Event matchmaking software: judging match quality not features

An organiser sent me a shortlist last week. Seven matchmaking platforms, scored against a grid of twenty-eight features. One product had ticks in twenty-six boxes. It was obviously the strongest option on paper. It was also, almost as obviously, the wrong tool for her event.

The grid did not test the thing that matters. Nobody on her team had opened the products, clicked into a real match and asked the question that actually separates event matchmaking software worth buying from software that just schedules meetings: is this match worth acting on?

My take: most buying decisions in this category are made on the wrong criteria. Strip the category back to its core job and matchmaking software exists to put two people in the same room who, for roughly the next 90 days, are trying to solve overlapping problems. Everything else - profiles, messaging, scheduling, gamification, leaderboards - is packaging around that one job.

Why most shortlists start in the wrong place

The shortlist I was sent had columns for AI meeting scheduler, smart recommendations, in-app chat, lead capture, gamification, reports, and eighteen other things. Every vendor had ticks against most of them. Her team had spent the best part of a fortnight filling the grid in. The grid was scoring a brochure.

Here is what the grid did not ask. Open the product. Click into an example match between two real past attendees. Ask the vendor to walk you through why this specific match was made. Which data points the algorithm drew on. What the other three candidates it considered first looked like, and why it ranked them lower. What the two attendees did afterwards. Strong products have that walk-through ready. Weak ones need a week and a product manager.

This is the single cleanest test for event matchmaking software, and almost no feature grid includes it. Good matching is evidence-based, not atmospheric - if a vendor cannot explain one match on the spot, they will not be able to help your attendees understand theirs either. The attendee who opens the app, sees a suggestion with no reason attached and taps away is the attendee you will not win back next time.

There is a second buying trap too. Freeman's 2024 Event Organizer Trends Report found that 60% of event teams distribute networking responsibilities across staff or do not actively manage networking at all (Freeman via PCMA, 2024). Most organisers end up buying matchmaking software with no one assigned to champion it, which is the most reliable way to underperform any benchmark a vendor quotes. Before the shortlist, make sure someone on your side owns the rollout. The organiser champion effect is what determines the adoption number the vendor will not want to put in writing.

What "good matching" actually means

I think of match quality in three layers: the profile data underneath the match, the signal the algorithm reads from it, and the surfacing - how the match is presented to the attendee. A product can be strong on one layer and weak on the others, which is exactly why the feature-grid approach fails. A grid scores the packaging, not the stack.

Layer one is the profile. A match can only be as good as the fields it has to work with. If your registration form captures job title and a free-text box labelled "networking interests", no algorithm will save you. The richest matchmaking data lives in the registration form you already run - role, sector and the specific thing the attendee is trying to solve at this event. If the software cannot integrate cleanly with your registration system, treat that as a downgrade even when every other feature looks strong.

Layer two is the signal. Different algorithms weight different things. Some match by similarity - same job title, same sector, same stage of growth. Some match by complementarity - one has the problem, the other has sold the solution twice. Some blend the two, weighted by cohort. The questions to ask a vendor are narrow: what are the weightings, can I see them, and can I override them for a particular event or cohort where the default logic does not fit? Any answer that reaches for the word "proprietary" should cost the vendor points.

Layer three is the surfacing. Even a strong match falls over when the attendee opens the app, sees a person and a job title, and has no idea why they should walk across the room. The best matchmaking software tells the attendee in plain English why they have been matched and what to ask in the first two minutes of the meeting. Black-box matching trains attendees not to act on app recommendations next time. That is how adoption quietly dies between event one and event two.

Three signals that beat a feature grid

When we help a client evaluate event matchmaking software, we score vendors against three questions. Each one reveals more than twenty feature ticks.

One. Can the vendor show me a real match from a past event and walk me through why it was made, what else was considered, and what the attendees did with it? A strong product has case data to hand and a product person who can talk through the reasoning without looking anything up. A weak one will offer to come back to you next week.

Two. What is the adoption benchmark on events of our size? Industry data puts average event app adoption at 55-65%, with well-promoted events hitting 80% and unpromoted ones dropping to 20-30% (Nunify, 2025). A perfect matching algorithm at 30% adoption produces fewer meetings than a fair algorithm at 75%. Any vendor that will not share benchmarks by event size is asking you to trust them without evidence. Ask for the numbers in writing.

Three. What happens to the data after the event? Match history is raw material for next year's registration form, next year's sponsor brief and next year's audience-intelligence report. If the software locks that data inside the platform, the investment compounds for the vendor rather than for the organiser. The data you extract after the event is also the data that argues the renewal.

What vendors will not volunteer

Three things that do not come up in a demo unless you raise them.

Meeting conversion on suggested matches. What share of the matches the platform recommends actually lead to a held 1-1 meeting? Vendors track this number. Most are quietly reluctant to quote it because the honest answer across the category often sits under 15%. Ask for it by event size. A confident vendor will have cohort benchmarks to hand.

What happens when matching is wrong. Every algorithm has edge cases. Ask the vendor to walk you through the attendee-facing cancellation or decline flow. If a declined match is treated as a failure to hide from reporting, the system is not learning. If the product asks the attendee why the match did not land and feeds that signal back into the next round, you are looking at an actual learning system rather than a static recommendation engine.

The pricing structure for next year's audience intelligence. Match data is valuable to sponsors as well as organisers. Some platforms include sector-level audience reports in the base fee. Others unlock them at a higher tier. Others sell them back to you as an add-on at renewal. Know exactly what you are committing to across the full renewal cycle, not only for the first event.

It is worth holding all three against a wider industry reality. Freeman's 2025 Networking Trends Report found that 51% of attendees now say effective networking alone is reason enough to return to an event (Freeman Networking Trends Report, 2025). Attendees are not the only ones noticing. OECD time-use data has been tracking a decade-long drop in weekly in-person social interaction across rich economies (OECD Social Connections and Loneliness, 2024), which quietly raises the bar for what a two-day event is expected to deliver. Your matchmaking software is, at this point, one of the few things standing between a booked delegate and a trip they cannot justify again next year.

What good looks like, in one sentence: the software that makes it easiest to explain to an attendee why they were matched with a specific person, and easiest to explain to a sponsor why their segment got the quality of connections they paid for, is usually the right choice. Everything else is packaging.

If you want a quick read on whether your current matchmaking is pulling its weight, the free networking gap calculator walks through it in six questions. It is the same diagnostic we use on the events we help redesign at All Along.