mooga sony music case study (update april. 09)

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Sony BMG was looking to enter the market with a differentiated service that was unlike any other competitor offering. •The approach taken by Mooga was seen as ground breaking and market leading •Mooga is currently connected in Argentina and being connected in other four South American countries •This is the first mobile music portal with intelligence in the market.

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Page 1: Mooga Sony Music Case study (Update April. 09)
Page 2: Mooga Sony Music Case study (Update April. 09)

To provide highly relevant and extremely personalized context-based end user

experiences for the digital world (mobile/online/voice/DTH/ipTV/Set-top Boxes/etc.)

Page 3: Mooga Sony Music Case study (Update April. 09)

  iKen Solutions is a NASSCOM Innovation Awards 2008 Finalist

  iKen Solutions selected by Microsoft to participate in Le Web ´08 as one of the Top 10 innovative startups in the world.

  iken Solutions won the Tie-Canaan Entrepreneurial Challenge 2008.

  Mooga won Silver Award for “Best Technology Innovation” at the Mobile Content Awards 2008.

  iken Solutions was awarded direct entry into the Microsoft Start-up Accelerator Program.

Page 4: Mooga Sony Music Case study (Update April. 09)

Current Scenario

Page 5: Mooga Sony Music Case study (Update April. 09)

Help|Cost|Home

Search

Everybody gets the same

Page 6: Mooga Sony Music Case study (Update April. 09)

  Content providers and Carriers select the “hottest” and latest content to be marketed to consumers.

  The best sellers of each period are profitable, so therefore “safe”.

  Consumers are constantly updated with new content as operators continuously reinvent their portfolios.

  No longer “hottest” = No longer relevant or profitable.

NEWBeyonceSong

1yearlater

BeyonceSong

6Monthslater

BeyonceSong

Static limited offer placement

Page 7: Mooga Sony Music Case study (Update April. 09)

The evolution of digital business

Page 8: Mooga Sony Music Case study (Update April. 09)

• The Pareto Principle: 80/20 rule, traditional pattern of sales concentration.

• C. Anderson (WiredMagazine-2004): The Long Tail

  By lowering inventory storage, distribution and search costs, digital markets have the potential to increase the collective share of niche products, creating a longer tail in the distribution of sales.

  Now there are 2 markets to attack:

•  Old Market: Top Sellers.

•  New Market: Long Tail.

What percentage of your items are you selling at least once a month?

Page 9: Mooga Sony Music Case study (Update April. 09)

• James Surowiecki (2004): Wisdom of Crowds

• A diverse collection of independently-deciding individuals is likely to make decisions and predictions better than individuals or even experts.

o Lego: encourages its fanatical customers to design their products.

o InnoCentive.com: Companies pay solvers from $10k to $100k per solution. More than 30 percent of the problems posted on the site have been cracked.

The Many Are Smarter Than the Few

Page 10: Mooga Sony Music Case study (Update April. 09)

Make everything available, help your customer find it and you will increase your sales.

Page 11: Mooga Sony Music Case study (Update April. 09)

Mooga The new wave

Page 12: Mooga Sony Music Case study (Update April. 09)

Dynamic personalized one to one offer

Page 13: Mooga Sony Music Case study (Update April. 09)

  Adaptive subscriber storefronts lead to infinite mobile shelf space and time

  Subscriber analytics and recommendation engines allow the long tail of niche markets to form across the content universe

  Incentive-based subscriber self-distribution allows for spread of mobile content and for easier content discovery across users

SpidermanIClips

BeatlesOldies

StarWars

2005SpringFashionClip

20,000 80,000andongoing

BlackEyePeasSongs

Elvis’sHits

SpidermanIII

FergieSongs

Page 14: Mooga Sony Music Case study (Update April. 09)

Viral self learning entertainment ecosystem incorporating Artificial Intelligence techniques to understand, track, predict & recommend

content based on individual user tastes, downloads & popular contents.

Page 15: Mooga Sony Music Case study (Update April. 09)

iKen Studio (Hybrid AI framework)

Page 16: Mooga Sony Music Case study (Update April. 09)

Mooga: a consumer 3.0 analytic

N=1 Plat-form

Dynamic Behaviors

and Interactions

Personal Profile

Wisdom of crowds &

Market info

Compliance, policy and Business

Rules

Contents Products

and Services

Personal Preferences

Personalized Experiences

Page 17: Mooga Sony Music Case study (Update April. 09)

Case Study

Page 18: Mooga Sony Music Case study (Update April. 09)

  Sony BMG was looking to enter the market with a differentiated service that was unlike any other competitor offering.

  The approach taken by Mooga was seen as ground breaking and market leading.

  Mooga is currently administrating SonyBMG´s portal in Argentina, Chile and being launched in other Latam countries.

  This is the first mobile music portal administrated by artificial intelligence in the market.

Page 19: Mooga Sony Music Case study (Update April. 09)

The SONYBMG Contextual Framework has been automatically built with our auto-context scripting engine using SonyBMG´s existing metadata,

enabling a rapid deployment.

Page 20: Mooga Sony Music Case study (Update April. 09)

Mooga allows to mix dynamic and static sections to promote specific content due to marketing needs.

Page 21: Mooga Sony Music Case study (Update April. 09)

In order to find a content, you must know what you are looking for.

Mooga discovers relevant content for each user.

Page 22: Mooga Sony Music Case study (Update April. 09)

Search results provide a 3 tier view to useful and relevant content as the crowd knows best

what everyone wants!

Page 23: Mooga Sony Music Case study (Update April. 09)

Ease of content access coupled with implicit recommendations powered by Artificial Intelligence

Page 24: Mooga Sony Music Case study (Update April. 09)

Statistical Validation

Page 25: Mooga Sony Music Case study (Update April. 09)

  Give each customer WHAT THEY WANT, not what you think they need:

o  Static Top5 made 7,8% of total sales meanwhile the AI Dinamic Storefront and the Recommendation engine administrated 92,2%.

o  67,6% of users who clicked on a recommendation ended making a download.

  CONTEXT IS KING

o  Almost 12% of users made multiple downloads from same artist.

Hey,Idon´tlikefish!

Page 26: Mooga Sony Music Case study (Update April. 09)

  Give customers INFINITE CHOICE and they will make infinite choices

o  54,5% of the content available was download at least once (2.554 pieces of content).

o  83% of artists got at least one download (266 artists).

  Help your customers FIND RELEVANT CONTENT

o  Almost 25% of subscribers used the recommendation engine.

o  27% users made more than one download in a single session.

Page 27: Mooga Sony Music Case study (Update April. 09)

Beyond the tip of the iceberg

Page 28: Mooga Sony Music Case study (Update April. 09)