Zoom Webinar Post-Event Analysis From Registration and Attendance Data
Learn what worked from numbers and feedback.
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Analyse a webinar. Data: registrations, attendees, join and leave times, poll results, Q&A counts, survey scores and comments, traffic sources: [WEBINAR_DATA]. Goals of the event: [GOALS]. Use anonymised data under our privacy rules and delete it when retention ends [VERIFY]. Report the funnel in order with a percentage at each step: registered, attended, stayed to the end, took part, gave feedback. Calculate attendance rate (400 registered and 212 attended is 53 percent), average time attended (38 of 60 minutes is 63.3 percent), drop-off points, poll participation, questions per attendee and average satisfaction, with arithmetic. Compare registration sources and times of day if the data allows, and suggest the best time for the next event. Summarise comments by theme with counts and one short anonymised quote each. State sample sizes and do not draw conclusions from small numbers. Return a table, five findings with evidence, three improvements for next time with a way to test each guess, and a short stakeholder report.
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Invented data: 400 registered, 212 attended = 53 percent. Average time attended 38 of 60 minutes = 63.3 percent. 130 voted in the poll = 61.3 percent of attendees. 41 questions = 0.19 per attendee. Survey average 4.2 out of 5 from 64 responses (30.2 percent response rate). Drop-off: 25 percent left at minute 25. Hypothesis: the first talk ran long. Test: shorten it by five minutes next time. Registration sources: email list 220 registrations with 135 attendees (61.4 percent); social 120 with 52 (43.3 percent); partner 60 with 25 (41.7 percent). Reading: the email list converts best. Comments theme counts from 64 responses: content praised 28, too long 12, audio problems 9, wanted more examples 15. Action: add a reminder email the day before for social registrants.
Illustrative only, made-up data. Your results will differ and must be reviewed.