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Cloudof Knowing

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How content analytics can be brought into research. The presentation was given as a webinar for the IE Business school where John Griffiths is a visiting professor.It features examples of the use of Purefold transmedia as a research methodology and the use of demographic replicator research bots. Part of the Cloud of Knowing project

Publicado en: Empresariales

Cloudof Knowing

  1. 1. The Cloud of Knowing content analytics and the future of market research John Griffiths Planning Above and Beyond Jan 20 th
  2. 2. Ground I am going to cover <ul><li>Work in progress from Cloud of Knowing project </li></ul><ul><li>Paper for the Market Research Society conference </li></ul><ul><li>Online content – how it can be part of MR </li></ul><ul><li>MR stuck using offline research paradigms </li></ul><ul><li>Will introduce 2 new approaches </li></ul><ul><li>A way to bring content into research </li></ul>
  3. 3. The questions we need answers to <ul><li>Is sampling central to research or does research have to change? </li></ul><ul><li>If we don’t ask questions is it still research? </li></ul><ul><li>Do we need permission to use people’s content? </li></ul><ul><li>Do we need to protect anonymity? </li></ul><ul><li>How can research use internet content for business decision support? </li></ul><ul><li>Is there such a thing as real time research? </li></ul>
  4. 4. Redrawing the lines around research Will research advance to include content? Or will research retreat and become a specialism? the guys who do Interviews..
  5. 5. Research cultures <ul><li>Farmer/cultivators </li></ul><ul><li>Hunter gatherers </li></ul><ul><li>Scavengers </li></ul>
  6. 6. Blog site
  7. 7. Scavenging on the web <ul><li>But it is only one blogger even with comments from others </li></ul><ul><li>Who is the blogger? Where are they based? </li></ul><ul><li>Are they representative? All internet posters are atypical </li></ul><ul><li>That person may be misrepresenting themselves – corporate blogging/PR </li></ul>
  8. 8. Current resources to analyse online content <ul><li>Social media measurement experiments - eg #measurementcamp </li></ul><ul><li>Netnography – online behaviour and content coming from this </li></ul><ul><li>E-Anthropology –social analysis using web artefacts </li></ul><ul><li>Bricolage – support to qualitative research </li></ul><ul><li>Research practice says </li></ul><ul><ul><li>research data needs to come from a valid sample representative of the population </li></ul></ul><ul><ul><li>If projective materials are used then research participants need to explain it </li></ul></ul>
  9. 9. So can online research help? Online survey panels Online focus groups Face to face/CATI surveys Offline discussion/ Focus groups Research Communities { } { } Open platforms Eg FB group
  10. 10. Business decision support using more and more data sources <ul><li>Business process </li></ul><ul><li>Web analytics </li></ul><ul><li>Customer satisfaction </li></ul><ul><li>Corporate reputation tracking </li></ul><ul><li>Transaction data </li></ul><ul><li>Customer research? </li></ul>A lot of these aren’t being managed by the marketing department
  11. 11. Research at the crossroads
  12. 12. Purefold: open source co-created transmedia film director story ‘ seeds’ RSS feeds gather raw content Friendfeed hopper Visitors /linkers grade and link to other Web content storylines amplified Brand owners sponsor & create characters storylines Output put into production Ridley Scott Assoc/Ag 8
  13. 13. Purefold model applied to research
  14. 14. Benefits of the Purefold model <ul><li>Continues to use real people as participants </li></ul><ul><li>Dual role of research participants as graders and taggers </li></ul><ul><li>Sampling of participants can be controlled </li></ul><ul><li>Content can be filtered and amplified </li></ul>
  15. 15. Demographic replicators: Research bots ‘ Wefeelfine’ emotional wrapper DGR Felix text bot twitter posterous friendfeed network Analysis of others who share bot tastes Comments/ retweets of those who dialogue with the bot Findings aggregated with other bots
  16. 16. Meet felix <ul><li>Emotional wrapper: wefeelfine.org:8080/ ShowFeelings?feeling&limit=50 gender=M city=london agerange=20 </li></ul><ul><li>emotion_keywords: { sad: [divorce, desk], great: [Floyd, Doors], depressed: [sales, weight, divorce, client], lonely: [at home, the divorce, miss my kids, desk], tired: [work, boss, home, hangover, sales] </li></ul><ul><li># Times of day time_keywords: 04: [work, sales, weight, conference, procurement, desk] </li></ul><ul><li>weekend_time_keywords: { 10: [home, kids], </li></ul><ul><li># Words to fall back on if nothing else matches, or to add randomly character_keywords: [work, boss, divorce, fat] </li></ul>
  17. 17. What is Felix? A projective device for researchers to reframe research questions? A dynamic sample/panel which can be observed and with which the researcher can interact A lure/decoy for drawing out customer response
  18. 18. Benefits of Replicators <ul><li>Continues to use real people as participants </li></ul><ul><li>You don’t need to recruit research participants unless you want to </li></ul><ul><li>Sampling of participants can be controlled </li></ul><ul><li>Content is filtered and amplified </li></ul><ul><li>Content can be used to stimulate online response </li></ul><ul><li>Content can be used to inspire the researcher as analyst </li></ul>
  19. 19. Past the sample/content bottleneck Sample Content Quant & Qual research keep sample and content questions separate Inability to control sample is what makes web content analysis problematic Sampling is literal: 20 male, works in local govt, lives in London
  20. 20. Computing has a similar bottleneck Instructions/data Memory/CPU
  21. 21. Knitting machines.. two different media programme cards wool
  22. 22. Into the cloud.. <ul><li>Sampling </li></ul><ul><li>Permission </li></ul><ul><li>Anonymity </li></ul>
  23. 23. Sampling <ul><li>Probabilistic scoring has been standard in lifestyle database marketing and geo-demographic marketing for 20 years </li></ul><ul><li>Use sample and content tags to mark up data. Could use cookies as a type of sample tag. </li></ul><ul><li>Use scoring models to decide whether to include content within sample. </li></ul><ul><li>Use best fit algorithms to aggregate content and sample tags. </li></ul><ul><li>Identify content first and then use sample tags to eliminate all the content which is off sample. </li></ul>this starts to make available to us the riches of the web in realtime search engines and Google/Yahoo alerts
  24. 24. Permission <ul><li>If we source content probabilistically then permission is no longer an issue </li></ul><ul><li>We can use their content without ever disturbing them. </li></ul><ul><li>Is this permissible within research or not? </li></ul><ul><li>The volume of online content that could become the subject of research is potentially so great that data protection becomes meaningless – permission becomes unnecessary </li></ul>
  25. 25. Anonymity <ul><li>MR principle protects research respondents from being sold to </li></ul><ul><li>Anonymity can only be granted in the context of a customer interview. There is always a possibility with behavioural targeting that that the digital marketer knows something about you that you don’t. </li></ul><ul><li>Probabilistic systems already being used for behavioural targeting and direct marketing would identify them anyway but there would not be greater disadvantage than anyone else who is the subject of behavioural targeting. </li></ul>
  26. 26. To summarise <ul><li>To bring content within research – need new methods </li></ul><ul><li>Purefold co-creation using taggers and graders </li></ul><ul><li>Use of DGR research bots </li></ul><ul><li>Probabilistic sampling </li></ul><ul><li>Challenge the use of permission and the protection of anonymity </li></ul>
  27. 27. Vested interest in MR preventing the incorporation of online content Qual: Research by hand Quant: Self measurement
  28. 28. CRM the natural starting point <ul><li>The need to engagement means that CRM is no longer focussed on hard sell </li></ul><ul><li>Multiple contact points with customers – very few falling within conventional research practice </li></ul><ul><li>The natural starting point for analysing web content. </li></ul><ul><li>Research needs to be part of it </li></ul>
  29. 29. Final thought? Customers are tribal stakeholders an extension of the company <ul><li>Perhaps customers willing to be involved in regular dialogue as part of CRM programmes </li></ul><ul><li>Customers as valued stakeholders </li></ul><ul><li>Extended members of the company ‘tribe’ </li></ul><ul><li>Is it possible that research industry is perpetuating the divide: </li></ul><ul><ul><li>Research respondents as outsiders? </li></ul></ul><ul><ul><li>Researchers as essential intermediaries? </li></ul></ul>
  30. 30. Thank you .. Questions??
  31. 31. Some references you may find useful.. <ul><li>http://www.webjam.com/cloud_of_knowing </li></ul><ul><li>http://www.research-live.com/events/annual-conference/research-2010-the-annual-conference/4000799.article </li></ul><ul><li>http://www.ag8.com/ purefold </li></ul><ul><li>http://felixfreeman.posterous.com/ </li></ul><ul><li>http://twitter.com/felix_freeman </li></ul><ul><li>[email_address] </li></ul><ul><li>johngriffiths7 twitter </li></ul>

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