--- title: The Transformation of Marketing Research description: The Transformation of Marketing Research --- - - - - [mailto:info@gmi-mr.com](mailto:info@gmi-mr.com) [![Kantar-Logo-Small-Use-Black](https://info-profiles.kantar.com/hs-fs/hubfs/logos/Kantar-Logo-Small-Use-Black.png?width=119&name=Kantar-Logo-Small-Use-Black.png)](http://www.lightspeedresearch.com) - [Home](http://www.lightspeedresearch.com/) - [Sample Audiences](http://www.lightspeedresearch.com/sample-audiences/) - [Quality Suite](http://www.lightspeedresearch.com/sample-audiences/quality-suite/) - [Panel Profiling](http://www.lightspeedresearch.com/sample-audiences/panel-profiling/) - [B2B Panels](http://www.lightspeedresearch.com/sample-audiences/business-to-business-panels/) - [Custom Panels](http://www.lightspeedresearch.com/sample-audiences/custom-panels/) - [Millennial Panel](http://www.lightspeedresearch.com/sample-audiences/vice-voices/) - [Research Solutions](http://www.lightspeedresearch.com/research-solutions/) - [Quick Turn Surveys](http://www.lightspeedresearch.com/research-solutions/lightspeed-quick-turn-surveys/) - [Survey Design](http://www.lightspeedresearch.com/research-solutions/survey-design/) - [Tracking Research Design](http://www.lightspeedresearch.com/research-solutions/tracking-research-design/) - [Integrated Technology Solutions](http://www.lightspeedresearch.com/research-solutions/integrated-technology-solutions/) - [Data Processing](http://www.lightspeedresearch.com/research-solutions/data-processing/) - [Ad Tracker](http://www.lightspeedresearch.com/research-solutions/ad-tracker/) - [Survey Programming](http://www.lightspeedresearch.com/research-solutions/ad-tracker/) - [Sample Only Services](http://www.lightspeedresearch.com/research-solutions/sample-only-services/) - [Data Services](http://www.lightspeedresearch.com/data-services) - [Data Appends](http://www.lightspeedresearch.com/data-services/data-appends/) - [Mobile](http://www.lightspeedresearch.com/mobile/) - [Mobile Solutions](http://http://www.lightspeedresearch.com/mobile/) - [Resource Center](http://www.lightspeedresearch.com/resource-center/) - [Events](http://www.lightspeedresearch.com/resource-center/events/) - [Demos](http://www.lightspeedresearch.com/resource-center/demos/) - [Case Studies](http://www.lightspeedresearch.com/resource-center/case-studies/) - [Blog](https://blog.lightspeedresearch.com/) - [General Inquiries](http://www.lightspeedresearch.com/contact-us/general-inquiries/) - [About Us](http://www.lightspeedresearch.com/about-us/) - [Leadership Team](http://www.lightspeedresearch.com/about-us/leadership-team/) - [Press Releases](http://www.lightspeedresearch.com/about-us/news-press-releases/) - [Why Lightspeed](http://www.lightspeedresearch.com/about-us/why-lightspeed/) - [Careers](http://www.lightspeedresearch.com/about-us/careers/) - [Regions](http://www.lightspeedresearch.com/about-us/regions/) - [Awards](http://www.lightspeedresearch.com/awards/) - [Contact Us](http://www.lightspeedresearch.com/contact-us/) # Kantar's Profiles Blog # The Transformation of Marketing Research Posted by [Frank Kelly](https://info-profiles.kantar.com/author/frank-kelly) on Oct 1, 2014 ![](https://info-profiles.kantar.com/hubfs/20170504-Lightspeed-Exec-Portraits-003-RET-flat-final.jpg) - [Tweet](https://twitter.com/share) A dozen years ago, while working for Nielsen, I had the good fortune to work on the development of a service with YAHOO! Inc. that helped improve ad targeting on its main website. This was a very successful early Big Data research service that used purchase panel data in conjunction with YAHOO! surfing behavior. The surfing activity of a group defined from Nielsen’s purchase data was then scored against all YAHOO! visitors to improve ad placement on the site. Additionally, Nielsen offered a test and control approach to assess the ROI of the campaign. This was an innovative research service that provided inputs that made marketing activities more efficient. Yesterday I attended a notable presentation, *Extract the True Value of Research with Big Data and Machine Learning*, at the 2014 CASRO annual conference. Presented by Doug Miller (Vice President of Analytics at Rock Fuel, Inc.), he illustrated well for me the current state of the art in Big Data and the changes that it will bring to the market research function. The impressive advances on both the media buying side, via the development of programmatic buying, and the ad placement side, with increasingly complex and comprehensive techniques that constantly update and refine ad targeting models, have pushed us close to the ultimate goal of one-to-one marketing. A fundamental shift has occurred here, marketing research in these Big Data marketing machines is embedded in the process and not a separate activity. That said, you have research that helps refine and improve the effectiveness of the advertising as we had in the Nielsen example, but now it is conducted as an integral, real-time component of the marketing activity. Marketing research has long held a position as an independent auditor with a mission to seek out the consumer truths. Marketing agencies that did their own research were regarded as ‘foxes guarding the henhouse.’ In the fast paced world of Big Data, there may not be a place for an independent market research function -- I wonder if the MR fraternity will embrace these new marketing agencies or ignore them? We need to acknowledge that the future definition of MR firms will be blurred and the ultimate goal of our industry should be to ensure the automated research processes used in many Big Data applications adhere to the MR Code of Ethics. Media targeting and ROI analysis will become a fully integrated part of the marketing agency function, rather than an activity performed by researchers. The watchdog will be the role of the corporate MR staff rather than an independent MR agency. We can embrace this as a positive development for the MR function in general. By viewing this like a production line that has been sped up to increase efficiency, companies will soon realize that if mistakes are made a lot of product can be wasted, if no one is watching. The future MR professional will be part data scientist, part quality control manager. 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