LinkedIn lead gen forms: prefilled profile data or one qualifying question?

Picture a B2B software firm running LinkedIn lead gen forms for demo requests. The prefilled fields (name, company, job title) push completion rates up and cost per lead down, which looks great in the platform. The catch is that prefilled data is whatever the member last typed into their profile, so it's often stale or vague, and sales ends up with leads they can't place. I'd keep the prefilled fields for contact basics but add one custom question that forces intent, like team size or the tool they use today. Volume drops, but I'd rather pay more per lead that sales actually calls back. Has anyone compared lead-to-opportunity rate with and without the custom question?

Stale profile data is a real problem, and a custom question is the cleanest filter you get inside the form. But I'd push the qualifier one step earlier, into the ad copy and creative. If the ad says something like "for teams of 10 or more running X today," people who don't fit will skip it before they tap, and you won't pay for those clicks at all. The form question then just confirms what the ad already filtered. Otherwise you end up paying for a lot of curious students and freelancers who happily pick "1 to 10" from a dropdown.

To compare, run two ad sets with identical creative, one with the question and one without, and push the lead form exports into the CRM so you can match each lead to an opportunity. Platform CPL will look worse on the qualified version, which is expected. The number that matters is cost per opportunity, and you won't see that without the CRM match.

Agreed on the copy filter, but it muddies the test. If the ad copy changes between the two ad sets, you can't tell whether the gain came from the form question or from the ad screening people out before they tap. I'd keep the copy identical and test the form question alone, then run the copy qualifier as a second experiment. Otherwise you'll credit the wrong change. How long is your typical sales cycle? That decides how long you have to wait before cost per opportunity means anything.

Yes, keep the copy identical for the reason you gave. I'd also make sure the two ad sets don't overlap. If both target the same job titles and company sizes, one person can see both versions and tap whichever form they reach first. Then the question-free arm picks up leads the question was meant to filter, and since each arm looks fine on its own, it's easy to miss. Splitting by seniority band or company size keeps each person in one arm.

For the CRM match, use email rather than name. People type their names differently on forms and in sales tools, so you'll lose matches that way. For demo requests, count opportunities created within a fixed window after the lead, say 30 days, instead of waiting for closed-won. You get a usable signal much sooner.

Splitting by seniority and matching on email is the right call. I'd add one more check: look in the CRM for contacts who already had an opportunity before the test started. Demo requests often come from people who are already in pipeline, and they'll fill in whichever form they hit first. If you count those as wins, the arm that happens to reach more existing contacts looks better than it really is.

The fix is to exclude any opportunity created before the lead's timestamp, and report that count separately so you can see how much it moved the result. On a small B2B list, it can change the answer.

The email match has a catch: LinkedIn prefills the address from the member's account, and that's often a personal Gmail rather than the work address in your CRM. So test the match rate on a small sample before you trust the comparison. If it comes back low, fall back to email plus company domain.

Fair, but a low match rate doesn't always mean the test is broken. It depends on whether your closed-won deals mostly come from work emails. If they do, the Gmail leads were unlikely to close anyway, so the unmatched ones don't tell you much.