Webinar Attendance and Drop-Off Analysis
Analyse webinar registration, attendance and viewing time data to see where people drop out and what to change next time.
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[VERIFY] is an editorial flag, not a blank to fill. Wherever the prompt shows [VERIFY], check that item against a reliable source before you use it.
Help me understand my webinar results. I will paste the numbers: registrations [REGISTRATIONS], attendees [ATTENDEES], attendees still present at each quarter of the session [RETENTION_BY_QUARTER], average watch time [AVERAGE_WATCH_TIME], replay views [REPLAY_VIEWS], and conversions or next-step clicks [NEXT_STEP_CLICKS]. I will also paste the session outline with minute markers: [SESSION_OUTLINE]. Registration sources, if known: [REGISTRATION_SOURCES]. Calculate and show the arithmetic: 1) Attendance rate (attendees divided by registrations), live-to-replay ratio, and conversion rate based on attendees and on registrations. 2) Drop-off between each quarter as counts and percentages, and the largest single drop, matched with the outline content at that point. 3) A findings table with the columns Observation, Evidence, Possible cause (stated as a hypothesis), and Test for next time. 4) Which of the causes sit before the webinar (promise, reminders, timing) versus during it (pace, content, tech). 5) A plan with three changes to try, each measurable. Rules: use only the numbers pasted; do not quote industry benchmarks, because I have not supplied any and they vary widely. If counts are small, say that differences may be chance. Platform attendance definitions differ (joined versus watched a set time), so mark definitions [VERIFY] with the platform's documentation. Do not predict revenue.
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