How to Test Your Startup’s Website Messaging With Low-Cost Research Tools 

Why testing your message matters

Your messaging isn’t just words on a page. It’s the difference between someone instantly “getting it” or bouncing after five seconds.

And while there are tools built for message testing (like Wynter or UserTesting), they’re pricey. We’re talking thousands of dollars for a single test—great if you’re a $50M ARR SaaS company, not so much if you’re a pre-seed founder who’s still living off oat milk lattes and optimism.

So what’s the scrappy alternative? Lightweight UX research tools.

The kind most people use for testing app screens—but that also happen to be perfect for gut-checking your messaging.

Message testing tools for startups

• Lyssna (formerly UsabilityHub): my go-to for quick B2B message tests. You can filter by job titles, industries, and even add screener questions so you only hear from the right people.
  
  
• PickFu: more of a fit for B2C, but still a solid option when you need fast feedback.

Both tools cost a fraction of other message-testing platforms. You can run a study for about $50 and get useful data back within hours.

How to test your website messaging using Lyssna

In the video above, I walk through an actual Lyssna test I ran for Spyndle (a link-building startup I’m part of). Here’s the basic approach:

1. Choose your test type.
   
   Lyssna gives you a few options:
    
   • Preference tests (which headline do you like better?)
   • Five-second tests (show your hero section, take it away, ask “what do you think this company does?”)
   • Design surveys (my favorite for messaging—upload your copy/design and ask open-ended questions).
     
     
2. Pick your audience.
   This is the most important part. Lyssna allows you to narrow it down your audience by demographics, such as role, industry, seniority, and location. That might be enough in some situations. But I recommend using screener questions to better qualify your audience.  This allows you to allow or disallow respondents based on how they answer certain questions. For example:
   
   Are you responsible for generating leads at your company?
   
   Do you write and test copy as part of your job?
   
   
   
3. Ask the right questions.
   

   Tools like Lyssna only let you include one or two open-ended questions (unlike pricier platforms such as Wynter that give you more flexibility). But for early-stage startups with early-stage messaging, that’s usually enough.

   My go-to pair of Qs is simple:

   “Please read all the copy on this page. What’s your first reaction?”
   This is deliberately broad. I’m not leading the witness; I want their unfiltered, gut-level response in their own words. Do they feel confident? Skeptical? Confused?

   “What, if anything, is unclear or off-putting?”
   This digs into the negative. You don’t just want praise; you want to know what might push your ideal customer away.

   That combination gives you a quick clarity check: you’ll hear what’s working and where the red flags are.

   
   
4. Collect ~15–20 responses.
   That’s usually enough to reach what researchers call saturation—the point where new responses stop surfacing new insights.
   
   Studies in UX research (like this Nielsen Norman Group article) show that small sample sizes uncover the vast majority of usability or clarity issues. Once you start hearing the same feedback on repeat, you’ve got enough to act on.
   
   
5. Do a quick sentiment check.
   Tag responses as positive, neutral, or negative. Look for patterns. Do people doubt your claims? Do they get the problem you’re solving? That’s your roadmap for tweaks.

Here’s what feedback looks like in practice (from feedback on the homepage for spyndle.co):

Tagging and categorizing the responses allows you spot themes and patterns. For example:

People liked the problem statement.
Several marketers admitted they had “no idea how results rank in AI platforms like ChatGPT” or described the space as “confusing.” That was a clear signal our problem focused-copy was resonating: There’s a lot of noise on how to optimize for AI search, but nobody really has it figured out

But we didn’t back up our claims enough
A few responses flagged skepticism. One person called out the use of the word “proven” in our copy and wanted to see actual evidence. Another said they weren’t familiar with the brands we showcased and suggested that recognizable logos might add credibility. In other words: the core message was good, but the trust signals weren’t strong enough.

Those two insights alone was the worth the $50 we spent. Plus, it took just a few hours to get responses back. 

If your startup hasn’t launched yet

In the video I also showed how to check how likely your new offer is to resonate with a target audience. The approach is similar to the method described above, but with a small change.

Start broad: “What are your initial impressions?”
→ captures gut-level reactions in their own words.

Add a quick scale: “How interested would you be in this offer? (1–5)”
→ gives you a directional signal on interest.

Follow up: “Why did you choose that score?”
→ surfaces what’s exciting, unclear, or missing.

But these tools won’t tell you everything…

Here’s the important caveat: tools like Lyssna are a single input. They don’t tell the whole story.

Pair them with:

• Feedback from sales calls (yes, record them and actually read the transcripts).
• Comments you hear at trade shows or from booth visitors.
• Customer interviews

Then roll it all up into a Voice of Customer doc so you can get a collective view of how your messaging resonates. Having all this information in one spot allows you to better spot patterns and understand what’s working and what isn’t. 

It’s  all vital information that will help you learn about your customers and grow your startup.