Scenarios

Scenarios

Based on our personas, we have predicted some possible scenarios of people interacting with the Aura system in order to accomplish specific tasks.

Scenario 1: Dave

As described in personas, Dave, 22 is a casual internet lurker and a user of Aura. Aura keeps him engaged with its gamification strategies, and helps him pick content based on his mood and recent activities.

  1. Dave registered an Aura account.
  2. Dave assesses his personal social media experience using his Facebook, Twitter and Instagram accounts.
  3. Aura gives him an overall mark for his social media experience according to things he posted on these three social media.
  4. Dave does a quiz about emotion and mood test and gets the result immediately.
  5. Dave finds this result very interesting, so he shares the link to his results to his friends and invites them to join Aura too.

Scenario 2: Richard

Richard, 40 is the recruiting manager at a media company. Richard has a very busy life and needs to fill a vacancy really quickly with an appropriate writer. He needs to know the writing style of the applicants, and the effect they have on readers without having to go through all their work manually. He uses Aura to index and builds a report on the writing characteristics of all applicants.

  1. Richard subscribes Aura’s business account.
  2. By using the sentiment analysis system of Aura, Richard searches for applicants of his company.
  3. Aura system gives Richard results of sentiment analysis of his candidates that reflect their personalities and characteristics.
  4. Richard finds Dave (Scenario 1) matches his requirements best.
  5. Richard recruits Dave as a new writer of his media company.

Scenario 3: Meera

Meera, 29 is a marketing manager in an online video streaming company. She wants to optimise the marketing budget, by specifically targeting audiences with content based on their current state of mind. She uses Aura to view the recent online activity of the user and suggest a content, or save the budget by skipping the particular user as there are no close matches.

  1. Meera and her company join Aura’s business account.
  2. Meera uses Aura sentiment analysis system to scan data and information on social networking sites.
  3. Aura system tell Meera Internet users’ comments about online video streaming are mostly positive, and users aged between 18 and 35 and interested in computer games will be concerned about online video streaming.
  4. Meera concludes results from Aura and decides to pay more attention to manage their users aged between 18 and 35 and like playing computer games.
  5. Meera would like to cooperate with some game companies to expand the business, for example, Steam.

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