Baby steps into the wearable era of research: ESOMAR DD 2014 Roundup

Compared to other global research events the ESOMAR Digital Dimensions conference is by no means the biggest, it faces competition, without doubt, from more ‘ideas’ driven events, but never the less it is by far and away still my favourite market research event on the global calendar. Now I have to say that because I was chairman this year, but I do feel that despite all the competition, it has reliably proved to be one of the most fruitful sources of new thinking and new trends for the market research industry - I consistently learn so much more at this event compared to the others I attend and this year it was particularly fruitful.

I think that part of its success is down to the consistently high standards ESOMAR sets on paper submission, only 1 in 5 papers get selected and it also demands a lot more robust thinking from its participants. What you get as a result from this conference is a really thoughtful mixture of new ideas, philosophy and argued out science.

This year was one of the strongest collections of papers ever assembled, so much so that the selection committee asked to extend the prizes beyond 1st place. There were 6 major themes that emerged and 1 paper that I think could go on to have a major impact well beyond the boundaries of market research and I returned home with 23 new buzzwords and phrases to add to my growing collection (see other post).

The big themes

1. The Physiological data age: At this conference we witness some of the baby steps being taken into the world of wearable technology; and a prostration by Gawain Morrison from SENSUM who were one of the stars of the event, that we are about to enter the physiological data age.  They showed us a galvanic skin response recording of a 7 hour train journey which revealed the insight that the highest stress point on the journey was not caused by any delays or anxiety to reach the station but when the on-board internet service went down!  IPSOS are one of many MR companies to start experimenting with google glasses and showed us how they were using them to conduct some ethnographic research amongst new parents for Kimberly Clarke. We saw some wonderful footage of  a father interacting with his new born child in such a natural and intimate way it does not take much of a leap of the imagination to realise wearable technology is going to be a big topic in future MR events.

2. The Big Privacy issues looming over these new techniques:   With the rise of wearable devices raises a whole range of new issues surrounding data privacy that was widely discussed at this conference,  Alex Johnson highlighted in his award winning work Exploring the Practical Use of Wearable Video Devices, which won best paper, - the central emerging dilemma - it’s almost impossible to avoid gathering accidental data from people and companies who have not given their consent to take part in the research when doing wearable research. It’s critical for the research industry to take stock of.

3. Developing the new skills needed to process massive quantities of data:  The second big focus of this conference, that Alex Johnson’s paper also highlighted, was the enormity of the data evaluation tasks researchers face in the future, for example processing hundreds of hours of video and meta data generated from wearable devices.  Image processing software is a long way from being able to efficiently process high volumes of content right now. He had some good ideas, to process this type of data. He proposed a whole new methodological approach which centres around building taxonomies and short cuts for what a computer should look for and a more iterative analytical approach.  In one of the most impressive papers at the conference TNS & Absolute Data provided an analytical guide to how they deconstructed 20 million hours of mobile phone data to build a detailed story about our mobile phone usage, that could be utilised as a media planning platform for the phone – the research battle ground of the future is surely going to be fought on who has the best data processing skills.

4. De-siloed research techniques: I wish I could think of a better simple phrase to describe this idea as it was probably the strongest message coming out of the ESOMAR DD conference - the emergence of a next generation class of more de-siloed research methodologies, that combined a much richer range of less conventional techniques and a more intelligent use of research participants. Hall & Partners described a new multi-channel research approach that involved a more longitudinal relationship with a carefully selected small sample of participants where across 4 stages of activity they engaged them in a mix of mobile diary, forum discussion and conventional online research - challenging them to not just answer questions but help solve real marketing problems; Millward brown described a collaboration with Facebook where they mixed qual and mobile intercept research and task based exercises to understand more about how mobiles are used as part of the shopping experience;  Mesh Planning described how they integrated live research data with fluid data analysis to help a media agency dynamically adjust their advertising activity; IPSOS showed us some amazing work for Kimberly-Clarke that spanned the use of Facebook to do preliminary qual, social media analysis, traditional home based ethography, and a new technique of glassnoraphy. What all these research companies demonstrated was that decoupled from the constraints of convention, given a good open brief from a client and access to not just the research data that the research company can generate but the data the client has themselves we saw some research companies doing some amazing things!

5. Mining more insights from open ended feedback:  Text analytics in infancy focussed on basic understanding of sentiment but 3 great papers at the event showed how much more sophisticated we are becoming at deciphering open ended feedback.  Examining search queries seems to be a big underutilised area for market researcher right now and KOS Research and Clustaar elegantly outline how you could gather really deep understanding of people’s buying motivations by statistically analysing the search queries around a topic.  Annie Pettit from Peanut Labs, looking at the same issue from the other end of the telescope, showed how the suggestions to improve brands and new product development opportunities could be extracted from social media chatter by the careful deconstruction of the language they used to express these ideas.  And Alex Wheatley, in my team at GMI, who I am proud to say won a silver prize for his paper, highlighted just how powerful open ended feedback from traditional market research surveys could be when subjected to quant scale statistical analysis, rivalling and often surpassing the quality of feedback from banks of closed questions.

6. Better understanding the role of mobile phones & tablets in our lives: We learnt  a whole lot more about the role of mobile phones and tablets in our lives at the conference, some of it quite scary.  We had expansive looks at this topic from Google, Yahoo and Facebook.  AOL provided some useful “Shapely value” analysis to highlight the value of different devices for different tasks and activities, it demonstrated how the tablet is emerging as such an important “evening device” , its role in the kitchen and bedroom and how the combination of these devices opens up our access to brands.  We learn how significant the smart phone is when we go retail shopping for a combination of social and investigative research reasons. We learn about the emergence of the “Google shop assistant” many people preferring to use google in shops to search for their shopping queries than actually ask the shop assistants and how we use the phone to seek shopping advice from our friends and how many of us post our trophy purchases on social media.

The impact of technology on our memory

The paper that had the single most impact at the conference was some research by Nick Drew from Yahoo! and Olga Churkina from Fresh Intelligence Research showing how our use of smart phone devices is really impacting on our short term memory – we are subcontracting so many reminder tasks to the technology we carry around with us that we are not using our memory so actively and this was demonstrated by a range of simple short term memory test correlated with mobile phone usage found the heavier smart phone users performing less well. The smart phone is becoming part of our brain!  This obviously has much bigger implications outside of the world of market research and so I am sure we are going to hear a lot more about this topic in the future.

Scary thought, which made the great end session by Alex Debnovsky from BBDO about going on a digital detox all the more salient.  I am going to be taking one soon!

The 4 killer stats from the ESOMAR 3D conference

I was only able to attend one day of this conference, for me without doubt this is the most useful research conference of the year and so I am sorry, I am only able to give you half the story, but  here is what I brought back with me, 4 interesting stats, 3 new buzzword and 1 stray fact about weather forecasting.

350 out of 36,000: This is how many useful comments Porsche manage to pick out from analysing 36,000 social media comments about their cars. So the cost benefit analysis of this runs a bit short and this was probably the headline news for me from the ESOMAR 3D conference: No existing piece of text analytics technology seems to be capable of intelligently process up this feedback. Every single one of these comments had to be read and coded manually I was shocked. I thought we were swimming in text analytics technology, but apparently most of the existing tools fall short of the real needs to market researcher right now (I spot one big fat opportunity!).

240 hours: This was the amount of time spent again conducting manual free text analysis by IPSOS OTX to process data from 1,000 Facebook users for one project (and from this they felt they had really only scratched the surface). As Michael Rodenburgh from IPSOS OTX put it "holly crap they know everything about us".  There are, he estimated, 50 million pieces of data associated with these 1,000 uses that it is possible to access, if the end user gives you a one click permission in a survey. He outlined the nightmare it was to deal with the data that is generated from Facebook just to decipher it is a task in itself and none of the existing data analytics tools we have right like SPSS now are capable of even reading it. There was lots of excellent insights in this presentation which I think deservedly won best paper. 

0.18: This is the correlation between aided awareness of a brand & purchase activity measured in some research conducted by Jannie Hofmyer and Alice Louw from TNS i.e. there is none. So the question is why do we bother asking this question in a survey? Far better just to ask top of mind brand awareness  - this correlates apparently at a much more respectable 0.56. We are stuffing our survey full of questions like these that don't correlate with any measurable behaviour.   This was the key message from a very insightful  presentation. They were able to demonstrate this by comparing survey responses to real shopping activity by the same individuals. We are also not taking enough care to ask a tailor made set of questions to each respondent, that gleans the most relevant information from each one of them. A buyer and a non buyer of a product in effect need to do 2 completely different surveys. Jannie senses that the long dull online surveys we create are now are akin to fax machines and will be obsolete in a few years time. Micro surveys are the future, especially when you think about the transition to mobile research. So we need to get the scalpel out now and start working out how to optimise every question for every respondent.

50%: The average variation between the claimed online readership of various dutch newspapers as publish by their industry jic and the readership levels measured from behavioural measurement using pc and mobile activity in tracking as conducted by Peit Hein van Dam from Wakoopa. There was such a big difference he went to great lengths to try and clean and weight the behavioural measurement to account for the demographic skew of his panel, but found this did not bring the data any closer the the industry data but in fact further away. Having worked in media research for several years I am well aware of the politics of industry readership measurement processes, so I am not surprised how "out" this data was and I know which set of figures I would use. He pointed out that cookie based tracking techniques in particular are really falling short of delivering any kind of sensible media measurement of web traffic. He cited the "unique visitors" statistics published for one Dutch newspaper website and pointed out that it was larger than the entire population of the Netherlands.

Note: Forgive me if I got any of these figures wrong - many of them were mentioned in passing and so I did not write all of them down at the time - so I am open to any corrections and clarifications if I have made some mistakes.

3 New buzzwords

Smart Ads: the next generation of online advertising with literally 1000's of variant components that are adapted to the individual end user.

Biotic Design: A technique pioneered by Yahoo that uses computer modelling to predict the stand out and noticeability of content on a web page. It is used to test out advertising and page design and we were show how close to real eye tracking results this method could be. We were not told the magic behind the black box technique but looked good to me!

Tweetvertising: Using tweets to promote things (sister of textervising)

One stray fact about weather forecasting

Predicting the weather: We were told by one of the presenters that although we have super computers and all the advances delivered by the sophisticated algorithms of the Monte Carlo method, still if you want to predict what the weather is going to be like tomorrow the most statistically reliable method is to look what the weather is like today, compare it to how it was yesterday and then draw a straight line extrapolation! I also heard that 10 human being asked to guess what the weather will be like, operating as a wisdom of the crowns team, could consistently out performed a super computer's weather prediction when programmed with the 8 previous days of weather activity. Both of these "facts" may well be popular urban myths, so I do apologise if I might be passing on tittle tattle, but do feel free to socially extend them out to everyone you know to ensure they become properly enshrined in our collective consciousness as facts!

Big data and the home chemistry set

Are we all Dodos?   I heard a couple of people tell us at the ESOMAR 3D conference that we are perilously close to extinction,  that we market researchers are dodos. In fact this has been a bit of a common theme at many of conference I have attended in the last few years a prediction of the terminal decline of research as we know it. The message is that our industry is gonna be hit by a bus with the growth of social media and the big boys like Google and Facebook and IBM muscling in to our space. We are also in many parts of the world facing tough economic times and tightening budget.

Yet despite all this it appeared that this was the best attended 3d conference ever, and it's not just this isolated conference either. I have been going to research conferences all around the world over the last year and they all seem to be seeing growing numbers of attendees and all I can sense from these conferences and particularly at this event, is an industry brimming with confidence and ideas.

So are we all putting on a brave face? Are we naively sleep walking into the future?   I don't think so...


The macro-economics of market research

Over the last decade we have seen a near exponential growth of data being generated by the worlds population. It is literally pouring out of the internet and our mobile phones.   We also have an ever increasing range of innovative ways to measure and analyse things, ranging from geo-location tracking right through to sensors attached to our heads.  We are able to measure almost everything we do. So who is going to do it? 

 We learnt at this conference how hopeless computers are at actually thinking and they lack the ability to really intelligently analyse data to the quality and standard needed to glean real market research insights. In every presentation we saw the critical contribution that human being had.  It just leads me to believe that with all this expansion of data the pool and means of measuring things more people are going to be needed to make sense of it all and who is best at doing this?  Ultimately I believe it is market researchers.  Media companies and consultancy firms might think they are in with a shout but I genuinely don't believe they have to core competences needed. Market research is all about working out how to measure things, gathering and analysis of data and using this to delivering insights. That is what we specialise in, that is what we are expert at.   No other industry is better placed to capitalise on all this free flowing data than ours.

The big thing I think we need to focus on is developing new tools to process big data. Right now it looks like we have oil tankers full of information waiting on our door step and the research industry is currently attempting to use tools that look like they are from a home chemistry set to try and process it into fuel.  

We need to develop more tools to refine all this information and learn the skills to do it.  That is our challenge , grasping the technology that is out there and adapting it for our needs.

But I have every confidence we can. I believe we are the best industry out there at cross communicating ideas and with that comes innovation. There are lots of people who bemoan the lack of innovation in our industry and again I see quite the opposite. I see an industry racing to innovate.  Step back and look at how things have developed in the last couple of years alone.  Look what we can do already in the field of mobile  research,  how many research companies have so quickly moved into offering social media research solutions. Look at some of the fantastic tools that have emerged like facial emotion measurement and neuro/biometric monitoring, look at what we are learning and embracing from the fields of behavioural economics, look at crowd sourcing and the success of MROC communities and how we have developed technology to serve these communities. Look at some of the new text analytics tools that are emerging.

I think the market research industry is more than capable to adapt to these needs and I feel it has a big future.

Evolution of Advertising v Survey design

Designing surveys is without doubt a creative process similar in many ways to other creative commercial art forms like advertising and presentation design.  I feel there is something we can learn from looking at the evolution of these other sister creative processes...

The evolution of advertising

Once upon a time advertising look like this...

But unfortunately not many people were reading them.  So they began to evolve.  They first of all started to realise the value of adding images...

And slowly over the course of 100 years or so they learnt the art of creative communication...

Minimalising the use of text and focusing on branding and selling messages and visuals grabbed peoples attention and re-enforced the message. 

Leading eventually to the evolution of the advertising agency...

Companies realise realising that they did not quite have the skills to do this job themselves, they passed it on to people who specialised in it.

And who today would deny the importance of creativity in advertising design.

Over a period of 200 years advertising moved from focusing only on what people wanted to say to focusing on how to say it.

Presentation design

A similar journey has been made in the development of presentation design.  Once upon a time presentations looked like this, text heavy and dominated by bullet points

They then tried rather unsuccessfully to liven them up with clipart and whacky transition effects..

And by throwing everything they could think of onto the page to grab your attention....

But slowly they learnt that colour and images should not be used just to decorate per say, but to help communicate ideas more clearly...

Image courtesy of Presentation Zen

And they learnt to cut back on content and use well chosen visuals to help emphasise content and make it more memorable...

And many of us now would probably call in a designer to help us create an important presentations say if we were delivering to 50 people at a conference..

Over the course of 20 years we have moved from focusing only on what we wanted to say to focussing on how to communicate a message.

And so to survey design...

Once upon a time surveys used to look like this..

 And they now tend look like this...

Sorry I am being a bit unfair there as there are people creating surveys that do look better than this, and so this is probably a bit of a cheep trick,  but I hope you get my point that this is still today what the majority of surveys look like.  We have not really got our heads round the survey design process quite yet.  I would say we are still at the 1980's clip art and whacky transitions stage of things. Our idea of making a survey more creative is to add in often a badly designed flash question or slapping a thumbs up icon on the top of a likert scale.  Our only real concession to the consumer in 15 year has been to add a progress bar, but I have seen recently suggestions we should take it off as it is causing drop-out (presumably because they are looking at it and thinking oh dear how much more of this survey have I got to endure!)

There is almost no basic grasp of design aesthetics in most surveys I see, very little effective use of imagery and that is just the start. The problems extend far beyond the visual. Our whole approach to the structure and copy writing of surveys is stuck in the 1950's when face to face interviews were pioneered, with these long verbose questions that nobody want to read and no sense of what it feels like as a respondent to answer a typical survey.

Over the course of the last 15 years we have not really moved very far, we still are focussing solely on what we want to know and give little but scant thought to ways to get respondents to give more effective and thoughtful feedback which is where I think we need to be at.

A question then is why?

Well there are clearly lots of reasons but the one thing in my mind is that we have not officially recognised as an industry survey design as a creative skill and we are not sure who's job it is either. And it is a task that is falling between 2 stalls...

Right now the only time creativity is considered is when the survey has been signed off and passed onto the survey programmer which I my mind is too late.  And just the term survey "programmer"  itself says something, often this is someone in a "downstairs"  department so to speak who you are not really actually expecting any creativity from.  

I feel that creativity needs to be injected right up the line starting at the conception stage and really needs to be focused at the writing stage, how we copy write and conceive questions and structure surveys is so important which is something I will be discussing in a later post.  

My main point though is that we need to recognise the importance of creativity in research design and establish creative service teams in research companies that take charge of injecting more creativity in research design across the board, who have the authority to orchestrate things higher up the line than at the production stage.  Akin to the authority an advertising agency has over the design of advertising.  

Note: This topic and these slides are an extract from a presentation I recently delivered at the WARC 2012 conference on the future of Online research where I was talking about how to inject more creativity in survey design.  The full deck and the full story can accessed from 

www.warc.com/OnlineResearch2012

Follow the discussion of this event from twitter on #nowandnext

Honesty of responses: the 7 factors at play

I read this very interesting post by Edward Appleton about the authenticity of peoples online behaviour published on the Greenbook blog. http://www.greenbookblog.org/2012/02/01/how-authentic-are-we-online/

The authenticity of online respondents is a very interesting philosophical question and is an area we have been looking at recently too - albeit in perhaps in a more literal way...

We have been examining ‘honesty’ within the online survey environment, by comparing answers to questions where we hold known norm figures about behavioural activity and building up a picture of levels of honest answering to different types of questions.


We have found that in the main most people in western* markets who respond to surveys are, on the whole, very honest in the answers they give.

Rolled up into averages, about 95% give "honest" answers to the average question - so it is not something you need to worry too much about for a typical survey.

But that figure of 95% is for the average question. This figure can vary dramatically and we have witnessed questions where up to 30% or respondents show signs of untruthfulness based upon the context of how you ask the question and the type of questions being answered and who you are asking.

The reasons for this, though, are complicated. We have identified a range of driving factors that determine the level of authenticity to an answer we may give, these are:

1. The Peacock syndrome: We like to show off and make others think we are smarter, wealthier, happier, better than other people. You can see this issue in effect on magazine readership studies where, for example, the claimed number of readers per copy of Vogue magazine is 12 - about four times higher than the average magazine. The number of people who claim to shop at Harrods the premium London on the TGI survey is about 2 times higher than the estimated footfall*. So you can never really trust stated figures about any claimed behavioural activity if it is socially desirable.

You must also remember that this process works in reverse. So as an example, people admitting to watching soap operas, smoking or noticing advertising, all things that we don't like to admit to doing, are all downgraded by us naturally.


*These figures themselves may not be completely truthful, they are plucked from my memory which is a well known source of untruthfulness if I am to be brutally honest!

2. Pleasers: This is perhaps more of a cultural issue. , Some people like to answer in certain ways to please you. Now, this is different to the peacock syndrome and it effects different types of questions, those that are less commercial questions and more social questions such as political opinions as an example. We are often very reticent to give our real views on certain topics for fear of perhaps offending. Or we may worry that our views are not socially acceptable. Or even in the extreme case of say, the fear of persecution if you were conducting research in an oppressive political regime.

3. Gamers: Now these are a set of people who adapt their answers to play the system, which is a big problem particularly in certain countries and for certain types of topic. For example, if I am trying to sample top end business people and I am offering a high incentive to take part then there will be those who will try to pretend to be business people so that they can qualify to participate in the surveys. But this is not just limited to a small group of fraudulent respondents. A lot of respondents start gaming the system when they simply get bored. They stop saying they do things or buy things to avoid having to answer extra follow-on questions.

4 Disengagement: This leads onto the last group which is the disengaged respondents who don't answer truthfully because they can't be bothered to think about it. It manifests itself on lots of different levels. Ad recall can vary by upwards of 100% between engaged and disengage respondent groups.

5. We lie to ourselves: We are all naturally quite self delusional. The image we have of ourselves photographically, for example, is often nothing like the image that other people see. So if you asked me to pick a picture which is a good likeness of yourself nine times out of ten it will be a different picture to what someone else will pick. It results in peacock answering but also a lot of delusional responses to social behaviour questions e.g. are you the sort of person who would recycle? We all like to think we do and a lot of us believe we do, but it is something we don't actually do in practice. Here is a link to a wonderful paper exploring this issue http://www.tandfonline.com/doi/pdf/10.1080/15298868.2011.617886.

6. The power of the unconscious: So much of what we do is controlled by unconscious decision making paths. The conscious v unconscious mind are often in conflict. We, as a result, often make irrational decisions and so we are not very good observers of aspects of our behaviour which is controlled by the unconscious. As a result we are hopeless predictors of certain things we do. Obviously this issue sits at the heart of behavioural economics.

7. General Ignorance: We simply don't know or don't remember answers to certain often very clearly obvious questions: do I have brown eyes? I don't know. Where do I live in the US - 10% of people don't know the answer to this, particularly if you show them a map of where they live (to the extent we had to stop using maps for this question in our surveys!). We also are unable to predict our future behaviour because we don't really know what we will do. , We are, in fact, particularly bad at this. You may as well pluck a random number out of your head instead of asking somebody if they are likely to buy a new product in the future or not as it is likely to be just as accurate.

Cross cultural differences in truthfulness

I have starred *Western markets earlier on because in non western markets the level of "honest" answering can drop significantly down to, in some cases, around 70%. In fact in some countries you can forget any other worry about panel quality and demographic sample biases. The level of honesty is the Number One issue that you need to contend with. The variance in levels of truthfulness is compounded by factors such as income. If the incentive to take part in a survey is relatively higher in one country v another you will see higher numbers of people motivated to be gamers for example.

The big questions

The big questions are to what extent can these relative factor be quantified? What impact do these things have relatively?, and what tools and techniques do we have to counter them?

This is something our Chief Scientist at GMI, Mitch Eggers has been extensively exploring over the last year and I hope we will be able to publish a paper on the topic at some stage in the near future.

Editorial: Pop Science Books

Reg Baker in his inevitable style posted a wonderfully forthright blog piece (click here to read) bemoaning the industries taste in books, pointing out that a great majority of the books in the list of nominees for the books that had the most transformative impact on market research were Popular Science and highlighted how unscientific some of these types of books are, championing potentially totally bogus theories that have not been subjected to proper scientific scrutiny. 

Now I can total understand his emotional reaction to this. I have exactly the same response when I go into health food shops and see all homoeopathic remedies on the shelf and am horrified that they can get away with their often totally bogus healing claims that have not been subjected to any rigorous medical trials.

But I have a few points on this that I thought I would share:

1. Books are not apples:  and in most cases not in the class of homoeopathic style remedies, one or two bad ones do not rot the whole crop.  Whilst there are some very bad pop science books, there are also some really brilliant ones that help, as Tom Ewing has pointed out, eloquently digest and explain often very complex subject matter in a clear and understandable way. To draw over riding conclusions about pop science books on the bases of analysis of parts of the sample is in itself is bad science.

2. We can learn things from all types of books:  I think reading pop science books is as important as reading more serious business books and as is in fact being open to read anything from any source. To be closed to one genre of books is like gathering research from an unbiased sample.   I am a believer in the wisdom of the crowd and any business book bogus or not that says reaches the New York Times best seller bogus or not, I would want to read almost on principal to find out what thoughts and ideas people find so interesting.  Its not to say you cannot read these with a critical mind.  What is more just because something is packaged up as a light read does not make it a bad thing.  It like a classical musician dismissing all pop music as rubbish and not listening to it - they would be missing some great tunes and conceptual musical ideas.

3. MR is a branch of pop science:  We in Market research are all actually in business of conducting "popular science".  Market Research is in theory a branch of science but very rarely do we adhere to the rigorous standards that scientist need to adhere to where conducting proper scientific research.  Who for example has ever conducted a double blind trial as part of a market research experiment? Next to nobody.  Who puts up all their raw data from their experiments up for peer review? Next to nobody.  Have I ever read an MR paper that would stand up to a rigorous scientific review?  Well yes, but not the vast majority and (certainly not any of the ones I have written I am afraid!).  

4. This type of debate is important:  So it is easy to take a pop at what Reg has written. But I would seriously encourage Reg to keep writing these types of posts. Without Reg Baker the MR industry would be woefully short of serious internal detractors and we need them.  Despite what we think, that we are all firing pops at each other in the MR industry,  very few people actually have the courage to stand up and hold something to account which is essentially what Reg is trying to do here.   

5. Science and commerce play by totally different rules: The reason is we are operating in a commercial environment where the market decides on whether something is right on wrong true or false not science.  We are all out peddling snake oil on one level or another and the once that can do it most successfully are hailed as kings.  Be it a company putting water in a bottle and selling it as a remedy or Apple packing up a few computer chips in nice wrapping and selling them for a lot more than their inherent value all commerce is a form of "deception of the truth", selling something for more than its inherent value or actual worth. As market researchers we are often called upon to work out what truths and falsehoods we can get away with, what deceptions will fly.  So for our industry to be respected we have to ensure we do try to re-enforce the types of standards that Reg Baker with every fiber of his being is trying to espouse.  

What Reg Baker is simply asking us to be is more scientific in our approach which I hail.