Message Testing for Campaigns & Advocacy

Political research has a brutal asymmetry: the campaigns that most need message testing can least afford it. A single traditional focus group costs more than a county race's media budget, so framing decisions that swing persuadable voters get made in the war room on instinct. AI voter panels close that gap: test the framing, the slogan, the attack response, and the donor appeal against personas modeling your actual electorate, in hours and without field exposure.

Start free or try the free persona generator.

The research gap you're working around

Polling tells you what, not why

A topline number says the message is underwater. It doesn't say which word is sinking it, or what frame would float with the same voters.

The calendar is unforgiving

News cycles turn in hours. Any testing process measured in weeks produces answers for arguments the race has already moved past.

Leaks are fatal

Field-testing an attack response or a vulnerable framing with real voters risks the test becoming the story. Synthetic panels keep the draft inside the room.

What you can run, starting today

Test policy framings by segment

The same policy, framed three ways, run past panels modeling base, persuadable, and opposition-leaning voters. AI Focus Group.

Pick the stronger slogan

Head-to-head slogan and tagline tests with the reasoning behind each persona's preference. AI A/B Test.

Rehearse the rebuttal

Run the opposition's likely attack and your candidate's response past a skeptical panel before debate night. Message testing.

Sharpen the donor appeal

Test fundraising email framings against donor personas: urgency versus vision, threat versus opportunity. AI Poll.

Understand the persuadable voter

Interview a conflicted-voter persona 1:1 about where your message loses them, and what would win them back. AI Deep Dive.

An illustrative example

A statehouse campaign tested three framings of an infrastructure bond measure it supported.

Focus groups with three voter panels: reliable supporters, fiscal-skeptic independents, and low-information likely voters.

The decision: The campaign led with cost-of-inaction plus named projects, and dropped the aspirational language that tested as wallpaper.

Built for the way you work

Frequently Asked Questions

Can AI panels predict how voters will actually vote?

No, and treat any claim otherwise as malpractice. What panels do well is comparative message diagnosis: which framing communicates, where comprehension breaks, and what objections surface. Pair it with real polling for measurement; use this for the why and the iteration speed.

Is this appropriate for sensitive political content?

The platform is built for legitimate message development: framing, clarity, and persuasion testing for campaigns and advocacy organizations. It's not a tool for deception, voter suppression content, or impersonation.

How do we model our specific electorate?

Describe segments the way your targeting does: demographics, geography, partisanship lean, turnout propensity, and the issues they're cross-pressured on. The panel generates personas to match, and you can save them for reuse across the cycle.

Who uses this besides candidate campaigns?

Advocacy organizations testing issue framings, ballot measure committees, public affairs shops, government communicators testing public-service messaging, and unions and associations testing member communications.

Keep exploring

Put a panel to work today

Start free and run your first study in minutes. Get started.