Augmented Reality & Sports | Riffing on AR (Part III) Guest Blog

Gravity Jack In the Press

The following is part 3 of an augmented reality guest blog series, from Mike, at RecKoNation.

While users are waiting for sporting events to begin they could purchase and download official datasets from their favorite teams. They may be able to view the datasets by date or big game.

It would also be possible to ‘Augment stats’- that is, users could advance through the game they are currently watching, inning by inning or quarter by quarter and see the big plays or track trends in where the action is occurring on the field.

Monetization

Generally speaking, the app and tools should be free to help catalyze rapid adoption.

There are a number of angles in which the platform could be monetized including some of the following ideas:

  • Sponsorship – A session or a dataset would be sponsored by a company for a fee
  • Paid Premium Content Creation Feature Set – Premium Content Creators (e.g. Official Boston Red Sox) would pay a yearly subscription fee for access to premium features in the content editor. This would make them ‘official’ creators of premium content for the platform. The datasets would look more polished and may be more interactive because of the enhanced feature set they would be using for creation and editing.
  • Banner Ads – Banner ads would be served in the app – the user could ‘turn them off’ for a small fee
  • Paid Download of Premium Feature Sets – The ‘Official Gettysburg Data Set from the National Parks Dept. would be available for a small fee.

Note- At first blush the sponsorship model seems the least attractive of these ideas. In order to support the deployment of such a system, alot of support in terms of infrastructure, business relationships and sales would be needed.

Socialization and Datasets

There would be two classes of datasets ‘Free’ and ‘Premium’. Premium datasets are vetted and created by professionals and available for purchase while free datasets can be created by anyone.

Users will have the ability to ‘vote’ and rate data sets (ala Yelp or really any customer review-based app) and filter and search for relevant datasets via their mobile client.
When loading datasets users could filter out lower rated datasets.

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