{"id":1099358,"date":"2026-08-04T01:12:19","date_gmt":"2026-08-04T08:12:19","guid":{"rendered":"https:\/\/www.questionpro.com\/blog\/?p=1099358"},"modified":"2026-08-04T01:12:42","modified_gmt":"2026-08-04T08:12:42","slug":"ai-incidence-rate-estimate","status":"publish","type":"post","link":"https:\/\/www.questionpro.com\/blog\/ai-incidence-rate-estimate\/","title":{"rendered":"Stop guessing your incidence rate. Let the AI read your screeners instead"},"content":{"rendered":"\n

Your broad audiences forgive a rough guess. Your niche ones send you back for a requote. That is exactly why you need an AI incidence rate estimate to do the heavy lifting.<\/em><\/p>\n\n\n\n\n\n

The number you guess decides the whole quote<\/strong><\/h2>\n\n\n\n

You are setting up a feasibility check. Respondents, country, completion date. Then one small field asks for your incidence rate, and you pause.<\/p>\n\n\n\n

You type 40. Or 60. If you are honest, you are guessing.<\/p>\n\n\n\n

That guess is not harmless. It sets your cost per complete, your timeline, and the quote you hand your client. Guess too high, and the study underdelivers, the field runs long, and you are back asking for a requote. For a broad consumer audience, a rough number is usually close enough. For a niche one, it rarely is.<\/p>\n\n\n\n

That is the gap an AI incidence rate estimate closes. Instead of asking you to know the number, it reads your survey and your targeting, then hands you a data-driven starting point.<\/p>\n\n\n\n

Learn More:<\/strong> Access respondents and run feasibility with QuestionPro Audience<\/a><\/p>\n\n\n\n

What is an AI incidence rate estimate?<\/strong><\/h2>\n\n\n\n

It is a feature inside QuestionPro Audience that predicts your survey incidence rate before you launch. It reads your screener questions and qualifying answers, the panel filters you have applied, and historical panel profiling data where it exists. Then it returns a suggested IR with a confidence level.<\/p>\n\n\n\n

It sits right next to the incidence rate field in your feasibility setup, behind a “Check with AI” button. One click, and you get a number instead of a shrug.<\/p>\n\n\n\n

Three things it is not. It is not a live field metric that updates while your survey runs. It is not a quota simulator. And it does not redesign your survey for you. It gives you a better number to start from, and leaves the decisions with you.<\/p>\n\n\n\n

How it works, from screener to feasibility<\/strong><\/h2>\n\n\n\n

The payoff is a realistic IR without the manual math. Here is the flow behind it.<\/p>\n\n\n\n

You select or upload your survey, then tag which questions are screeners. You mark the answers that qualify a respondent. You apply the panel filters that are actually available for your target. Then you click “Estimate IR.”<\/p>\n\n\n\n

The system sends that package to the AI, which compares two things: what your survey requires versus what the panel can genuinely target and profile. Within seconds, you see a suggested IR, a confidence level, and a niche warning if your target looks hard to reach. You can apply the number to your feasibility with one click, or type your own if you would rather.<\/p>\n\n\n\n

What it looks like in practice<\/strong><\/h2>\n\n\n\n

A broad consumer study<\/em><\/h3>\n\n\n\n

Say you are fielding a tumble dryer usage study to US adults, 18 to 65, all genders, any household income, with a single screener: owns or has access to a tumble dryer. The AI reads that setup and suggests an IR around 82 percent, inside an 80 to 85 percent range, with high confidence. The logic is right there to read: dryer ownership is high, the demographics are broad, and the screener is inclusive. You apply it and move on.<\/p>\n\n\n\n

A niche, brand-specific target<\/em><\/h3>\n\n\n\n

Now say you want owners of one specific electric vehicle brand. The panel may only be able to target “car owners,” not that exact model. The estimate comes back lower, the confidence drops, and a warning tells you the audience is very niche. That is the moment to reset expectations with your client, or to talk to the Audience team, rather than discovering the problem three days into field.<\/p>\n\n\n\n

The advantages of an AI incidence rate estimate<\/strong><\/h2>\n\n\n\n