We run 10+ events per year. Can we build one AI reporting system that works for all of them?

Absolutely — that's the ideal use case. We'll help you build a unified AI analytics platform that ingests data from all your events (regardless of format or platform) and generates standardised reports while allowing customisation for event-specific metrics. Many participants report the biggest ROI comes from reusable AI reporting templates across their event portfolio.

Our event data is scattered across Zoom, Eventbrite, Whova, and SurveyMonkey. Will AI work with this fragmentation?

Yes. Most AI analytics tools we teach integrate with these platforms via APIs or CSV exports. We'll show you how to build AI data aggregation pipelines that consolidate fragmented data sources into a unified analytics database. Part of the programme includes mapping your specific data ecosystem and building integration workflows.

How do you handle attendee data privacy when using AI analytics on event data?

All AI tools we recommend comply with PDPA (Singapore, Thailand), PDPO (Hong Kong), and Indonesian data protection regulations. We teach data anonymisation techniques for aggregate reporting, consent management for individual-level analysis, and how to communicate AI analytics use transparently to attendees. During hands-on labs, we use synthetic event data — no real attendee data is required for training.

Can AI help us benchmark our events against competitors or industry standards?

Yes. We teach AI benchmarking techniques using industry-standard metrics (e.g., PCMA, ICCA, UFI benchmarks for conferences, exhibitions, and trade shows). We also show you how to create your own historical benchmarks by aggregating data across your event portfolio. For Southeast Asia MICE specifically, we provide regional benchmark data from Pertama's event analytics database.

What if our clients or sponsors have specific reporting requirements we need to meet?

Perfect — bring those requirements to the workshop. During the Use Case Development module, we'll help you build AI reporting templates tailored to your specific stakeholder needs (sponsor ROI reports, client satisfaction dashboards, internal leadership summaries). Many participants leave with customised AI report templates ready to deploy on their next event.

Training Solutions

SUMMIT-ROI

Cohort-basedSubsidy eligible

AI Post-Event Analytics & ROI Reporting

Event teams can independently deploy AI analytics tools for automated attendee satisfaction analysis, sponsor ROI measurement, content performance tracking, lead scoring, and industry benchmarking — reducing reporting time from 2-3 weeks to 2-3 days while delivering 4x more comprehensive insights to stakeholders.

Transform post-event reporting from manual spreadsheet compilation to AI-powered insights. Learn to automate attendee satisfaction analysis, sponsor value measurement, content performance tracking, lead scoring, and ROI benchmarking — delivering stakeholder reports in hours instead of weeks.

Duration2-3 days

InvestmentUSD $15,000 - $22,000

Best forEvent directors, MICE analytics teams, client services managers, and conference organisers responsible for demonstrating event ROI to sponsors, clients, and internal stakeholders across Southeast Asia

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THE CHALLENGE

Sound familiar?

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We spend 2 weeks after every event compiling reports manually. By the time we deliver, clients have moved on.

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Our sponsors ask for ROI data we can't provide — booth traffic, quality of leads, brand exposure metrics.

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Post-event survey response rates are 18%. We're making decisions based on tiny, biased samples.

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We have data across 5 different platforms (registration, app, survey, social media, lead capture) but no unified view.

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Our clients want to know which sessions delivered the most value, but we only have attendance numbers, not engagement quality.

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We can't benchmark our events against industry standards — every report is a one-off with no comparative context.

Trusted by enterprises across Southeast Asia

Financial Services

Healthcare

Education

Manufacturing

Professional Services

Government

OUTCOMES

What you'll achieve

Problems you'll solve

Post-event reporting taking 2-3 weeks of manual data compilation across fragmented platforms
Low survey response rates (15-25%) creating biased, incomplete attendee feedback data
Sponsor ROI measurement limited to basic metrics (booth visits) instead of lead quality and business outcomes
Content performance evaluation relying on attendance counts instead of engagement quality and learning impact
No systematic lead scoring from event interactions, resulting in poor sales follow-up prioritisation
Inability to benchmark events against industry standards or historical performance for continuous improvement

Value you'll gain

Time Savings: Reduce post-event reporting time from 2-3 weeks to 2-3 days using AI data aggregation and analysis
Data Completeness: Increase feedback data coverage from 20% (surveys) to 80%+ by analysing app interactions, social media, and behavioural data
Sponsor Retention: Improve sponsor renewal rates by 30% through comprehensive ROI reporting with lead quality metrics
Client Satisfaction: Deliver stakeholder reports 10x faster with AI-generated insights and visualisations
Continuous Improvement: Benchmark events against industry standards and historical performance to drive 15-25% YoY improvement in key metrics
Revenue Growth: Increase event pricing and sponsorship revenue by 20% with data-driven value demonstration

OUR PROCESS

How we deliver results

Step 1

Industry Assessment

We assess your current post-event reporting workflows, data sources, stakeholder requirements, and key metrics. This includes reviewing past event reports, sponsor deliverables, and client feedback to identify your highest-impact AI analytics opportunities.

Step 2

Curriculum Customisation

We tailor modules to your event types (conferences, trade shows, incentive travel), stakeholder needs (sponsors, clients, internal leadership), and data sources (registration platforms, mobile apps, CRM systems). All examples use real Southeast Asia MICE reporting scenarios and industry benchmarks.

Step 3

Hands-On Delivery

Interactive workshops where participants build AI analytics workflows using their actual event data. Each module combines concept explanation with immediate practice on tasks like automated data aggregation, sentiment analysis, lead scoring, sponsor ROI calculation, and benchmark reporting.

Step 4

Use Case Development

Participants develop 2-3 AI analytics use case proposals specific to their reporting needs — automated attendee satisfaction analysis, sponsor ROI dashboards, or content performance scoring — with implementation roadmaps and stakeholder presentation templates ready for immediate deployment.

Step 5

Adoption Support

30-day post-programme support includes office hours, Slack access, implementation coaching on your next post-event report, and a follow-up session to review AI analytics outputs and refine reporting templates based on stakeholder feedback.

What you'll receive

Event Analytics AI Maturity Scorecard
Customised Training Workbooks (one per module)
AI Analytics Toolkit (reporting templates, sentiment analysis models, lead scoring frameworks)
Event Analytics AI Use Case Playbook
90-Day AI Implementation Roadmap
Team Certification (individual + organisational)
Post-Programme Support Package (30 days)

Best for

Event directors, MICE analytics teams, client services managers, and conference organisers responsible for demonstrating event ROI to sponsors, clients, and internal stakeholders across Southeast Asia

IS THIS RIGHT FOR YOU?

Finding the right fit

This is ideal for you if...

Event agencies running 5+ events per year seeking to automate post-event reporting and improve stakeholder satisfaction
Conference organisers needing to demonstrate clear ROI to sponsors and increase renewal rates
MICE analytics teams overwhelmed by manual data compilation and looking for AI-powered efficiency gains
Client services managers responsible for delivering post-event reports to multiple stakeholders with tight deadlines
Event organisations seeking to benchmark performance against industry standards and drive continuous improvement

Consider another option if...

Individual event professionals (this is a team programme — try our AI Readiness Fundamentals instead)
Organisations running only 1-2 simple events per year without complex reporting requirements
Teams already using advanced AI analytics platforms and seeking cutting-edge innovation (try our Engineering tier)

See yourself in the list above?

Let's Talk

CURRICULUM

What you'll learn

2 days total

Understand how AI data aggregation, natural language processing, sentiment analysis, and predictive analytics transform post-event reporting. Learn which AI capabilities apply to which analytics challenges, and build a framework for measuring AI analytics ROI.

What you'll be able to do

Distinguish between AI data aggregation, NLP, sentiment analysis, and predictive analytics for event reporting
Identify 10+ specific AI applications across attendee feedback, sponsor ROI, content performance, and lead scoring
Map your post-event data ecosystem and integration opportunities across platforms
Evaluate AI analytics tools for conferences, trade shows, and hybrid events
Understand data quality requirements and privacy considerations for AI event analytics