Test Your Idea
What do real people actually think about your next move?
Most organizations make their biggest decisions first, then find out if people trust them, reject them, misunderstand them, or turn them into a crisis. That is backwards. FactHub helps teams learn before they launch, spend, or commit.
You are flying blind. So is everyone else.
Surveys are slow. Focus groups are narrow. Social media is noise. By the time real intelligence reaches the people who need it, the moment has passed and the money is already spent.
FactHub flips that. We put the real thing in front of real people, capture what they actually do, and turn that reaction into decision intelligence you can use immediately.
From public reaction to instant decision intelligence.
FactHub began with news because news is where reality breaks every day. But the same system that verifies stories, measures public reaction, and challenges narratives live can test almost any decision before it happens.
Show people the real thing
A product concept, campaign, policy, price change, startup idea, public message, brand move, or market prediction.
Capture live human reaction
Votes, comments, challenges, emotional signals, disagreements, concerns, debate behavior, and Crowd Map patterns.
See what is forming
Identify who supports it, who rejects it, who is unsure, where confusion begins, and which changes can improve the outcome.
Not prediction. Formation.
We show how public reaction forms — before the market, media, or public opinion locks the outcome in place.
We capture the interaction layer behind every decision.
A product, message, price, or policy does not succeed in isolation. It succeeds or fails through interaction: people reacting, questioning, challenging, agreeing, resisting, sharing, and changing their minds.
FactHub captures that process in real time. This is decision intelligence built for the moment before launch — when there is still time to adjust the message, fix the confusion, reduce the backlash, strengthen the offer, and move with the market instead of chasing it later.
Real people, not ad traffic.
Google and social ads are built to target and convert. FactHub is built to evaluate. People react to the idea itself, not just an ad unit competing for a click.
Structured signal, not social media chaos.
Social media usually shows reaction after the narrative has already escaped. FactHub organizes support, rejection, confusion, trust, price resistance, and backlash risk while the decision can still be changed.
Not what people claim. What they reveal.
People do not always know what they want — or say what they really think. FactHub builds its intelligence from revealed behavior: what people vote for, challenge, ignore, repeat, debate, resist, and reconsider.
Just-in-time intelligence, not a report after the damage.
The output is built for action: what to clarify, what to remove, which audience is moving first, where resistance is forming, and what to fix before the decision becomes expensive.
Test almost any decision before it hits the real world.
Product launch. Campaign message. Startup idea. Restaurant menu item. Pricing change. Retail experience. Public communication. Brand repositioning. Market narrative. Open each case to see what FactHub can test before the decision goes live.
01 Product Launch Test demand, confusion, excitement, price sensitivity, and rejection risk.
Example: Rabbit R1. Rabbit R1 generated huge early attention as an AI-native device, but after people saw the product clearly, the core question kept coming back.
The issue was not only technical. It was adoption: everyday usefulness, performance, price, habit change, and whether the device solved a real problem better than tools people already used.
With FactHub, a company could test before launch
- Whether consumers immediately understand why the product exists
- Which objections appear again and again
- Whether excitement survives exposure to tradeoffs
- Whether users see enough value to change habits
- Which features people actually care about
- Whether attention reflects novelty or purchase intent
- Which audiences understand the value immediately
- Which concerns become rejection risk
02 Campaign Message See whether a message builds trust, backlash, curiosity, or indifference.
Example: American Eagle x Sydney Sweeney campaign. The “Sydney Sweeney Has Great Jeans” campaign created massive attention, but public interpretation split sharply.
What was intended as playful wordplay was read by some audiences as clever branding, and by others as exclusionary, tone-deaf, or politically loaded. The issue was not simply attention. It was what kind of attention the message created.
With FactHub, a brand could test before launch
- Which interpretations emerge immediately
- Which audiences understand the intended message
- Which language creates trust versus skepticism
- Which emotional reactions dominate first exposure
- Whether people see the campaign as authentic or opportunistic
- Which concerns appear organically
- Which message variations reduce backlash risk
- Whether engagement reflects approval, outrage, confusion, or debate
03 Startup Idea Find out what people understand, question, want, and would actually pay for.
Example: Humane AI Pin. Humane raised major funding and launched an ambitious AI hardware product, but consumer reaction quickly focused on unclear value, usability concerns, and whether people actually wanted the product in daily life.
With FactHub, founders and investors could test before building and scaling
- Whether consumers understand the idea immediately
- What questions appear repeatedly
- Whether the problem feels important enough
- Which features people actually care about
- Whether willingness-to-pay exists
- Which objections survive debate
- Which tradeoffs weaken interest
- Which expectations emerge organically
04 Restaurant Menu Test Test whether customers actually want a new item before putting it on the menu.
Example: A restaurant chain testing a new spicy chicken bowl. The item may follow the right trend: spicy food, protein bowls, Korean flavors, healthier fast-casual meals, or value pricing.
But customers may like the idea and reject the price. They may love the flavor concept but dislike the name. They may try it once but not reorder it.
With FactHub, the chain could test before rollout
- Whether customers understand the item immediately
- Which ingredients create excitement or hesitation
- Whether the price feels fair
- Whether the name makes the item more appealing or confusing
- Which photos or descriptions increase purchase intent
- Whether people see it as a meal, snack, or limited-time gimmick
- Which customer groups are most likely to try it
- Which objections reduce repeat-purchase potential
05 Pricing Change Detect who accepts it, who resists it, and what makes the value feel fair.
Example: Streaming subscription price increases. A price increase may look small internally, but customers judge it emotionally: value, fairness, alternatives, loyalty, and timing all matter.
With FactHub, a company could test before rollout
- Which customer segments resist the increase
- What makes the increase feel unfair
- Which explanation improves acceptance
- Which objections appear repeatedly
- Whether users still perceive enough value
- What price threshold triggers churn risk
- Which features customers anchor value around
- Which communication framing builds trust
06 Retail Experience Test Test store, checkout, loyalty, and customer experience changes before rollout.
Example: A retail chain testing a new self-checkout policy. A faster checkout system can feel convenient to some people and frustrating to others. A loyalty program can feel valuable, confusing, or like another data grab.
With FactHub, a retailer could test before rollout
- Whether customers understand the change
- Which parts feel helpful versus annoying
- Whether the change improves trust or creates friction
- Which customer groups resist the experience
- What language makes the change feel beneficial
- Whether people see the update as convenience or cost-cutting
- Which objections appear repeatedly
- What would make customers more likely to accept it
07 Public Communication Test communication before confusion, distrust, or backlash makes it harder.
Example: Student loan repayment communication. When repayment systems changed, many borrowers faced confusing deadlines, eligibility rules, forgiveness requirements, and payment structures.
Even when policy teams understood the rules internally, public understanding varied widely. Confusion became part of the problem.
With FactHub, agencies, campaigns, or institutions could test before rollout
- Which explanation creates understanding versus confusion
- Which wording increases trust
- Which information people believe is missing
- Which groups misunderstand the message
- What concerns appear repeatedly
- Which messages reduce misinformation
- Which explanations move people from uncertainty to confidence
- Which framing persuades undecided or skeptical audiences
08 Brand Risk Understand backlash risk before a partnership, statement, or repositioning.
Example: Jaguar rebrand discussion. Jaguar attempted a dramatic repositioning from legacy luxury automaker to ultra-premium electric brand. Some saw bold reinvention. Others saw confusion, heritage loss, and brand disconnect.
With FactHub, a company could test before launch
- Whether customers understand the repositioning
- Whether removing heritage strengthens or weakens trust
- Which messages preserve loyal customers while attracting new ones
- Which visuals create excitement versus confusion
- Which audiences see the move as premium, modern, alienating, or unclear
- Which objections become backlash risk
09 Market Sentiment Test consumer reaction to a trend, category, narrative, or investment thesis.
Example: AI hardware enthusiasm versus real adoption. Consumer AI hardware attracted enormous excitement, but attention did not always translate into demand. Many consumers were curious, but skeptical about daily use, pricing, privacy, and whether the product solved a real problem.
With FactHub, companies and investors could test
- Whether consumers are excited or just curious
- Whether people understand the category
- What creates belief versus skepticism
- Which use cases feel real versus forced
- What consumers would actually pay for
- Which objections appear across different audiences
- Whether market attention reflects durable demand or temporary hype
- Which narratives survive challenge and debate
Not just “Do people like it?” The real question is why they react.
Test Your Idea launches at the end of May 2026.
Built for companies, founders, campaigns, investors, agencies, media teams, and public organizations that need to know how real people will react before the decision goes live.