B2B Event Matchmaking Software: How AI Matching Works

What B2B event matchmaking means

Matchmaking is the step before scheduling: deciding who should meet whom. At a business event it takes three common forms.

• Attendee to attendee. The event app suggests other attendees worth meeting, and people send each other meeting requests.
• Buyer to seller. Buyers are matched with exhibitors or suppliers. In a hosted buyer programme, the organiser invites vetted buyers who commit to a set number of pre-scheduled meetings with exhibitors.
• Customer to expert. Someone asks to meet your company, and you decide which of your people should take the meeting.

The first two are run by the event organiser, on the organiser's platform, across everyone at the event. The third is run by one company for its own team, and we cover it in how to schedule better meetings at business events.

This post is about the first two, which is where most "AI matchmaking" claims are made. For AI across scheduling more generally, see AI meeting scheduling for B2B teams.

How AI matchmaking works

Whatever a vendor calls it, event matchmaking works from three kinds of input.

• What people say. Job title, company, industry, the interests they tick at registration, and what they are at the event to do: buy, sell, hire, invest, or meet peers.
• What people do. Sessions saved, profiles viewed, exhibitors searched for, suggestions accepted or skipped.
• What the organiser sets. Who may meet whom, how many meetings each person can take, and which groups get priority.

From these, the system scores how well two people fit and shows each attendee a ranked list of suggestions. Some tools also show what the two have in common.

Three things are worth understanding about that list.

It is a recommendation, not a decision. A person still chooses whom to ask, and the other person usually has to accept.

Similar is not the same as useful. Two heads of procurement at rival companies look alike on paper. A buyer and a seller look different, and are the better match. Good matchmaking pairs what one side wants with what the other offers, which only works if the system asks both questions.

It has little to go on at the start. A first-time attendee who has not opened the app has given it no behaviour to learn from. Until they do, they are matched on their registration answers alone.

How event platforms describe their matchmaking

Described broadly, from what each vendor publishes:

• Grip describes AI matchmaking that combines what participants say at registration and onboarding with how they behave in the app, including whether they mark a suggestion as interesting or skip it.
• Brella asks attendees to choose interests and an intent for each, such as networking, trading, investing, or recruiting, and suggests connections from those.
• Swapcard describes AI recommendations for people, exhibitors, and sessions, and shows what an attendee has in common with a suggested contact.
• b2match is built around business profiles in which participants say what they offer and whom they want to meet. On the event pages we looked at, a meeting request has to be accepted before it is scheduled.
• Cvent offers attendee recommendations and appointment scheduling between attendees, exhibitors, and sponsors as part of its wider event platform.

The mechanics are more alike than the marketing suggests: stated interests, behaviour, and organiser rules, producing a list for a person to act on. The differences that matter are in what the system asks attendees, what the organiser can control, and what happens after a match is accepted.

Several vendors publish their own figures for recommendations made or meetings accepted. Treat those as the vendor's claims, and ask for results from an event like yours. Features change, so check each vendor's own site. We looked in October 2026.

Where event matchmaking goes wrong

• Thin profiles. Matching is only as good as the answers behind it. If registration asks for a job title and nothing else, the suggestions will be generic. Ask what people want from the event, at a point where they cannot skip the question.
• One-sided value. Every exhibitor wants to meet every buyer. Buyers want to meet a few. Without a limit on requests and a real option to decline, the buyers everyone wants are flooded and stop opening the app.
• Popularity. The most senior people on the list receive far more requests than they can take. A cap for each person protects them.
• Ranking nobody can see. If the organiser or a sponsor can influence who appears at the top of the list, attendees should be told.
• Tracking people did not expect. Matching on behaviour means recording what attendees view and search for. That is personal data. Say so plainly at registration, and let people opt out of matchmaking without losing the rest of the event app.
• Weak commitment. A meeting that an app suggested between two strangers is easy to skip. The fixes are the same as for any event meeting: confirm, remind, and make rescheduling easy.

A match is not a meeting

This is the failure that matters most, and it has nothing to do with AI. A match says two people should talk. A meeting needs a time both are free, somewhere to sit, and, for anything commercial, the right person from the selling side.

Matchmaking tools handle the first part. The rest is a scheduling problem:

• A time. Both diaries, the conference sessions each person plans to attend, and the walk between halls.
• A place. A table in the networking area or a room at the stand, reserved in the same step as the time. Meeting space needs planning as carefully as people's time.
• The right person. The exhibitor's contact in the event app is often whoever registered the stand. The buyer wanted the product specialist.

For exhibitors there is a further catch. The organiser's app knows about the meetings booked through it. It does not know about the ones your team booked directly, or about your own rooms. Two systems that both hold your experts' time is how double bookings happen.

Some shows go further than matching and book the appointments themselves. See hosted buyer programmes for how pre-scheduled appointment diaries work.

How exhibitors can get more from matchmaking

If you are exhibiting at an event that offers matchmaking:

1. Write the company profile in the buyer's words. Describe what you offer in the terms a buyer would tick at registration, not in your product names.
2. Put your specialists in the app. People are matched with people, so the profile should not stop at whoever organised the stand.
3. Do not rely on it alone. Recommendations reach the attendees who use the app. Your own target list and pre-event outreach reach the accounts you chose.
4. Know your capacity before you accept. Work out how many meetings your team can actually hold, then accept requests against that number.
5. Bring every meeting into one schedule. Matched meetings, outreach meetings, and walk-ups compete for the same people and rooms, so they belong in one meeting programme.
6. Route each accepted request. Read what the buyer asked for, assign the person on your team who can answer it, and tell them why they are in the meeting.
7. Record what happened. Knowing which matched meetings were held, and what came of them, is the only way to judge whether the event was worth it.

Questions to ask about event matchmaking software

For organisers choosing a platform, and for exhibitors deciding how much to rely on one:

1. What does matching use: stated interests, behaviour in the app, or both?
2. What does a first-time attendee with an empty profile see?
3. Does it pair what one side wants with what the other offers, or only find similar people?
4. Does a meeting need both sides to accept, and can each person limit how many requests they receive?
5. When a meeting is confirmed, are the time and the place reserved together?
6. Can attendees see why someone was suggested, and can sponsorship change the ranking?
7. What are attendees told about tracking, can they opt out, and is their data reused at other events or to train models?
8. Can exhibitors export their meetings, or sync them with their own schedule?
9. What can you report afterwards: meetings requested, accepted, and held?

The fifth and eighth decide whether matches turn into meetings.

This guide is written by the team building CallShark, so treat it as informed rather than neutral. CallShark is not an event-wide matchmaking platform and has no AI features. It is being built for the step after the match: routing each request to the right expert on your team, and reserving that person, a room, and a time together. The product is temporarily down.