Case study · From the Pluris libraryReceipt no. 9417
What sucked
The chair of a national conference for a global peer network of business owners wanted each of a couple hundred attendees to meet the person they most needed to meet.
The default was an alphabetical seating chart. Doing better required detailed attendee data, which meant a long survey with every question required.
What they built
North Group built a required 80-question attendee survey, a custom AI matching model that paired a couple hundred conference attendees across four formats under chair-set criteria and guardrails, and an AI agent that wrote each opted-in attendee a personal readout.
What changed
9 in 10 completed
Attendees who finished an all-required survey that took 37 minutes on average
100 readouts
Personal ~800-word readouts, each sent within about 15 minutes of submission
59 of 81 opened
Readouts opened, of the first 81 delivered
More fixes like this
- How an ER Front Desk Cut Onboarding From Weeks to DaysBoxcar ai · Healthcare & Life Sciences
- How One Research Firm Cut Trend Reports to 35 Min With AIFractional AI · Professional Services
- How a DOOH Ad Platform Replaced Unsellable InventoryTenex · Media & Entertainment
- How a Law School Cut Bar Exam Question Time 75%GenFutures Lab · Education & EdTech