks like at different team sizes
- The integration requirements buyers in that vertical ask about on sales calls
- The switching scenario from whatever they're currently using.
Tying bottom of funnel content to pipeline metrics
AI search has made attribution messy. A buyer researches your category in ChatGPT, gets a recommendation, searches your brand on Google, and books a demo from the homepage. GA4 calls that direct traffic and the page that drove the decision is invisible.
You should add a "How did you hear about us?" field to every client's demo booking form. It catches the touchpoints analytics tools miss and gives you a holistic view of whether SEO/AEO is driving demos.
For the traffic that does come through organic search, make sure you’ve set GA4 conversion events at the URL level so you can see exactly which blog post brought the visitor and whether they booked a demo.
For AI visibility, you can track brand mentions across LLMs to see which platforms cite and recommend your brand, how often, and against which competitors. That fills in the picture GA4 can't show you.
Start with one bottom of funnel keyword this week
If you are reading this and your blog is bringing traffic without demos, the action this week is to ship one bottom of funnel post.
Pick one buyer-stage keyword. Run it through the three-criteria filter: search demand, product relevance, ICP pain-point alignment. Pull five recent sales call recordings and surface the specific buyer language they use to describe the problem your post will solve. Write the post and publish it.
If you want help identifying the right BOFU keywords for your SaaS and mapping the content to pipeline, that's what I do. The 35-to-210 demo result on the CMMS SaaS account came from running this exact process.
Book a free strategy call and I'll walk you through what it looks like for your product and ICP.
Frequently asked questions about bottom of funnel content
How long should a bottom of funnel blog post be?
It depends on the keyword intent. Comparison and "best X for Y" queries usually need 1,500 to 3,500 words to cover what the buyer needs to make a decision. Alternatives and "vs" pages can be shorter when focused. The principle is to cover what the buyer needs to evaluate. The word count follows the substance.
Should I write bottom of funnel content if my SaaS has a low domain authority?
Yes, and you should start there. Low-difficulty BOFU keywords are where a low-DA SaaS can win first. That is what I did with the CMMS SaaS client when they started in the low 30s. Build ranking and authority on the easier comparison terms first. Then climb the difficulty ladder once the domain has wins behind it.
How long until bottom of funnel content drives demos?
An individual BOFU post can rank within one to three weeks for low-difficulty keywords. The pipeline impact grows as more BOFU pages are published.
Can I use AI to write bottom of funnel content?
AI is fine when used smartly with a human in the loop. It can’t replace sales call insights or the specific buyer language that comes out of real conversations. The CMMS SaaS client's previous content strategy was AI-generated articles with no differentiation. That is why the blog produced traffic but very few demos. Use AI for the structural lift. Use sales calls and SME conversations for everything that turns the content into pipeline.
7+ years in B2B content marketing and SEO. I help brands rank on Google, get recommended by LLMs, and turn content into pipeline. For agencies, I lead client accounts end to end as a fractional SEO strategist. I also build AI-powered workflows for content teams who want to do more with less. When I’m not in the trenches, I’m probably watching cricket.