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Staying on the Right Side of the Fence when Analyzing Human Data
- 1. Staying on the Right Side of the Fence when Analyzing Human Data
- 2. Susan Etlinger Industry Analyst ALTIMETER GROUP Tim Barker CEO DATASIFT
- 3. Data Ubiquity and the Trust Imperative What we’ll cover today 1 2 3 4 5 Principles of Ethical Data Use How Social Networks are changing to privacy-first approaches Audience vs Individual Insights Discussion / Q&A
- 4. 4 Susan Etlinger Industry Analyst, Altimeter Group, A Prophet Company @setlinger The Trust Imperative A Framework for Ethical Data Use
- 5. 5 An Origin Story (2012)
- 6. 6 A Tipping Point (2013) “Paging through the catalog, we realized to our dismay that whoever had sent us this thing knew us. They’d nailed our demographic precisely. They even knew what kind of convertible car seat we’d want! Who were these people, or should I say, machines?!?” − Alexis Madrigal
- 7. 7 “ “Legislation can’t keep up with technology, which makes it a flawed vehicle to govern what happens in this space.” − Judy Selby, Partner, Information Governance BakerHostetler
- 8. 8 1. Data Collection Has Become More Ambient—and Intimate 2. Consumers Don’t Control Their Personal Information 3. Consumers Report Distrust of Data Use 4. Trust is a Major Concern for CEOs 5. Distrust Has Quantifiable Impact on Business Performance Trust is a brand issue
- 9. 9 Consumers do not trust data use
- 10. 10 They feel “resigned” “Most Americans disclose their personal data to companies for discounts because they believe that marketers will harvest the data anyway.” Joseph Turow, Ph.D., Michael Hennessy, Ph.D., Nora Draper, Ph.D., “The Tradeoff Fallacy: How Marketers are Misrepresenting American Consumers and Opening them Up to Exploitation,” University of Pennsylvania Annenberg School of Journalism, June 1, 2015.
- 11. 11 Lack of trust has clear consequences
- 12. 12 “ “Just complying with the law is not going to be nearly enough to make consumers comfortable.” − Jennifer Glasgow, Chief Privacy Officer, Acxiom
- 13. 13 Principles of Ethical Data Use* * Developed by the Information Accountability Foundation (IAF) Beneficial • Does our use of data benefit consumers as much as it benefits us? Progressive • Do we have a culture of continuous improvement and data minimization? Sustainable • Are the insights we identify with data sustainable over time? Respectful • Have we been clear, transparent and inclusive? Fair • Have we thought through the potential impacts of our data use on all interested parties?
- 14. 14 “Before conducting any type of new analysis, we ask ourselves whether it will bring benefit to customers in addition to the company. If it doesn’t, we won’t do it.” Joshua Kanter, Senior Vice President, Revenue Acceleration, Caesars Entertainment Benefit in Action
- 15. 15 “Organizations should not create the risks associated with big data analytics if there are other processes that will accomplish the same objectives with fewer risks.” − Information Accountability Foundation Progressiveness in Action
- 16. 16 Senate Bill 576, “GPS Data Privacy for Mobile Devices,” (California) “[R]equires that consumers get a clear notice explaining how their location information will be used and shared when they install a new app.” It also ensures that app users give express consent before their geolocation data can be collected and shared.” Legislating Progressiveness
- 20. 20 A Framework for Ethical Data Use
- 21. 21 The Sunshine Test What would happen if all the details of what you are doing were out in the open, in the light of day? Photo: Madalena Pestana, CC 2.0
- 22. 22 “ “By knowing where the borders are, you can innovate more around them.” − Stefaan Verhulst Co-Founder and Chief Research and Development Officer The Governance Lab (NYU)
- 23. How Social Networks are adopting privacy-first approaches Tim Barker CEO DATASIFT.COM #DSWebinar
- 24. April ’15 Topic data provides anonymized and aggregate insights into content and audiences on Facebook. Nov ’15 Instagram introduces platform policy change to restrict data access to approved applications. Trust is the currency of social networks. May ’15 Linkedin limits API access to select, approved partners. API Changes in last 12 months to protect consumer data from misuse. #DSWebinar
- 25. 25 It’s messy Separate Signal from Noise It’s text-based Unlock meaning from text Challenges in Extracting Insights It contains personal data Extracting insights while protecting consumer privacy Insights drive marketing investments in Social Networks. But it’s a Big Data challenge. Insights drive more marketing spend on social networks. Insights drive marketing spend on Networks #DSWebinar
- 26. 26 Enables an ecosystem of product-builders. See datasift.com/partners for complete list. Application Builders Agencies We help networks build an insights-driven ecosystem Filter Signal:Noise Understand Meaning Explore Insights DataSift partners with Social Networks to help them build an insights-driven ecosystem Insights drive marketing spend on Networks Transform raw feeds of activity data into insights into content, engagement and audiences. DataSift technology builds insights, protects identity DataSift helps Social Networks build an insights-driven ecosystem Helps developers build compliant, compelling insights. #DSWebinar
- 27. 27 DataSift platform connects to the real-time feed of Posts, Comments, Likes. Facebook Topic Data: Privacy-First Approach to Insights Surface Insights from activity across Facebook Built from posts, comments, likes Aggregate and anonymized results #DSWebinar
- 28. 28 Anonymized and Aggregate approach.Analysis that spans all of the available data. Multi-Dimensional data analysis Net-Positive for Consumers + Businesses “Bigger Data” for Bigger Insights Why a Privacy-First Approach Wins “Better Data” for Audience Insights #DSWebinar
- 29. “Bigger Data” for Bigger Insights Comparison of volumes of engagement relating to an automotive brand across 7-day period. FACEBOOK PAGES ~1,000 Posts and Engagement on your own Facebook Pages TOPIC DATA ~70,000 Brand-related Posts and Engagement across all of Facebook #DSWebinar
- 30. “Better Data” for Consumer Insights Create Insights from Multi-Dimensional. 30 Gender: Male Age Range: 35-44 Region: California, USA CONTEN T Negative Positive DEMOGRAPHICS SENTIMENT Automatic classification of related topics e.g. Star Wars VII (Film) TOPIC ANALYSIS CONTEN T LINKS Analyze URLs shared across Facebook Engagement and Demographics around Likes, Comments and Shares ENGAGEMENT Can’t wait to take the kids to watch Star Wars VII CONTEN T Privacy-safe aggregate analysis of text TEXT ANALYSIS #DSWebinar
- 31. Advertising Agency for a Drink Brand 31 Advertising Agency wanted to understand… How women engaged with their client’s beverage brand and with hot drinks. Deeper understand of the media consumption / magazine stories which most engaged their target consumers #DSWebinar
- 32. Identify the publications, stories & celebrities which drove most engagement amongst the target audience segment Recommended Actions ๏ Look at featuring different drinks when advertising in different markets and to different demographic groups ๏ Use story insight for media placement as well as for identifying potential influencers 1st 2nd 3rd LATTE HOT CHOCOLATE ESPRESSO HOT CHOCOLATE LATTE CAPPUCINO CAPPUCINO LATTE ESPRESSO USA UK GERMANY Under 35s, as a % of brand’s total engagement 47% Client Brand Competitor A Competitor B 31% 58% Celebrity stories driving most engagement There are big variations in preferences for hot drinks across nations and demographic groups The brand found that they suffered with the lowest relative engagement amongst millennials Insights into Content and Audiences JENNIFER LAWRENCE SHARON STONE TAYLOR SWIFT KYLIE JENNER JUSTIN TIMBERLAKE #DSWebinar
- 33. 33 + WinLose Zero-Sum Game Positive-Sum Game WinWin + - Data is anonymized to protect identity. - Deeper audience-level insights possible by using demographics / interest-graph data added by social networks. - Insights built on a foundation of data privacy and trust. - To evolve from audience-level analysis to individuals, use a social- network opt-in to allow customers to control data they want to share. Privacy does not have to be a zero-sum game - For business to win, consumers have to lose. #DSWebinar
- 34. Q&A
- 35. THANK YOU http://bit.ly/ds-reasons Resources BALANCING INSIGHT AND TRUST Altimeter White Paper http://bit.ly/insightvstrust 10 REASONS FACEBOOK TOPIC DATA WILL CHANGE YOUR WORLD DataSift eBook
Editor's Notes
- Media, legal and privacy