Apicts keynote marshall_sponder_updated - 3-10-12-submitted-final111


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Keynote: Mining for Ultraviolet Data and a New Approach to Social Media
What is Ultraviolet data (information which we either failed to collect, or which we have collected, but is not useful for analysis and insights) and how to work with it. The analogy of "ultraviolet" to cover platform capabilities (the unused features of software that most of us don't use, but which may be more valuable than the parts we do use).
Social Analytics - how we can improve the way Analysts and Stakeholders use platforms, and the data they get as a result, but adding a different approach to how Analytics is conducted, and who runs it.
The role of Analytics – the importance of a Chief Analytics Officer and the need for one in every agency, to better inform agency heads, stakeholders and clients of the best selection of vendors and the best use of the data, as crucial.
Marshall Sponder, Founder of WebMetrics Guru INC. and Author of Social Media Analytics: Effective Tools for Building, Interpreting, and Using Metrics, US

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  • Open for a shot of Singapore after you arrive
  • Lets talk about Ultraviolet Data – What is it? - Ask Audience – what they think it means? Questions? - What it is to you – Way back when, Dan Bricklen’s Demo II software – you only used part of it’s capabilities, the rest were Ultraviolet. People also have UV properties as does Data (we don’t collect and know how to use most of it).. It’s like it’s invisible to us, but not really, it’s more like “ultraviolet light”, bees and wasps can see it, but humans can’t (unless they have special devices to help them detect it).
  • Have agencies providing you about the latest market perceptions, campaign information around your brand, your competitors and your industry (some of it useful, others, not so much).
  • So much public domain data is available, but not collected -
  • High on your list should be matching social data with internal data customer data
  • These should be your primary acquisition targetsWhat should you do (action) when you find customer following both or Like both your brand and competitors ....
  • Outcome for marketer = tailored product, tiered customer management and a lift in spend
  • After we have done all these stuff, are they buying more from usthe UV data you needed is social profile of the buying action taken you want to know - who is 'buying' from us Buying data here is the purchase process visited/revisited down load brochure asked for a quote entered a competition sign up a trail A lot of these information is already in e-com system, in your google analyticsThe piece that is missing is the link between traffic and social profileThere are a number of projects/products heading down this track[Screen shot of ??...AW need to check with client first ][Outcome for marketer = tailored products, increase conversion ]
  • Apicts keynote marshall_sponder_updated - 3-10-12-submitted-final111

    1. 1. Ultra violet data
    2. 2. Marshall Sponder – FounderWebMetricsGuru INC. Marshall Sponder is an Author of the McGraw-Hill book, Social Media Analytics, he is independent Web analytics, data and SEO/SEM specialist working in the field of market research, social media, networking, and Outbound Communications. Marshall is currently working with Principal at WebMetricsGuru INC and Insights Digital, INC , both partnerships focus on the practice around Social Analytics. Marshall’s blog is http://www.webmetricsguru.com and book site is http://www.smabook.com
    3. 3. Swimming in Data?Amazing Images of a pool here in Singapore – and right in thisresort! Great setting to explore “UltraViolet” Data
    4. 4. 1. Signal to Noise Ratio2. Not Scalable, too manual3. Insightful vs. Actionable4. Poor Geography / Location5. Local Data Gap / Blind Spot6. Platforms often lack needed segmentation capabilities7. Correspondence between Online chatter vs. Offline Word of Mouth is Industry dependent8. No established, universally acceptable standards for conducting social listening
    5. 5. Burburry Brand Affinity Strength Who What Wear MoMA The Museum of Modern Art Nordstrom Fashionista BCBGMAXAZRIA Marie Claire DVF - Diane von Furstenberg The Metropolitan Museum of Art- New YorkWhere do I Food Network Burberryfocus my Lady Gaga H&MMarketing? GUCCI Dolce & Gabbana Sephora CNN Fast Company InStylecom Shopbop Smithsonian Institution
    6. 6. Local Content Surfaced Local Content Blind Spot 32% 68% Blind Spot 24% 76% Blind Spot 37% 63% Blind Spot 38% 62% Blind Spot18% 82% Blind Spot August 2011 August 2011
    7. 7. They mess up here A LOT! If I wasn’t in a rushnor a coffee addict I would go somewhere else!
    8. 8. 70,000 Real-time Sources 100,000 future events/day 3+ Billion Time-tagged Facts
    9. 9. Mobile and Tablets - Next three years Huge market segments still emerging• Over 75% of businesses plan on deploying tablets by 2013• Revolutionizing health care delivery, on-site and mobile• Disrupting software engineering and user expectations
    10. 10. Salesforce + WealthEngine When Salesforce+WealthEngine are combined you get your own lead database with net worth information addedhttp://www.youtube.com/watch?v=EnT1ERSxjSo
    11. 11. Salesforce + WealthEngine + Radian6 When Salesforce+WealthEngine are combined you get your own lead database with net worth information added
    12. 12. Prioritise by influence – simple followers countAcquisition targetsTime the right platformssaves us
    13. 13. Source: Persona. 6Dgree.com Get Cicilline followers to follow opponent
    14. 14. Build connections Use social log as a site default id Use social plug-ins to collect social identities
    15. 15. These messages that stick Customer commented Liked it, shared it with their friendsStickiness data : Engagement metrics
    16. 16. This message has 250K readershipGoing viral
    17. 17. Social profile of page visited, provide a deeper understanding of the shopping behaviour.Lowest bounce rate andhighest economic indexContent finds resonancewith users withSporting and TV interest e-com traffic with social profile Illustration only
    18. 18. Geo-location tracking (must tie customer to Location) Email List Unique ID codeDifficult to track – tracked when acould do with subscriber retunescamera, tie it up to receipt (coupon)face recognitionbut face bigbrother fallout if Google Analyticsyou do can accuratelyGoogle Analytics record this part viacan track this part ecom tracking ifif set up correctly set up correctlyWe need to thinkdeeply on this anddecide whichMetrics and KPI’sactually are theright ones to track
    19. 19. Harvest UV Data Harvest UV Data
    20. 20. Avoid UltraViolet Data by making sureyour 1) Plan and 4) Roadmap Align
    21. 21. Illustration only
    22. 22. • Marshall Sponder• WebMetricsGuru INC.• www.smabook.com• www.webmetricsguru.comnow.seo@gmail.com@webmetricsguru@smanalyticsbook