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Event Technology

Event analytics that earn next year's budget

Every registration, check-in, session scan, meeting and lead already lives in one record. We turn that into live operations dashboards during the event and reports sponsors believe afterwards.

  • Live during the event
  • Sponsor and exhibitor reports
  • Warehouse exports and API
Who this is for

Four audiences, one set of records

Operations

Queue build-up, room capacity and printer health, minute by minute.

Marketing

Registration by source and campaign, conversion per stage, cost per attendee.

Sponsorship sales

Impressions, scans and session attendance per sponsor, ready for the renewal call.

Leadership

Attendance, engagement, revenue and NPS year on year, on one page.

What it looks like

The organiser dashboard

Illustrative event analytics dashboard: KPI tiles, check-ins over time, session popularity, a networking graph and no-show rate by ticket type Registered1,240 Checked in1,018 · 82% Meetings held312 Leads scanned2,760 Check-ins per 15 min 07:3009:0010:00 peak 08:15 Session attendance Keynote AI track Panel Workshop Closing Networking graph · attendees and exhibitors teal = exhibitor No-show rate by ticket type Paid9% Comp31% Exhibitor14%
Illustrative dashboard with sample data. The morning check-in curve sizes next year's entrance; the no-show panel tells you which comp codes to cap.
KPIs

The metrics we instrument by default

KPIHow it is measuredWho uses it
Registration conversionConfirmed registrations ÷ form starts, by source, coupon and ticket typeMarketing
Check-in rateChecked in ÷ registered, by ticket type and registration dateOperations, leadership
Arrival curveCheck-ins per 15 minutes per entranceOperations (next year's station count)
Session attendance and dwellDoor scans in and out, or app check-ins, per session and trackContent team, sponsors
App adoptionLogged in ÷ checked in; daily active users during the eventLeadership, app owner
NetworkingSuggestions shown, requests sent and accepted, meetings held, cards exchangedCommunity team, sponsors
Exhibitor leadsScans per stand, per hour, with rating distributionExhibitors, sponsorship sales
Sponsor exposureBanner impressions, clicks, sponsored session attendance, push opensSponsorship sales
SatisfactionSession ratings, event survey, NPS by audienceEveryone
RevenueGross and net by ticket type, coupon, source and registration weekFinance, leadership

Reading the numbers: three questions per event

Did we get the people we promised sponsors? Compare attendee roles and industries against the sponsorship pack, not just the headcount. A show that over-delivers on students and under-delivers on buyers has a sales problem next year.

Where did we lose people? The funnel shows drop-off at ticket selection or payment. The arrival curve shows the entrance that queued, and session dwell shows the rooms people left early.

What changes next time? Every report ends with a short list: cap these comp codes, add two kiosks at entrance A, move the panel out of the post-lunch slot.

Sponsor reports that get renewals

Sponsors do not renew on impressions. They renew when a report shows who attended their session, which roles visited the stand and what those people asked about. We build each sponsor report from the attendee record, show sample sizes, and send it within a week while the budget conversation is still open.

What we deliver

Dashboards, reports and feeds

Live operations dashboard

Check-in throughput, station health, room counts and lead scans with alerts to the ops channel.

Post-event report

One document, generated from the records, with the KPI table above, year-on-year comparison and a what-to-change list.

Sponsor and exhibitor reports

Per-sponsor exposure and per-exhibitor lead reports, branded, sent automatically after the show.

Attribution

Tracking links and coupons tie registrations to campaigns; AI analytics joins it with web and ad data.

Warehouse exports and API

Scheduled exports of every record to your warehouse, or an API for your BI tool.

Process

Decide the questions before the event, not after

  1. Define

    The ten questions leadership, marketing and sponsors will ask, and the KPI that answers each.

  2. Instrument

    Tracking links, session scanning, sponsor placements and app events configured so the data exists.

  3. Watch live

    Operations dashboard during the event, with someone owning each alert.

  4. Report

    Post-event and sponsor reports within a week, while renewals are still being discussed.

  5. Compare

    Year-on-year dashboards and forecasts that improve with each event in the data set.

Why one record matters

Analytics is only as good as the joins. When registration, check-in, the app and lead retrieval share one attendee record, every metric above is a query rather than a reconciliation project.

FAQ

Frequently asked questions

Which event KPIs should we track?

Start with registration conversion, check-in rate, session attendance, app adoption, meetings held, leads per exhibitor and survey scores. The KPI table on this page defines each and says who uses it. Add revenue by ticket type and source if you sell tickets.

Can we see data live during the event?

Yes. Check-ins per minute and per entrance, session room counts, app activity and lead scans stream to a live dashboard. Alerts fire when a queue builds or a printer stops.

Can sponsors and exhibitors get their own reports?

Yes. Each sponsor sees impressions, clicks, session attendance and scans attributed to them. Exhibitors see leads, booth traffic by hour and comparisons with the show average. Reports are generated from the same records organisers see.

Can we export everything to our own data warehouse?

Yes. Scheduled exports or an API feed every event, attendee, session, scan and meeting record to your warehouse. Finance and marketing can then join it with their own data.

Can analytics predict no-shows?

With two or three past events as training data, yes. We forecast no-show rates by ticket type and registration date, which informs over-booking and catering. See predictive analytics.

Ready to make AI work in production?

Tell us about your systems, your data and your constraints. We reply within one business day with a straight answer and a suggested next step.