For many years now we've offered a self-serve 30-day trial for our SaaS product. About 20% of trial signups are good quality. The rest often have poor data, are difficult to get in touch with, or are foreign companies attempting to copy our features for their own projects. Should we put a better filter on who we let through the door? We're considering reviewing each trial to verify contact information and make sure we have a good product-customer fit prior to approving the 30-day trial. It seems these could be the benefits: 1. Improve the quality of active trials - Helps focus sales team efforts on quality leads only - Gives us earlier contact with the prospect so we can qualify and collect more information 2. Gives the product more of an exclusive feel / build a bit of anticipation because of a slight waiting period. 3. Makes it more difficult for competitors to get access and copy the results of all our R & D. 4. Makes us less of an open door target for hackers I'd love to hear your opinion or experience!
In theory, sure. In practice, to do this you'd need to find a mostly foolproof way of knowing who was "good" when they signed up*. Will the team reviewing be able to KNOW who is likely to be good? if not, you're just providing friction for signups.
This is a perfect thing to test. I'd use cohort analysis to follow a group you let in vs the control and see if the team does a better job than average at filtering out the "bad."
The Test would also then tell you if that friction point was hurting you overall, even if the team was unable to manually discern who the best customers are.
Another option: just review all the signups manually anyway and disable the ones you don't like. No need to reveal it.
*To do this, you'll need to find out what your good customers have in common. (the same industry? title? company growth phase?). This is called segmentation. Once you understand that you can then market to get to more of the good.