Automate Webinar Topic Suggestions with AI

Executive Summary

AI surfaces webinar topics with the highest predicted relevance and engagement by correlating behavior data, content trends, and historical performance. Replace a 6–15 hour manual process with a 18–40 minute automated workflow that outputs data-backed recommendations and a scheduling plan.

How Does AI Improve Topic Selection?

Topic intelligence blends interest scoring, audience fit, and lookalike analysis from prior webinars to forecast registration and engagement. Teams move from intuition-led choices to evidence-driven topics that convert.

Agents continuously learn from registration patterns, attendance rates, Q&A depth, and on-demand consumption to refine future topic recommendations and timing.

What Changes with AI Topic Intelligence?

🔴 Manual Process (10 steps, 6–15 hours)

Research audience interests and industry trending topics (2–3h)
Analyze previous webinar performance and engagement data (1h)
Evaluate competitor webinar topics and responses (1–2h)
Assess themes that drive highest registrations (1h)
Generate topic ideas from customer pain points (1h)
Test with surveys and feedback (1–2h)
Optimize topic selection based on predictions (30m)
Create content strategy and schedule (1h)
Monitor registration and interest signals (30m)
Refine selection based on performance (30m–1h)

TIME-INTENSIVE RESEARCH AND VALIDATION

🟢 AI-Enhanced Process (3 steps, 18–40 minutes)

Automated topic research with audience interest analysis (15–30m)
AI topic suggestions with engagement and registration prediction (8–10m)
Strategy optimization with performance forecasting (5m)

≈95% TIME REDUCTION

TPG approach: Calibrate models to ICP segments and lifecycle stage, enforce diversity across formats (live, panel, demo), and log rationale with confidence scores for governance.

Key Metrics to Track

80%+

Topic relevance score

15–30%

Predicted registration uplift

60%+

Attendance rate target

4.0/5

Engagement quality score

Metric	Definition	Target	Owner
Topic Relevance Scoring	Composite score based on audience fit, trend velocity, and thematic alignment	≥ 80%	PMM / Content Strategy
Audience Interest Prediction	Forecasted probability that a topic will exceed median registration	≥ +20% vs. median	Marketing Ops
Registration Optimization	Expected lift in sign-ups from title, abstract, and timing refinements	+10–30%	Demand Gen
Engagement Forecasting	Projected attendance rate and interaction depth (Q&A, poll completion)	≥ 60% attendance; 4.0/5 quality	Events Team

Recommended AI Tools

ON24 AI

Predicts topic performance and optimizes titles and abstracts for higher registrations.

Zoom Webinar AI

Analyzes audience behavior and suggests topics and formats to boost live engagement.

GoToWebinar Intelligence

Surfaces interest trends and recommends scheduling windows for maximum attendance.

These platforms connect to your marketing operations stack to automate research, scoring, and forecasting across your webinar calendar.

Use Case Overview

Category	Subcategory	Process	Primary Metrics	AI Tools	Value Proposition
Content Marketing	Event & Webinar Content Support	Automating webinar topic suggestions	Topic relevance, interest prediction, registration optimization, engagement forecasting	ON24 AI, Zoom Webinar AI, GoToWebinar Intelligence	AI recommends high-impact topics that maximize registration and engagement

Process Comparison

🔴 Manual Process (6–15 hours)

Audience and trend research
Historical performance analysis
Competitor benchmarking
Theme assessment for registrations
Idea generation from pain points
Survey testing and feedback
Prediction-based optimization
Strategy and schedule creation
Registration monitoring
Ongoing refinement

MANUAL, MULTI-SOURCE RESEARCH

🟢 AI-Enhanced Process (18–40 minutes)

Automated topic research and scoring
AI suggestions with registration and engagement predictions
Strategy optimization and calendar updates

SUSTAINED, DATA-DRIVEN TOPIC PICKS

Implementation Timeline

Phase	Duration	Key Activities	Deliverables
Assessment	Week 1–2	Audit webinar data sources; define scoring rubric and success metrics	Topic intelligence framework
Integration	Week 3–4	Connect webinar platform, CRM, analytics; enable feedback loops	Unified dataset & scoring pipeline
Training	Week 5–6	Calibrate for ICP, segments, and lifecycle; tune thresholds	Custom models & thresholds
Pilot	Week 7–8	Run recommendations for next cycle; compare against control	Pilot results & playbook
Scale	Week 9–10	Automate calendar, alerts, and content briefs	Productionized workflow
Optimize	Ongoing	Refine scoring, add formats, update seasonality	Quarterly improvement plan

Frequently Asked Questions

How are topics scored for relevance?

Scores combine audience fit, trending velocity, historical performance, and competitive saturation to prioritize topics with the best upside.

Can AI handle niche technical audiences?

Yes. Models are calibrated with your content taxonomy and past sessions to recognize specialized interests and tailor suggestions accordingly.

What data is required to start?

Basic webinar performance data (registrations, attendance, engagement), content tags, and target personas. Additional CRM and intent data improve predictions.

Will this replace our event team?

No. It augments planning by accelerating research and providing predictions. Your team still selects topics, formats, and speakers.