For Marketing Leaders Accountable for Pipeline

Stress test B2B campaigns
before launch.

Run hundreds of buyer agents on any page, ad, or email. Find bounce risks, bad targeting, and silent vetoes in 30 minutes. Not after six weeks of wasted spend.

Trusted by demand gen teams at
+ NDA design partners
RUN-2847 · LIVE Acme · Landing /platform
Committee Physics: Influence & Conflict
Does this page empower a champion to make the case internally?
Friction
END USER CHAMPION TECH OWNER ECON BUYER · VETOED GUARDIAN recommends cannot recommend stalls
300
agents · n=60/role
68%
bounce risk
99%
confidence
Every finding
is derived from
300
Persona
Simulations / run
5
Committee
Roles modeled
6
Live Data
Sources merged
~30m
From URL
to Conflict Graph
What WhyUser is

WhyUser is the Go-To-Market (GTM) Staging Platform — the staging environment for B2B marketing. It simulates hundreds of buyer agents grounded in your reality against landing pages, ads, and emails before launch. The output surfaces the silent vetoes, the missing proof, and the bounce risk that internal reviews and AI tools miss.

Problem · Solution

Stage every campaign before it runs.

Engineering has staging. Ops has dry runs. Finance has audits. B2B marketing is forced to test in production. WhyUser is the staging environment to fix every campaign before it launches.

High-Intent Bounce

Buyers shortlist with AI before they land. They arrive pre-qualified, with zero patience.

Echo Chamber

Internal reviews loved the page. Real buyers bounce in five seconds.

Engine · 01

Committee Simulation

Run the page through hundreds of buyer agents, each playing a specific committee role. See who vetoed and what proof was missing.

Silent Waste

Ad budget burns on pages that bounce.

Slow Feedback Loop

We launched a $50K campaign and waited six weeks to learn it didn't convert.

Engine · 02

Ad Campaign Simulation

Run the ad and the page through skeptical buyer agents hunting for the promise. If they cannot find it in five seconds, they bounce before the budget does.

List Burner

We burned a warm intro on untested copy. No second chance.

Persona Blur

One email to three roles wins for none of them.

Engine · 03

Email Campaign Simulation

Test subject, body, CTA, and landing page on the same buyer agent before you send. Get the winner per persona, with the causal reason.

Lookalike Trap

You target who bought before, not who this content is for.

CPM Spiral

Our targeting costs keep climbing. We bid on the same job titles as every competitor.

Engine · 04

Audience Discovery

Upload your content and get the exact roles and sub-verticals it resonates with, including Hidden Champion titles with lower CPMs. Plug the result into Clay or LinkedIn Ads.

One platform. Four engines. Every pain has a paired fix you can defend at a pipeline review.

WhyUser gives me the ammunition I need to make the case internally. To engineering. To leadership. To sales. It's not just telling me a page is broken. It's showing me exactly which buyer role bounces, why, and what to fix. That's gold for a lean marketing team.
Veronica Dominicis · Head of Demand Gen & RevOps · Vectara
Where WhyUser fits

AI tools create and orchestrate campaigns.
WhyUser simulates and validates them.

WhyUser is the Go-To-Market (GTM) Staging Platform
How it works

Where WhyUser fits in your campaign flow.

You don't change your workflow. WhyUser slots in as a one-hour pre-launch step — the gap between internal review and launch where every silent veto goes uncaught.

Phase · 01 Plan Brief & ICP
Phase · 02 Build Copy, design, ad creative
Phase · 03 Review Internal alignment
New step · pre-launch

WhyUser · Validate

Stress test the page, ad, or email against the buying committee. See which persona vetoes, what proof is missing, where the bounce risk hides.

30 min Statistical Before spend
Phase · 05 Launch Push live, allocate spend
Phase · 06 Measure Live performance, A/B

Your team already runs Plan → Build → Review → Launch → Measure. WhyUser is the one-hour validation step you've never had — the difference between learning a campaign was broken six weeks after the budget burned, and learning it before the page goes live.

The Platform

Four engines. One platform.

Every customer enters with Committee Simulation. The second engine depends on which channel you ship next — paid, email, or audience.

01 Committee Simulation

See the silent veto before it kills the deal.

Most B2B deals do not die on the call. They die in the dark funnel. The Champion likes the page. The CFO does not. Nobody tells you. Run any page through hundreds of buyer agents — each modeled as a specific committee role — and see exactly which persona vetoed and what proof was missing.

Conflict Graph Fix-It Playbook 30 min

The thing that clicked for me was seeing how the same page resonates completely differently with the champion vs. the economic buyer vs. the technical decision maker. That’s the starting point for actually fixing it — not guessing, not running an A/B test for six weeks, just knowing where to focus.

Veronica Dominicis · Head of Demand Gen & RevOps · Vectara
Engine · 01 Committee Simulation N=300 · 5 ROLES
Committee Simulation showing Conflict Graph: Champion and End User recommend, Economic Buyer cannot recommend, Technical Owner stalls
02 Ad Campaign Simulation

Catch the ad-to-page mismatch before the budget burns.

Your ad makes a promise. Your landing page either keeps it or it does not. Run the ad and the page through skeptical buyer agents hunting for that promise. If they cannot find it in 5 seconds, they bounce — before launch, not on the budget.

Bounce Risk Score Per-Persona Kill Sheet 30 min
Engine · 02 Ad Campaign Simulation N=270 · 90 PROFILES
Ad Campaign Simulation showing creative comparison with relevance scores, ad CTR, page CVR, and bounce metrics
03 Email Campaign Simulation

Validate the sequence before you press send.

A weak subject line wastes a quarter of the cycle. A bad body kills the click. A landing page mismatch kills the deal. Test all three on the same buyer agent before sending to 500 prospects. Get the winner per persona, with the causal reason.

Per-Persona Winner Forward Signals 30 min
Engine · 03 Email Campaign Simulation N=1,080 · 360 PROFILES
Email Campaign Simulation showing variant funnel performance with open rate, CTOR, page CVR, and campaign CVR per subject and body combination
04 Audience Discovery

Find the buyers who actually care.

Stop guessing job titles from last year's deals. Upload your content. Get the exact roles and sub-verticals it resonates with — including the Hidden Champion titles with lower CPMs you are not currently targeting. Plug the list into Clay or LinkedIn Ads.

Ranked Title Pool LinkedIn Targeting Hooks 30 min

After becoming HIPAA compliant, we revisited our Healthcare ICP. It didn't come back as a generic "Healthcare" segment. WhyUser surfaced high-fit sub-industries and 100+ verified roles mapped to jobs-to-be-done. Our usual targeting would have missed every one. That's the difference between burning spend on the wrong audience and putting it where it converts.

Nichole Larue, Head of Marketing Operations, ngrok
Engine · 04 Audience Discovery 157 → 104 → 10
Audience Discovery showing campaign targeting matrix across subverticals and buyer roles with verification funnel from 157 raw signals to 10 top opportunities
Architecture

How we build your buyer agents.

We do not imagine your buyer. We reverse-engineer them from your actual data footprint. Six grounded inputs feed the calibration. The output is a parameterized buyer agent — role, persona seed, Fogg behavioral state, context — that the simulation engine then runs at scale.

Company Context
site_crawl · acv · gtm
Customer Voice
gong · crm_objections
Market Intel
community · competitor_gaps
Buyer Agent
n=300 / run
AI Awareness
perplexity · chatgpt · claude
Campaign Context
ad_promise · landing_url
A/B Outcomes
live_perf · feedback_loop

Six grounded inputs converge into one parameterized buyer agent — calibrated with role, behavioral state vectors, mental model, and decision heuristics. Every run instantiates 300 of these across 5 committee roles, so findings are statistically defensible.

Most tools require weeks of manual data mapping and setup before you can even plan or launch a campaign. WhyUser's 'Ground Reality' onboarding ingested our site, social sentiment, and customer transcripts in minutes, creating a foundation that actually understands our business and users. The platform operates from that understanding instead of relying on prompting. You're not starting from scratch every time you test, and it keeps learning.
Nichole Larue · Head of Marketing Operations · ngrok
Differentiation

What every other reviewer misses.

Three things only WhyUser sees. Each one decides whether your campaign converts or burns.

01 · Mindset
Internal reviews see only one buyer mindset.
Your internal reviewers
  • Stay in one mindset: motivated, familiar, patient.
  • Already know what you meant. They want to like it.
  • Read the page top to bottom.
  • Catch typos and brand voice.
WhyUser buyer agents
  • Run in three mindsets: motivated, distracted, skeptical.
  • Have never seen your product. 5 seconds, low patience.
  • Scan, hunt, and bounce like real buyers do.
  • Catch the missing proof, the silent veto, the bounce.
02 · Timing
CRM tools see only buyers who already arrived.
Salesforce · Gong · HubSpot
  • Start recording when a buyer fills a form.
  • See deals already in pipeline.
  • Cannot tell you why most buyers bounced.
WhyUser
  • Start recording when a buyer scans your page.
  • See the buyers who never arrived.
  • Show the friction that killed them.
03 · Specialization
Generic AI gives you one helpful opinion.
ChatGPT · Claude · Custom GPTs
  • One opinion. Same answer for every company.
  • Read and summarize. Cannot scan-and-bounce.
  • Static. Day 1 looks like day 100.
  • Generic across every business.
WhyUser
  • 300 buyer agents per run, tuned to your committee.
  • Scan, hunt, and bounce like real buyers.
  • Sharper every week. Learns from your campaigns.
  • Specialized to your market, your buyers, your assets.
How WhyUser compares

WhyUser vs ChatGPT, A/B testing, and internal reviews.

Five common ways teams test campaigns today.

ChatGPT A/B Test Internal Review Custom GPT WhyUser
Pre-launch
Behavior simulation
Models the buying committee
Statistically grounded
Catches silent vetoes
Time to result minutes 4–6 weeks 2 weeks minutes 30 min
Cost per test free $10K+ meeting time free from $$

ChatGPT gives you one helpful opinion. WhyUser runs 300 buyer agents in parallel.
Different tool. Different job.

Who this is not for

If any of these are you, save your time.

We tell you upfront where the math doesn't work. Better than wasting your CFO's procurement cycle.

CMOs at 500+ person companies.

Your team needs the artifact, not you. We sell directly to your VP of Demand Gen instead.

Product marketing or content roles.

Different sale shape. We focus on the buyer who owns paid distribution and pipeline accountability.

B2C, e-commerce, or non-technical SaaS.

Buying committees are shallow. The political-shield framing is weaker. The math doesn't work for you yet.

Marketers who believe more AI throughput will fix conversion.

It won't. Come back after the campaign that taught you that.

FAQ

Top six.

Most-asked questions from B2B demand gen leaders evaluating WhyUser.

See all 16 FAQs
01 What is WhyUser, in one line?
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.
02 What is buying committee simulation?
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.
03 How accurate are buying committee simulations?
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.
04 Why not just use ChatGPT or Claude?
ChatGPT gives you one plausible opinion optimized for being helpful. WhyUser runs 300 adversarial matched-pair agents and finds the pattern that emerges across runs. The finding is statistically defensible — you can take it to a CRO. A single chatbot opinion is not. Different tool, different job.
05 Will Brand and Content see this as a critique?
We frame everything as hypothesis, not verdict. The output language is "the simulation suggests the Economic Buyer disengaged at the ROI section because…" — not "your page has X." This makes the artifact safe to forward to Content and Brand without it being a personal critique. Customers tell us this is why their cross-functional reviews actually move forward.
06 What does it cost?
Design partners are no-charge during the program. 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 model your cost and ROI.
Get Started

Fail in validation.
Win in the market.

Tell us about the next campaign you have going live. We respond within 48 hours.

The Cost

No charge during the program. Post-program: only if it earns its place in your stack.

The Trade

A 30-minute feedback call each week with our founder. We use it to guide product direction.

The Fit

You drive B2B traffic. Campaigns going live in the next 30 days. You can change them.