Common questions about WhyUser.

WhyUser is the Go-To-Market (GTM) Staging Platform. Engineering has staging environments to catch bugs before production. WhyUser is the same thing for your campaigns — stress test landing pages, ads, and emails against your buying committee before the budget goes out. Four engines in production today: Committee Simulation, Ad Campaign Simulation, Email Campaign Simulation, and Audience Discovery.

B2B deals are decided by groups, not individuals. The Champion approves. The CFO vetoes. The Technical Decision Maker raises a doubt that triggers the Budget Holder to walk away. Buying committee simulation models that chain reaction. WhyUser runs hundreds of buyer agents per persona, each playing a specific committee role, on the same asset. The output is a Conflict Graph showing which persona killed the deal and why.

WhyUser produces hypotheses, not verdicts. Every finding is a statistically grounded signal worth checking against your own data. The way to calibrate it is to run it on a campaign where you already know the outcome. If the simulation catches what actually happened, the accuracy question is answered by your data, not by our claims.

WhyUser searches the open web to map your company voice and community sentiment. You can also connect your CRM or upload Gong transcripts to add proprietary knowledge. The buyer agents react to your pitch the way your real customers do.

Yes. B2B deals are rarely killed by the End User. They die in the dark funnel when an Economic Buyer silently vetoes the page. WhyUser maps these node conflicts so you can add the missing ROI proof before launch.

ChatGPT gives you one helpful opinion. WhyUser runs hundreds of buyer agents in parallel. The CFO vetoes what the End User approved. Use ChatGPT to draft. Use WhyUser to validate. Different tool. Different job.

Salesforce, Gong, and HubSpot start recording data when a buyer fills a form, books a demo, or talks to sales. They see deals already in pipeline. WhyUser starts earlier. We simulate the buyers who scan your page, ask ChatGPT about your category, and bounce before any CRM event ever fires. We see the friction that killed the deal before it could begin.

Clay is excellent for building contact lists. It assumes you already know who to target. WhyUser completes the workflow. We reverse-engineer your messaging to surface the exact job titles that resonate. Once we give you a validated list, you plug it into Clay to find their emails.

Live A/B tools like Optimizely optimize a live funnel. They require burning ad budget and waiting weeks. WhyUser shifts testing left. You debug major conversion killers before launch. Your live A/B tests start from a higher baseline and win faster.

Internal reviewers stay in one buyer mindset: motivated, familiar with your product, and patient. They read the page from top to bottom and catch typos and brand voice. WhyUser buyer agents run in three mindsets: motivated, distracted, and skeptical. They scan, hunt, and bounce like real buyers do. They catch the missing proof, the silent veto, and the bounce risk that internal reviewers cannot replicate.

AI tools like ChatGPT and Claude write content. They are not built to validate it. WhyUser runs your AI-generated content through hundreds of buyer agents that scroll, scan, and bounce. You see exactly which persona rejects what, and why, before you publish.

A Figma mockup, a PDF draft, or a live URL. Pick your target buyer committee. Add the core promise of your campaign. Hit run.

Live B2B web traffic takes 4 to 6 weeks to reach statistical significance. A WhyUser simulation runs hundreds of buyer journeys and generates a prioritized Kill Sheet of friction points in minutes.

No. WhyUser is built for demand gen and growth leaders. No coding. No IT integration. Paste a URL or upload a PDF. Pick your committee. Run.

Your inputs and outputs stay yours. Data is encrypted in transit and at rest. We do not train shared models on your private content. SOC 2 controls in place. DPA available on request.

WhyUser uses an annual contract with a credit-based usage model. Each plan includes a monthly credit allotment for simulation runs across the four engines. Pricing depends on your simulation volume. Visit the ROI Calculator to see the per-test cost compared to live A/B testing or internal review cycles.