AI-Recommended Webinar & Event Topics
Turn customer signals into high-demand event topics. AI analyzes needs, behaviors, and support queries to recommend sessions with 91% topic relevance and lift attendance by 46%—in hours, not days.
Executive Summary
Customer marketing teams can replace manual topic brainstorming with AI that mines product usage, support queries, NPS comments, and behavioral data to recommend webinar/event topics. Typical 10–20 hours across 11 steps compresses to 2–3 hours with ~85% time savings, while precision targeting increases attendance and engagement.
How It Works
Inputs include CRM segments, CS tickets, product telemetry, community threads, and campaign performance. The agent scores each topic on relevance and expected engagement, then generates promotion copy variants per channel.
What Changes with AI?
🔴 Manual Process (11 steps, 10–20 hours)
- Customer needs analysis (2h)
- Topic research (1–2h)
- Relevance scoring (1h)
- Event planning (2–3h)
- Promotion strategy (1–2h)
- Registration optimization (1h)
- Attendance tracking (1h)
- Engagement measurement (1h)
- Feedback collection (1h)
- Optimization (1h)
- Future planning (1–2h)
🟢 AI-Enhanced Process (2–3 hours)
- Ingest behavioral & support data; auto-cluster needs
- Generate ranked topic list with predicted demand
- Auto-draft titles, abstracts, and channel copy
TPG standard practice: Keep human-in-the-loop approvals for low-confidence topics; A/B test copy variants per segment and preserve raw feature importance for future learning.
Key Metrics to Track
How to Operationalize
- Define segments: ICP, role, lifecycle stage, product tier.
- Connect data: CRM, MAP, CS platform, product analytics.
- Feedback loop: Post-event surveys auto-train the model.
- Governance: Approval thresholds and bias checks per segment.
Recommended AI Tools
These tools integrate with your marketing operations stack to automate topic discovery and cross-channel promotion.
Implementation Timeline
| Phase | Duration | Key Activities | Deliverables |
|---|---|---|---|
| Discovery | Week 1 | Define segments, success metrics, and data access | Measurement plan & data map |
| Integration | Weeks 2–3 | Connect CRM/MAP/CS, configure topic model & scoring | Working topic pipeline |
| Pilot | Weeks 4–5 | Run 2–3 events, compare AI vs. control topics | Pilot report w/ lift & learnings |
| Scale | Weeks 6–8 | Rollout to all segments, automate copy variants | Playbooks & dashboards |
| Optimize | Ongoing | Refine models with post-event feedback | Quarterly improvement plan |
Process Comparison
| Category | Subcategory | Process | Metrics | AI Tools | Value Proposition | Current Process | Process with AI |
|---|---|---|---|---|---|---|---|
| Customer Marketing | Customer Communication & Engagement | Recommending webinar or event topics based on customer needs | Event attendance rate, Topic relevance score, Customer engagement increase | Intercom Fin AI, Customer.io, Braze AI | AI-powered platforms deliver personalized, timely communications across all channels with automated workflows that adapt to customer behavior and preferences in real time | 11 steps, 10–20 hours (see Manual Process) | AI analyzes customer behavior and support queries to recommend event topics with 91% relevance accuracy, increasing attendance by 46% (2–3 hours, ~85% time savings) |