One thing I’ve noticed while working with different SaaS SEO projects is that most content strategies start almost the same way.
You do keyword research around the core topic.
Then competitor keyword research.
Then classify keywords into:
- TOFU/MOFU/BOFU
- awareness stages
- solution aware
- product aware
- problem aware
Then eventually build:
- homepage
- feature pages
- integration pages
- use case pages
- comparison pages
- blogs
- webinars
- whitepapers
- case studies
- event pages
And honestly this works. This is basic SaaS SEO and it works.
But one thing which has worked very well for me beyond traditional keyword research is using real sales call data.
Sales call data is underrated for SEO
In my experience, sales call data is very important because there you have real customer conversations.
You understand:
- what prospects actually need
- how they found you
- why they came to you instead of competitors
- what comparisons they are making
- what exact requirements they have
And during demos and conversations, they naturally reveal pain points.
The interesting part is:
many of the questions and language patterns they use never show up inside Ahrefs or Semrush.
Sometimes people consistently ask for something, but SEO tools show zero search volume.
That does not necessarily mean the topic is useless.
One thing sales calls help identify
Sales calls also help identify whether you are attracting the correct ICP or not.
For example:
If prospects ask for features that your SaaS actually provides, then probably your positioning and SEO targeting are aligned properly.
But if people continuously ask for requirements your SaaS does not solve, then somewhere your content strategy is attracting the wrong audience.
I think this is something many SEO people ignore.
Sometimes traffic is growing but lead quality is wrong.
Sales conversations reveal that very quickly.
We analyzed two years of sales call data using AI
In one SaaS project, the client had around two years of stored sales call data.
We analyzed it using AI tools.
It took a lot of time and was not fully automated, but still the insights were useful.
We found:
- repeated customer problems
- feature expectations
- industry-specific workflows
- niche use cases
- search topics that did not even appear in SEO tools
And this was interesting because traditionally an SEO person might say:
“There is no search volume so no point creating content.”
But I don’t fully agree with that anymore.
Not every page exists for organic traffic
Sometimes these insights can simply enrich existing content.
For example:
you realize customers repeatedly ask about a specific workflow or use case.
Then instead of creating a completely new page, you update:
- feature pages
- use case pages
- blogs
- integration pages
This improves topical depth and makes content closer to real customer conversations.
But sometimes the insight is important enough that it deserves its own page.
Even if there is no search volume.
That page could be:
- a feature page
- use case page
- integration page
- healthcare page
- workflow page
- support page
The interesting thing is:
sometimes these pages help conversions even without organic traffic.
A real example I noticed
One SaaS project was suddenly getting healthcare leads.
But the strange thing was:
we barely had healthcare-related content.
We had only recently created a healthcare page and it was getting almost no direct organic traffic.
So I checked GA4.
What was happening was:
- users were landing on other pages
- then navigating internally
- then discovering the healthcare page
- then converting
So even though that page was not ranking properly, it was still helping users self-qualify.
That was a very interesting insight for me.
Because sometimes SEO people only think in terms of:
- rankings
- impressions
- clicks
But some pages exist mainly to improve conversion confidence.
Navigation matters here
Another thing I noticed:
If sales calls repeatedly reveal an important feature/use case, then sometimes that page should be added directly into:
- header navigation
- footer navigation
- internal links
- feature menus
Even if keyword tools don’t show meaningful volume.
Because users visiting your website may still want reassurance that you support that workflow.
AI can help, but only if you understand the industry
People are correct when they say AI can analyze sales calls.
But honestly if you don’t deeply understand:
- the industry
- the ICP
- the workflow
- the SaaS product
then the output becomes superficial very quickly.
AI helps speed up analysis.
But understanding what insight actually matters still requires domain understanding.
Another thing I started doing
Sometimes I also look at CRM lead descriptions.
Especially detailed leads where users explain their exact problems.
Then using tools like:
- OpenAI ChatGPT
- Anthropic Claude
I try to reverse engineer:
“What kind of search intent probably brought this person here?”
Then I check:
- do we already have content for this?
- is the positioning clear?
- are we missing a use case?
- should this be added somewhere in navigation?
- should we create supporting content around it?
I’ve found this especially useful for long-tail B2B SaaS topics where keyword tools are often incomplete. So, analyzing sales call data is also helpful in improving your SaaS content plan.
Final thought
I still think keyword research is important.
But real customer conversations are probably more valuable than many SEO dashboards.
Because sales calls reveal:
- real language
- real objections
- real workflows
- real buying intent
- real pain points
And many times those insights never appear inside keyword tools.