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Predictive Recommendation Engine to Match Event Attendees with the Right People and Content (closed)

GlobalSign.In
This challenge has closed.
Audience: Students, Researchers, Start-Ups, Businesses, Subject Matter Experts, Other
Anticipated Funding: SGD 35,000
Applications close: February 14, 2020
Last Updated: February 16, 2020 10:08 PM
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The Challenge

SACEOS is the trade association of the meetings, incentives, conventions and exhibitions (MICE) industry in Singapore, to promote growth development and enhance the infrastructure as well as the capabilities of the MICE industry. GlobalSign.In (GSI), a member of SACEOS, is a leading event technology company that builds software for events, providing a whole range of service for events, from pre to during to post event. Their event management tools help a broad range of users like corporates and enterprises, MICE (meetings, incentives, conferences, and exhibitions) organisers, government agencies, associations and education institutions, power training and events of any size and cater to a wide range of event planning requirements.

As a service to event organisers, they have been providing an integrated platform for conference organisers to manage all kinds of processes from pre-event communications to actual day event processes like registration and event info to post event follow up and connections.

Over the years, the widespread use of the mobile phone as a personal and work device to access online information has changed the way conferences and exhibitions are run. Besides just content and product information, customers are looking for new and more curated experiences. Professionals visiting tradeshows and conferences hope to have more meaningful connections made, not just how many they make. They hope to gain access to the right exhibitors quickly and have less time and tolerance for general browsing.

As part of their commitment to deliver more personalised services to their clients, GSI hopes to enhance the professional attendee experience by leveraging on technology to provide better matches for the professional attendee so that they can make the most appropriate connections to the right conference exhibitor, fellow attendee and conference organiser. They hope to do this by leveraging on the increased availability of data sources today to capture more comprehensive customer information and using AI and machine learning to build a smart engine that would enable predictive matching that is personalised and relevant to the professional conference attendee.

Their vision is to create a way for professional attendees to make the most meaningful connections in the shortest amount of time at each conference or trade show they go to. At the heart of it, is a smart engine that is capable of analysing large amount of profile data to provide predictive recommendations on matches that meet the needs of professional attendees. This smart engine would be able to integrate into event organisers’ own platforms in multiple ways and power new applications (i.e. chatbots) that would facilitate the process of matching.

Problem Statement

How might we create a predictive engine for more accurate match rate for professional event attendees to networks and content during and after the event?

What They Are Looking For

  • A Proof-of-Concept (POC) solution that matches interest of professional conference attendees to relevant connections, enabled by a smart matching engine. The solution will be open-sourced and need to include:
    • An AI engine that is able to process data from different event data sources and perform data analytics to predict and recommend ‘matches’ that will be beneficial for the potential event attendee.
    • The matches should include (but are not limited) to the following connections that are key to a successful attendee experience.
      • Attendee-to-Attendee connections (E.g. connecting the professional attendee to potential partners, collaborators or clients who might be at the same event)
      • Attendee-to-Content (E.g. connecting the professional attendee to live sessions and tracks they may be interested in attending)
      • Attendee-to-Exhibitor (E.g. connecting the professional attendee to the right solution provider in the exhibition area)
      • Attendee-to-Organiser (E.g. connecting the professional attendee to key content that was missed out during the event, allowing the attendee to feedback on topics that they are interested to see in the next event)
    • In order to do this, the AI engine should be smart enough to capture data from different sources to build an accurate profile of the attendee and related parties to be connected with.
    • The engine should be able to leverage on Machine Learning to become more accurate over time as more data is collected over more events.
    • The output of the matches should create new value to the professional attendee with the following performance measurements:
      • Pre-event:
        • Accurate recommendations on sessions and talks to attend.
      • During Event:
        • Increased accuracies of accessing the right content.
        • Increased accuracies of meeting the right people.
        • Increased opportunities for business development.
      • Post-event:
        • Better and more intuitive follow-ups on contacts and solution providers.
        • Recommendations on content (video recording, slides, articles) missed out during event.
    • The engine should expose an API to make it pluggable to other platforms.

There are no restrictions on the geographic location of the problem solvers who may choose to apply to this challenge. However, the POC needs to be demonstrated in Singapore.

Eligibility Criteria

There are no restrictions on the geographic location of the problem solvers who may choose to apply to this challenge. However, the POC needs to be demonstrated in Singapore.

You, (or any of your teammates, if you are participating in the Challenge as a team) must not be a current employee of (a) GSI, or (b) any other organisation who is involved in administering or organising the Challenge (including IMDA).

For full details on this challenge please see the SG:D Open Innovation Platform website.

Terms and Conditions

For full details on this challenge please see the SG:D Open Innovation Platform website.

How to Apply

To apply for this challenge please see the SG:D Open Innovation Platform website.

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