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Social Photo Brand Clustering Analysis - IIeX North America 2015

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We learned last year how Ditto Labs, the leading visual search company, reads photos on Twitter, Tumblr, and Instagram to discover authentic consumer insights and to find influencers. The math wizards at Ditto are now calculating how product adoption tends to cascade across social networks. For example do liquor brands tend to cluster among people connected online while car brands are less socially influenced? With social photo insights marketers can predict which people are most likely to purchase a product based on what is revealed in their friends' photos! Data scientists call this flocking behavior homophily. Understanding these network effects will forever change how marketers identify influencers and the fastest, most efficient path to purchase.

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Social Photo Brand Clustering Analysis - IIeX North America 2015

  1. 1. Birds of a Feather…. Eat, Drink and Wear the Same Brands a social photo clustering analysis Insights Innovation Exchange Atlanta, GA June 16, 2015 Mary Tarczynski, CMO
  2. 2. • 2 Social photos continue to expand with more than 1.8 billion shared daily Mary Meeker 2014 Internet Trends Report
  3. 3. Photos capture what people are passionate about and many include brands
  4. 4. 4 Yet marketers are currently missing these pictures as 85% of the photos Ditto finds containing a brand do not reference it in text No reference to Bolthouse Farms V8 No reference to Uber No reference to Pampers @MaryTarczynski #iiex
  5. 5. 5 • Proprietary computer vision and machine learning algorithm built by MIT-trained vision scientists • Scours multiple platforms processing millions of photos daily • Finds tiny, obscured, reversed and upside-down logos in cluttered environments Ditto shines light on this “data blindspot” @MaryTarczynski #iiex
  6. 6. Marketers use Ditto for customer insights and engagement Analyze trends and identify affinities. @MaryTarczynski #iiex Unlock insights via the rich context of user-generated photos. Engage with influencers and grow community. Target ads based on brands and categories fans actually use in the wild.
  7. 7. @MaryTarczynski #iiex The Ditto dashboard displays affinity brands - other brands that appear in photos from handles that shared primary brand. What happens when we take a deeper look at brands that appear within the same users’ photo streams?
  8. 8. We employed statistical analyses used in measuring homophily, the tendency of individuals to associate with similar others. @MaryTarczynski #iiex
  9. 9. Coca-Cola was co-shared the most, with an intra-connected circle of brands and many tendrils. Corona, Bud Light, Red Bull, Monster, and Jack Daniels are also highly connected. @MaryTarczynski #iiex
  10. 10. Sharing relationships can be used to group brands into cross category “communities.” Are Harley Davidson, Brooklyn Lager, Sierra Nevada, Santa Cruz and Sodastream “hipster” brands? Why are Porsche and Nissan connected to Red Bull and Chevy and Lincoln with Coca-Cola? @MaryTarczynski #iiex
  11. 11. By limiting the graph to 50+ co-shares the highly connected brands stand out even more. The communities are similar, even though the graph is much sparser, which shows that the structure is persistent. @MaryTarczynski #iiex
  12. 12. As suspected, low cost, frequently consumed beverages are highly connected. @MaryTarczynski #iiex Beverages
  13. 13. Liquors @MaryTarczynski #iiex Well connected liquor brands could be reflective of the holiday time period.
  14. 14. @MaryTarczynski #iiex Beer The connection between Corona and Bud Light is likely a reflection of similar social (often outdoor) occasion positioning while Corona and Heineken are both approachable imports. The paucity of brands in this 50+ view could be indicative of less brand switching in the beer category.
  15. 15. @MaryTarczynski #iiex Cars As suspected, the high cost, infrequently purchased car category brands are not highly connected to each other (but often found in the same stream of user photos with beverage brands due to common sponsorships).
  16. 16. Let’s take a look at closer look at a couple of connected brands
  17. 17. In this data set, pictures shared on Twitter from 66 handles contained both Harley Davidson and Santa Cruz during this two month window. @MaryTarczynski #iiex
  18. 18. Australian pop band 5 Seconds of Summer members Michael Clifford and Calum Hood wear t-shirts sporting Harley Davidson and Santa Cruz Skateboards. Fans like Melissa Garcia are likely to share photos of both. @MaryTarczynski #iiex
  19. 19. We also found high co-sharing between Coca-Cola and Corona in this dataset – 170 instances in this data set. @MaryTarczynski #iiex
  20. 20. One of these co-sharers is Tomas Duarte, a surfer and prolific photo sharer who often features beverages. @MaryTarczynski #iiex
  21. 21. How can marketers use Social Photo Clustering Analysis? @MaryTarczynski #iiex Brand Co-Sharing Network • Co-promotions • Merchandising • Licensing agreements • Line extensions • Sponsorship selection • Media Placement • Ad targeting What are your business hypotheses that photo analytics can help solve? User Friendship Network • Identify memes and visual trends • Segment customers • Monitor brand adoption • Identify influencers • Predict adoption via social networks of products, causes and campaigns (good and bad)
  22. 22. Ditto is now rolling out CNN’s for Scene and Object Recognition @MaryTarczynski #iiex
  23. 23. Other Initiatives on the Ditto RoadMap @MaryTarczynski #iiex • More robust analytics within Ditto platform and expansion of API partnerships like Tracx • Private photo sets - communities and panels (medicine cabinet, pantry, fridge, broom closet, etc) • Expansion to international networks like Weibo • Video processing
  24. 24. Mary Tarczynski Chief Marketing Officer Mary@ditto.us.com ditto.us.com James Williams PhD Candidate, Applied Mathematics Yale Institute for Network Science james.s.williams@yale.edu QUESTIONS?

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