Why Mobile + Big Data = The Future of Events

May 11, 2013

Mobile + Big Data = Future of Events

Introduction

Lindsey Rosenthal (@eventsforgood) and Liz King (@lizkingevents) host a fabulous online radio show called Event Alley Show. On a recent episode, Lindsey and Liz interviewed Joe English about the future of events. Joe is Creative Director, Intel Developer Forums (at Intel). I was captivated by Joe’s take on the future of events:

The future is about contextual tools that bring information sources together about the audience.

When I ponder the future of events, I tend to jump directly to mobile apps, location awareness and other features tied to the smartphone. Upon further reflection, it occurred to me that mobility is a feature: part of a larger picture. And the larger picture is about the impact that events can make. In other words, what Joe said (above).

The mobile technologies of today will morph into new forms (of technology) tomorrow. So technology is the tool that facilitates context about the audience. And the better events can deliver “attendee intelligence” to sponsors, the more effective sponsorships will be.

Let’s take a closer look.

Step 1: Mobile-enable Event Attendees

The Double Dutch mobile event app

Image via Double Dutch.

Historically, events have been an inefficient medium, as far as data capture goes. Think about all of the “micro transactions” that occur within an event and how we’ve existed all these years without capturing them. Baby steps were made with post-event web surveys, RFID and badge scans, but the game changer has been mobile apps.

So step 1 in the future of events is already here. Event planners can choose from a wealth of mobile event apps. Michelle Bruno published an excellent overview of the mobile app vendors at Event Tech Brief.

Mobile event apps provide a personal assistant to help event attendees find the right content, meet the right people and generally get the most out of their experience. Meanwhile, all of the activity enabled by the app creates a stream of data that can turn into actionable intelligence when aggregated and interpreted.

Step 2: Aggregate Data Sources into a Common Repository

Image via Grzegorz Łobiński on flickr.

There’s an opportunity for a new player to emerge in Step 2. And that’s a vendor-neutral “Switzerland,” who builds interfaces for the industry’s vendors to exchange data (from the vendor’s applications into Switzerland). Here are just some of the many data sources that exist at an event:

  1. Mobile event apps.
  2. Registration.
  3. Online/hybrid events platforms.
  4. Badge scanners.
  5. Twitter.
  6. Survey systems.
  7. Photo sharing services.
  8. Third party location apps (e.g. Foursquare).
  9. Other social network apps.

The role of Switzerland is to combine proprietary data (from vendor applications) with publicly available data (e.g. public check-ins, tweets and other social streams) into a common data repository. From here, the next step kicks in.

Step 3: Apply Big Data to Deliver Attendee Intelligence.

We now apply Big Data technology against this enormous pool of event-specific data. Let’s return to the vision of Joe English: “contextual tools that bring information sources together about the audience.” Let’s consider a few applications of this.

An eHarmony for Events

Photo source: User VideoVillain on flickr.

Amazon makes awesome product recommendations for you because it’s gotten to know you (via your mouse clicks) and it compares your “profile” to what similarly profiled people have purchased. Via our new data repository, we’ve now collected a wealth of event data.

So now we can apply some science (similar to what eHarmony does to pair couples) to pair attendees to attendees and sponsors to attendees. As an attendee, wouldn’t it be neat for Big Data to tell you, “here are the three sponsors you should go visit today.”

Intelligence to Make Sponsors Smarter

Imagine mining the Big Data repository to provide aggregated intelligence profiles to sponsors. Activity data could be sliced and diced across numerous dimensions, including topic and frequency.

For instance, at a healthcare event, the analysis identifies the particular healthcare sub-topics that are receiving the most interest. Throw in a little sentiment analysis on top of this (e.g. from profiling public data and event-specific chatter) and you have some interesting possibilities.

With this sort of data crunching, attendee intelligence could tell sponsors:

  1. The specific sub-topics to focus on.
  2. The probability that particular profiles of attendees will engage with you.
  3. Whether attendee sentiment positive, negative or neutral about your company.

While this technology won’t deliver more visitors to your booth, the intelligence gained can allow you to adjust tactics “on the fly,” resulting in a more organic uptick in attendee engagement with you.

Intelligence for The Event Planner

By aggregating activity and engagement data (from attendees) and marrying that with sentiment analysis, event planners can infer attendee satisfaction. The thinking goes: the more engaged and active you were, the more you enjoyed the event.

Throw in the sentiment analysis and you can validate this. So you’d now have this option: instead of surveying attendees about your event, you can use Big Data to give you the answer implicitly.

Conclusion

So that’s my take on how technology can be applied to generate the contextual tools needed for attendee intelligence. I’d like to thank Lindsey, Liz and Joe for inspiring this post!


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