What are the best practices for data collection and analysis during and after an event?

1 Choose your data sources and tools

Before you start collecting data, you need to decide what kind of data you want to collect, and how you will collect it. Depending on your event goals and objectives, you may want to gather data on demographics, attendance, engagement, satisfaction, learning outcomes, behavior change, or revenue. You also need to choose the right tools and platforms to collect and store your data, such as registration systems, surveys, polls, quizzes, analytics, social media, or CRM. Make sure you have a clear data strategy and a data management plan that outlines what data you will collect, when, how, and why.

2 Collect data during the event

During the event, you should aim to capture as much data as possible to assess the performance and attendees' experience. Live feedback tools such as live polls, Q&A sessions, chatbots, or social media hashtags can be used to obtain opinions and gauge the level of interest, engagement, and satisfaction. Passive tracking tools like RFID, QR codes, GPS, or web analytics can measure attendance, participation, and movement of attendees. Content analysis tools such as video recordings, transcripts, or sentiment analysis can be used to evaluate the relevance, clarity, and effectiveness of speakers, sessions, and materials. These measures can help capture key insights and learnings from the event.

3 Analyze data after the event

After the event, you want to analyze the data you collected and turn it into actionable insights and recommendations. Descriptive analysis can be used to summarize and visualize your data with the help of dashboards, charts, or tables. This will help you identify trends, patterns, and outliers in your data and compare it with your goals and benchmarks. Inferential analysis can be used to test and validate hypotheses with statistical tests, correlation, or regression. This will help you understand the causes and effects of your data as well as measure the significance and reliability of your findings. Predictive analysis can be employed to forecast and optimize outcomes through machine learning, artificial intelligence, or simulation. This will help you anticipate the future behavior and preferences of your attendees while also identifying the best strategies and actions to improve your event performance.

4 Report and communicate your data

Once you have analyzed your data, it is important to report and communicate your findings to stakeholders such as clients, sponsors, partners, or team. You can use various formats and channels to communicate your data, including reports, stories, and presentations. Reports should be comprehensive and detailed, highlighting the data collection and analysis process, findings, insights, and recommendations. Stories should be engaging and compelling, focusing on the data collection and analysis journey, challenges, successes, and learnings. Presentations should be interactive and dynamic, showcasing the data collection and analysis results, impact, and value. When creating these materials make sure they are clear, concise, consistent, relevant, personal, emotional, informative, visual, and conversational.

5 Learn and improve from your data

To learn and improve from your data and inform future event planning and production, you can use evaluation, action, and innovation methods and tools. Evaluation can help you assess your data collection and analysis process, outcomes, and feedback using SWOT analysis, surveys, or interviews. Action involves implementing and monitoring your recommendations, actions, and changes with project management software, checklists, or KPIs. Innovation involves experimenting with methods, techniques, and tools like brainstorming, prototyping, or testing to explore new possibilities and solutions. This will help you stay ahead of the curve.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?