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Tim Macer Managing Partner Tim Macer Services Hampshire, United Kingdom

Where is market research technology leading us? It’s time to put the necessity back into invention. Tim Macer Managing Partner Tim Macer Services Hampshire, United Kingdom. AGENDA State of the market in 2002 Where technology could/should be taking us

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Tim Macer Managing Partner Tim Macer Services Hampshire, United Kingdom

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  1. Where is market research technology leading us?It’s time to put the necessity back into invention Tim MacerManaging PartnerTim Macer ServicesHampshire, United Kingdom

  2. AGENDA • State of the market in 2002 • Where technology could/should be taking us • Impact of the Internet, after ‘boom and bust’ • Standardization • The challenges of technology for all

  3. 1. The state of the market in 2002 How to back a winner in a 230 horse race

  4. What is the state of the art? • Relational databases • Open interfaces • Web enablement • Process automation • Ease of use

  5. What’s hot • ASP-delivered CATI • Sample and panel management systems • Portals and portal development tools • Open interfaces making customization easier • New visual interviewing tools • Multi-mode interviewing • Integration with enterprise databases and data warehouses

  6. The state of the market in 2002 • MR software now a $241 million industry, worldwide1 • Software companies employ >1600 people1 • Thousands more employed in agencies and research buyers • Over 100 specialist software manufacturers2 • Over 230 commercial MR software products2 • 82 web interviewing products • 50 CATI products 1Source: Research Software Guide, Jan 2002 2Source: Research Software Central

  7. The problems of over-supply • Years of under-investment showing • Endurance of the ‘old way of doing things’ • Programming scripts • New suppliers offering functionality the old ones don’t • New suppliers not offering everything the old ones do • Developers can’t do everything

  8. The way forward • Consolidation through acquisition and merger • Difficult to see how • Specialization: the niche within a niche • Already starting to happen • Co-operation through open standards • Allow customers to pick the ‘best of breed’ solution • Integration across vendors

  9. 2. Where technology could (or should) be taking us It’s time to solve the difficult problems

  10. To work faster Less time on repetitive tasks To work better improved accuracy; fewer errors To give more to the client Richer insights, more connected To give more to the respondent More rewarding experience To do all this for less money and still make a profit The challenges The right technology can help us reach these goals!

  11. Multimodal data collection • Serial • Phone/mail/phone • Telephone recruit/web interview • Parallel • Respondent chooses: phone, web, mail in • Respondent can switch • The challenges • Eliminating any reprogramming or reformatting • Overcoming modal differences

  12. Multimode: who’s doing what • Eliminating modal bias—web, CAPI and kiosk • Opinion One CAVI • Web-based CATI/CAPI/CASI • GMI, NEBU, Pulse Train • Modal templates • Askia • Interviewer assisted web interviewing • Surveyguardian • Multi-mode interview players • SPSS MR Dimensions (in development)

  13. Candidates for automation • Regular reporting • Managing change on continuous projects • Developing question libraries • Testing and error detection in scripts • Coding, editing and cleaning data • Questionnaire scanning • Eliminating paper records and storage

  14. Automation: who’s doing what • Report automation Confirmit • Good change management NEBU • Question libraries various but weak • Computer-assisted coding Ascribe • Process automation SPSS MR Script

  15. Going Paperless: who’s doing what • Paperless report distribution and archiving • E-tabs • Report library and research admin for clients • Research Reporter • Paperless interviewing • Techneos Entryware, J-TECH Electronic Comment Card, M-CAPI Express • Questionnaire Scanning • Bellview Scan, Eyes & Hands/mrPaper

  16. Mixed visual/syntax questionnaire authoring • Who does the survey authoring? • PD, technician, programmer? • We need editors that work like HTML page design tools such as Frontpage or Dreamweaver • Syntax preferred by expert users • Visual better for non-technical users • Syntax more efficient for repetitive functions • Visual more efficient for look and feel

  17. Better authoring: who’s doing what • The ‘Dreamweaver’ of survey authoring • Pulse Train’s Visual QSL • Cross-platform authoring tool • NIPO and CfMC visual survey editor • Easy importation of Word documents • Askia • Reading others’ questionnaire scripts • GMI

  18. Visual QSL Pulse Train

  19. Combining data from multiple sources • Mixing research data with hard data: some techniques • Match by actual customer • Cluster analysis and segmentation • Time overlay • Creating and using norms for comparison • Specialist market analysts are taking the lead

  20. Integrating with CRM processes • Adding the ‘why’ into knowing ‘what’ • Example: Egg, Internet bank in the UK • Customer panels • Event driven research • Ad hoc • Extranet for project definition and approval • Real-time reporting • Ethics: setting clear boundaries between marketing, MR and CSS activities

  21. Who’s doing what: multi-source & CRM • Visual tools to merge survey and warehouse data for analysis • SPSS Clementine • Ability to read directly from a data warehouse • SPSS MR Data Model, Pulse Train’s Pulsar • Sampling from CRM systems + adding data back into the enterprise database • Centurion’s MaRSC

  22. Clementine SPSS

  23. In the future… expert systems? • research design • survey authoring • translation • sampling • data cleaning • coding • automated analytics and data mining

  24. 3. The real impact of the Internet, after the ‘boom and bust’ Sure, if you can prove it’s faster, cheaper and better

  25. Client Outworkers Agency Supplier Agency After the froth • Continued growth for data collection in US • Slower elsewhere • The web as the means to deliver computing • More focus on delivery: growth of the ‘portal’ • Greater collaboration Client Outworkers Supplier Agency

  26. Portals • Client portals provide real-time access to their research data, current and past projects • Many large research agencies are providing web access for their clients • Realtime, online or published reports? • Project ordering and briefing • Survey testing and approval • Respondent portals allow panelists to manage their own profiles, surveys and create ‘online communities’

  27. Who’s doing what: Portals • Portal building tools for client and respondent interfaces • GMI • Web-based analytics • Confirmit, GMI, Pulse Train, SPSS MR • Respondent portals • NEBU

  28. Net-MR Portal Management Global Market Insite

  29. Working visually • Most web surveys still text based • Next generation will be more visual and more multi-media, sound, animation etc • Not just a gimmick • Aim to improve the interview experience • Faster to complete • Closer to reality

  30. Who’s doing what: Going visual • Visual interviewing for CASI, web and CAPI • OpinionOne CAVI • Web-based quali/quant image-based evaluation and tradeoff • GMI in association with 2ndSight • Web-based and ASP-delivered conjoint • IdeaMap.Net

  31. CAVI OpinionOne

  32. 4. Standardization Enabling us to go for ‘best of breed’

  33. Proprietary imports and exports are not good enough • Too many competing packages; you may be in a universe of one using your combination • Proprietary data formats can change without notice • Too much effort wasted converting from one format to another • Data are useless without the definitions and texts - the metadata

  34. XML is not a standard language • According to W3C, “The Extensible Markup Language (XML) is the universal format for structured documents and data on the Web” • Close relative of HTML: both originated from SGML • Lets you create your own definition languages • Increasingly used within MR software for data definition and execution logic • Everyone’s XML is different • Easier to translate but not mutually intelligible

  35. Initiatives from around the world Triple-swww.triple-s.org • First published 1994 • Originated in the UK but now implemented by 30 vendors worldwide • Exchange data and metadata via exports and imports in a generalized format • Version 1.1 introduced XML support • New version 1.2 adds filters, weighting and multi-language support

  36. <VARIABLE ID="4"> <NAME>Q4</NAME> <LABEL>Which sights have you visited?</LABEL> <TYPE>MULTIPLE</TYPE> <POSITION>41 TO 42</POSITION> <SPREAD>2</SPREAD> <VALUES> <VALUE CODE="1">Statue of Liberty</VALUE> <VALUE CODE="2">Empire State Building</VALUE <VALUE CODE="3">Times Square</VALUE> <VALUE CODE="4">Central Park</VALUE> <VALUE CODE="5">Rockefeller Center</VALUE> <VALUE CODE="9">Other</VALUE> </VALUES> </VARIABLE> Example triple-s code

  37. Initiatives from around the world Open Surveywww.opensurvey.org • Not-for-profit organization that promotes open standards for software • Encourages production of open source software for market research • AskML is its proposed XML standard for exchanging survey instruments • TabSML is its working standard for exchange of cross-tabular reports in a generalized format • Also endorses triple-S

  38. Initiatives from around the world Object Management Group www.omg.org • Looks after the Common Warehouse Metamodel • Pan-industry initiative to provide an agreed framework for defining the storage and handling of large amounts of data in data warehouses • Has an Analytic Data Management SIG with links to triple-S and Open Survey

  39. Initiatives from around the world Data Documentation Initiative www.icpsr.umich.edu/DDI • Based at the University of Michigan • Developing XML-based tools and open standards • Aims to create machine readable archives of textual descriptions and metadata for past surveys, independently of the original proprietary data formats used • Will overcome future problem of surveys defined in defunct languages

  40. Initiatives from around the world SPSS MR Dimensions Data Model www.spssmr.com • A new open (though proprietary) metadata model for survey data • Can be licensed independently of all SPSS MR products (don’t have to use SPSS software) • Comes with a developers’ library of tools for building applications that will read or write data via the Data Model

  41. 5. The challenges of ‘Technology for all’ Are you licensed to drive that system?

  42. Technology for all • Researchers and clients want more control and more freedom to access surveys, data and management tools for themselves • Is this the freedom to make mistakes • Bigger, faster, more expensively…? • Are we putting dangerous weapons in the hands of the innocent ? • Is it the best use of the researcher’s time?

  43. The wider issues • End of the road for the specwriter and survey programmer? • New technology often means new ways of doing things: new processes and new procedures • Roles and responsibilities will shift • Who gets the blame if the logic or the weighting is wrong? • The need for the internal technology consultant and advocate

  44. “Every time I have seen it go wrong it is because senior management did not understand the technology. Expecting the systems or DP department to come up with the answers is very likely to give you a systems led solution rather than a research led solution.” John O’Brien, Chairman, BMRB International, on implementing new technology, interviewed in Research World, March 2001 (Esomar)

  45. Take a multi-disciplinary approach • New technology won’t work if it is simply molded around existing working models • Set up an implementation strategy team, involving all the operational units • Make sure everyone learns the new technology • Support for the new technology must come from the top • get someone as senior as possible with their hands on the technology

  46. The software gets simplerThe system gets more complex • The standard ‘turnkey package’ is on its way out • Multi-vendor solutions and going for ‘best of breed’ can mean integration issues • Open interfaces are making it easier to customize software • Customization is increasingly desirable

  47. Changing skills • Less programming in proprietary languages like Quancept and Survent • Expertise needed in Java, HTML, XML, SQL, Visual basic and so on • Research people need to know more about technology • Technology people need to know more about research

  48. Wising up - short term • Make training specific to your application of the software • about how it will be used, not about what it can do • use real examples • Aim for understanding so that people can rapidly learn to solve their own problems • Offer as many ways of learning as possible: courses, self-study, lunchtime seminars, web-based or distance learning

  49. Wising up - long term • Professional training in research must include something on technology • Where are the professional training and qualifications for the research technologist? • Proposed MRS Advanced Certificate in Research Practice and Technology • Modular courses to provide ongoing or continuous professional development for the research IT professional • Need to involve vendors as well as research agencies and buyers

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