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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Apicts keynote marshall_sponder_updated - 3-10-12-submitted-final111
- 2. Marshall Sponder – Founder WebMetricsGuru 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. Swimming in Data? Amazing Images of a pool here in Singapore – and right in this resort! Great setting to explore “UltraViolet” Data
- 16. 1. Signal to Noise Ratio 2. Not Scalable, too manual 3. Insightful vs. Actionable 4. Poor Geography / Location 5. Local Data Gap / Blind Spot 6. Platforms often lack needed segmentation capabilities 7. Correspondence between Online chatter vs. Offline Word of Mouth is Industry dependent 8. No established, universally acceptable standards for conducting social listening
- 17. 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 York Where do I Food Network Burberry focus my Lady Gaga H&M Marketing? GUCCI Dolce & Gabbana Sephora CNN Fast Company InStylecom Shopbop Smithsonian Institution
- 18. Local Content Surfaced Local Content Blind Spot 32% 68% Blind Spot 24% 76% Blind Spot 37% 63% Blind Spot 38% 62% Blind Spot 18% 82% Blind Spot August 2011 August 2011
- 19. They mess up here A LOT! If I wasn’t in a rush nor a coffee addict I would go somewhere else!
- 20. 70,000 Real-time Sources 100,000 future events/day 3+ Billion Time-tagged Facts
- 21. 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
- 22. Salesforce + WealthEngine When Salesforce+WealthEngine are combined you get your own lead database with net worth information added http://www.youtube.com/watch?v=EnT1ERSxjSo
- 23. Salesforce + WealthEngine + Radian6 When Salesforce+WealthEngine are combined you get your own lead database with net worth information added
- 27. Prioritise by influence – simple followers count Acquisition targets Time the right platforms saves us
- 28. Source: Persona. 6Dgree.com Get Cicilline followers to follow opponent
- 31. Build connections Use social log as a site default id Use social plug-ins to collect social identities
- 32. These messages that stick Customer commented Liked it, shared it with their friends Stickiness data : Engagement metrics
- 33. This message has 250K readership Going viral
- 34. Social profile of page visited, provide a deeper understanding of the shopping behaviour. Lowest bounce rate and highest economic index Content finds resonance with users with Sporting and TV interest e-com traffic with social profile Illustration only
- 38. Geo-location tracking (must tie customer to Location) Email List Unique ID code Difficult to track – tracked when a could do with subscriber retunes camera, tie it up to receipt (coupon) face recognition but face big brother fallout if Google Analytics you do can accurately Google Analytics record this part via can track this part ecom tracking if if set up correctly set up correctly We need to think deeply on this and decide which Metrics and KPI’s actually are the right ones to track
- 39. Harvest UV Data Harvest UV Data
- 41. Avoid UltraViolet Data by making sure your 1) Plan and 4) Roadmap Align
- 43. • Marshall Sponder • WebMetricsGuru INC. • www.smabook.com • www.webmetricsguru.com now.seo@gmail.com @webmetricsguru @smanalyticsbook
Hinweis der Redaktion
- 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 ]