When a discovery is about to enter delivery, talking to the people who raised the underlying problem is the fastest way to validate scope, clarify edge cases and avoid building the wrong thing. Every discovery already knows who those people are: the customers behind its linked feedback. Here are three ways to find the right ones to interview.
1. Browse the linked customers
Open the discovery and click the people icon in its header (View linked customers). The panel lists everyone behind the discovery's feedback, in two tabs:
Users: the people who gave the feedback
Companies: the companies they belong to
Each tab shows how many customers it holds, and each row shows the customer's segments. A customer who sent feedback from several channels appears once.
To contact them, tick the users you want in the Users tab and click Copy emails. Their addresses are copied, separated by commas, ready to paste into an email or a calendar invite.
2. Export the customers
To work on the list outside Harvestr, or hand it to whoever schedules the calls, export it:
In the discovery, click its title in the breadcrumb at the top to open its actions menu.
Click Export, then choose Export users, Export companies or Export feedback.
Pick CSV or XLSX.
The export runs in the background and you receive it by email. The download link stays valid for 7 days.
Export | Columns |
Users | Id, Name, Email, Company, Segments |
Companies | Id, Name, Segments |
Feedback | Discovery title, Discovery description, Feedback, Feedback date, User name, Email, Company name |
The feedback export is the most useful one to prepare interviews: you get each customer next to what they actually said, so you can pick people whose feedback is detailed and recent.
3. Ask HAI who to talk to
The linked customers list tells you who gave feedback. HAI tells you who expressed the specific need you want to explore, because it reads the feedback itself.
In the discovery, click the Chat button in the header to open HAI in the side panel, then ask, for example:
"Which customers in this discovery describe needing bulk editing? Give me their names, companies and the exact quote."
"Find 6 customers to interview about this discovery: mix Enterprise and mid-market accounts, and favor recent feedback."
"Which of these customers mentioned a workaround they use today?"
HAI answers with the customers and the feedback behind each choice, so you can check why they were picked. Each question counts as one AI ask.
Pick the right sample
For most research, you don't need to talk to everyone. A practical rule of thumb: five to eight conversations, spread across the customer types that matter for the discovery. Use segments to balance the sample (for example, Enterprise vs self-serve), and favor customers whose feedback is specific: they are usually the most willing to talk.
After the interviews
Add your notes back into Harvestr as feedback, and link it to the discovery. See Submit feedback directly from inside Harvestr. That way:
the interview insights sit next to the feedback they were validating
whoever picks up the discovery next sees what has already been asked
the discovery's feedback reflects your research, not just inbound requests