User Testing
How to Make Money Testing Websites and Apps in 2026
by
Lihong
|
Apr 29, 2026
Most Messaging Goes Live Without Anyone Outside the Building Reading It First
You are too close to what you are building to see it the way a first-time visitor does. Words that feel clear and compelling to the team that wrote them are often confusing, unconvincing, or forgettable to the people they were written for.
Most teams skip validation entirely. Marketing message testing gets treated as a nice-to-have rather than a prerequisite, so copy gets approved based on internal consensus rather than external reaction. The result is messaging that passes the internal review and fails in the market.
Message testing with TheySaid changes the input. Share your landing page, product page, or ad concept with real users, let AI moderate the reaction, and fix what is not landing while changes still take minutes rather than sprints.
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How TheySaid Enables Message Testing at Any Stage
Test First Impressions Before Your Campaign Launches
Share a link to your landing page, homepage, or ad concept and watch real users read it for the first time. AI asks what they understood, what felt unclear, and what they would do next. You see whether your product messaging testing is doing the job it was written to do before you spend a dollar putting it in front of a larger audience.
Find Out If Your Value Proposition Actually Makes Sense
Value proposition testing with TheySaid surfaces the gap between what you meant to communicate and what users actually understood. Participants read your core messaging and AI asks them to describe what the product does, who it is for, and why they would or would not try it. The answers tell you whether your positioning is working or whether you are speaking a language your audience does not recognize.
Compare Messaging Variations Side by Side
Run separate test plans for two or more messaging directions and compare how real users respond to each one. AI moderates every session consistently, making findings comparable across variations so you choose between options based on how users actually react rather than which version your team argued for more convincingly.
Test Landing Page Messaging at Every Stage of the Funnel
Test landing page messaging across every touchpoint in your funnel: the headline that captures attention, the subheading that earns the next scroll, the feature descriptions that build conviction, and the CTA that converts. AI asks participants what they understood at each stage, what language created doubt, and which sections gave them the most confidence in your product.
Hear How Real Users Describe Your Product in Their Own Words
When participants describe your product after reading your messaging, they reach for language that often resonates more naturally than what your team wrote. TheySaid captures every word users say across all sessions, giving you transcripts full of real audience language you can draw from when rewriting copy.
Validate Before You Scale
TheySaid's Synthetic Panel (coming soon) lets you run AI testers through your messaging immediately, giving you fast preliminary signal on whether your copy is clear and compelling before you recruit real participants for deeper validation. Eliminate weak messaging directions early and invest your testing resources in the versions worth refining.
Everything You Need to Validate Messaging Before It Goes Live
First Impression Testing
Watch real users encounter your messaging for the first time. AI captures immediate reactions, asks what users understood before reading further, and probes whether the page communicated the right thing at a glance. First impressions are the hardest thing to gauge internally and one of the most valuable things to test with real users.
AI-Moderated Comprehension Testing
AI conducts structured copy testing sessions where participants read your messaging and describe back what they understood. You see the gap between what you intended to communicate and what actually landed, without needing to moderate a single session yourself.
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Voice Reactions and Real-Time Transcription
Participants speak their reactions to your messaging aloud as they read. Voice captures the hesitation, enthusiasm, and confusion that typed responses rarely surface. AI transcribes every response in real time and asks follow-up questions based on what users say, giving you richer signal from every session.
Side-by-Side Variation Comparison
Run structured comparison studies across messaging variations using consistent AI moderation. Compare how users respond to different headlines, value propositions, or CTA language and make the call based on behavioral evidence rather than internal preference.
Flexible Recruitment for Any Audience
Test messaging with your existing customers through email or direct links, or recruit specific audience profiles from TheySaid's panel of 5M+ participants with demographic and behavioral targeting. Use the Synthetic Panel (coming soon) for fast early-stage concept validation before committing to full participant recruitment.
Messaging Approved Internally vs. Messaging Validated With Real Users
Without TheySaid
Copy Gets Approved Based on Who Likes It
Internal reviews surface opinions, not insights. The headline that survives the review process is the one the most senior person in the room preferred, not necessarily the one that communicates most clearly to your actual audience.
You Find Out Messaging Doesn't Work From Conversion Data
Low click-through rates, high bounce rates, and underperforming paid campaigns tell you the messaging is not working. They do not tell you which part of it failed, why it failed, or what to write instead.
A/B Testing Tells You Which Version Won, Not Why
Split testing produces a winner, but it does not explain why one version outperformed the other or what specifically drove the difference. You optimize toward the winner without understanding the underlying signal well enough to replicate it.
Messaging Rewrites Are Expensive After Launch
Rewriting copy after a campaign has launched means pulling assets, updating pages, revising ads, and realigning teams. Changes that would have taken minutes during the drafting stage take days after the messaging is live and distributed.
No Direct Access to How Users Describe the Product
Teams write copy using the language they use internally to describe the product. Real users often think about the problem and the solution in completely different terms, and the gap between the two is where messaging fails.
With TheySaid
Validate Before the Campaign, Not After Message testing
With real users catches unclear positioning, confusing headlines, and weak value propositions before they go live. Fix the copy while changes take minutes, not days.
Understand Why, Not Just What
TheySaid captures the reasoning behind every reaction. You hear what users understood, what confused them, and what would have made the messaging more compelling, giving you direction for the rewrite rather than just confirmation that something is not working.
Choose Between Variations With Confidence
Compare messaging directions based on how real users respond to each one. User feedback on messaging collected through consistent AI moderation makes the choice between options a data decision rather than a preference debate.
Hear Your Audience's Language Directly
Real users describe your product in their own words during every session. Reviewing transcripts across sessions surfaces the natural language your audience reaches for, which is often the most direct input available for writing copy that actually resonates.
Launch Faster by Validating Earlier
Catching a messaging problem before it goes to design, legal, and media buying is faster and less expensive than catching it after. Message testing software that delivers findings in hours rather than weeks keeps your launch timeline intact.
See What a Message Testing Study Looks Like
See what customers say about our AI user testing platform
"Implementing TheySaid has led to a 5-10% increase in qualified leads from our existing customers in just a few months while reducing churn. The results speak for themselves."
Alex Farmer
Chief Revenue Officer @ Nezasa
"TheySaid's AI Surveys helped us step up our insight gathering game. It's smarter and more engaging for customers."
Maggie C.
VP, Product Design @ ClickUp
"How did TheySaid AI come up with such great question recommendations? These are questions that our teams really want to know and discussed internally a lot. I am impressed!"
Brook P.
VP, Marketing @ DX
"Integrating TheySaid has been a game-changer. We've seen a 5-10% decrease in customer churn with an increase in upsell opportunities since its implementation."
Srikrishnan Ganesan
Co-Founder & CEO @ Rocketlane
"Really easy to use and I think this might be one of the best ways to engage with your customers! Platform will really boost your customer engagement."
Danny L.
Co-Founder
From Concept to Launch: User Testing Use Cases
Learn how product teams use TheySaid's usability testing use cases and UX research use cases to validate prototypes, optimize features, test pricing strategies, and gather user feedback before shipping to customers.
Learn how product teams use TheySaid's usability testing use cases and UX research use cases to validate prototypes, optimize features, test pricing strategies, and gather user feedback before shipping to customers.
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FAQs
What types of messaging can I test with TheySaid?
Any written or visual messaging accessible through a browser, including landing pages, homepages, product pages, email drafts, ad concepts, onboarding copy, pricing pages, and feature announcements. If it can be viewed in a browser, TheySaid can test how real users respond to it.
How is message testing different from A/B testing?
A/B testing tells you which version performed better after it went live. Message testing tools like TheySaid tell you why messaging does or does not resonate before it goes live, giving you the understanding you need to improve the losing version rather than simply replacing it with the winner.
How quickly can I get results from a message testing study?
Most teams have a clear picture of how their messaging is landing within 24 hours of launching a test. AI analyzes sessions as they complete, so you see findings in real time rather than waiting for all participants to finish before any results appear.
Can I test messaging with my actual target audience?
Yes. Recruit from your existing customer base through email or direct links, or use TheySaid's panel with demographic, behavioral, and role-based targeting to reach the specific audience profile your messaging was written for. Testing with the wrong audience produces misleading signal, so participant targeting matters.
Can I compare two different messaging directions in the same study?
Yes. Set up separate test plans for each messaging direction and run them with the same or different participant groups. AI moderates every session consistently, making the comparison fair and the findings directly comparable. Marketing message testing studies that compare multiple directions give you the evidence to make a confident choice between options.
What is the Synthetic Panel and how does it help with message testing?
The Synthetic Panel is a coming soon feature that lets you run AI testers through your messaging immediately, without recruiting real participants. Use it to eliminate messaging directions that clearly do not work before investing research resources in the versions worth testing more thoroughly with real users.
How do I turn message testing findings into better copy?
TheySaid surfaces where comprehension broke down, what language users reached for naturally, and which moments created confidence or doubt. Use session transcripts as raw material for your next draft and address the gaps AI identified across sessions. Value proposition testing findings are often the most direct input for copy rewrites because they show exactly what users understood and what they missed.
Stop guessing if your message works. Find out.
TheySaid User testing recommends questions, delivers via your existing channels, engages your audience,and summarizes results through AI user testing, surveys, and interviews.
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