The Tragic Tale of Research Participants

In parallel to the GRIT report, last year Research Now partnered with ESOMAR to conduct a uniquely expansive survey into the public perception of the market research industry.

By Melanie Courtright 

This year, for the first time, the GRIT report explored the elements that come into play when designing and implementing research and it threw up some fascinating, yet slightly worrying, results. In parallel to the GRIT report, last year Research Now partnered with ESOMAR to conduct a uniquely expansive survey into the public perception of the market research industry, surveying over 6,000 people through multiple methodologies, in the US, UK and Germany. Combining some of the data points in these two surveys highlights what should be a significant concern for our industry.

Firstly, the GRIT report indicates that, in the last 3 years, there has been little to no change in the percentage of surveys that are optimized for mobile which stands at an embarrassingly low 15%. What also concerns me significantly is the importance of ensuring that participants have a positive impression of market research after they have contributed to a research project. Only 5% of client-side researchers and 9% of research providers judged this to be of significant importance when designing research studies. Only 4% of client-side and 7% of supplier-side researchers felt it important that participants speak highly of their research experience. And we wonder why respondent rates are falling?

In our public perception survey, we found that CATI participants had the lowest exposure to market research, compared to other methodologies (online panel and social media panel), with almost half of those in all 3 markets taking part in research less than once a year, or never. Because of this, it is clear that the data taken from the CATI sample provides the clearest view of the perception of market research in the broader general public. Data provided by the CATI participants showed that in the US only fewer than half of those surveyed agreed they trust market researchers with their data. And while participants in the US are comfortable sharing information such as their favorite supermarket or their thoughts on advertising, the study indicated they were far less comfortable sharing more personal information. Only 25% were comfortable sharing information about salary and just 30% were comfortable sharing their internet search activity.

When you combine these figures, we start to develop a detrimental story of the industry’s lack of consideration of participants and the public – and what that could mean in the long term for the industry.

The industry needs to do far more to communicate the value of the research to the general public; we should no longer treat them as a commodity but as people that need to be engaged with. The need to foster a human connection with participants is underlined by the degree of distrust and discomfort in sharing more sensitive data. We are proud to have partnered with ESOMAR on this study and we support them and others as they take steps to educate the public on the value of research. But we need to ensure the process of engagement continues when people become our participants. How can we hope for better data quality and healthy databases when many research providers care so little for the participant experience?

Market Research Automation: Our Greatest Fear or Innovation?

What new accomplishments may market researchers reach if they had better-thinking machines to assist them?

By Adriana Rocha

Let’s face the reality: in a very likely future, many of the things we do today will be automated. People, from many areas and industries, are becoming very concerned about advancing automation. And indeed we should be, especially that automation, in the form of artificial intelligence, is invading many work areas, even those more intellectual than manual, and those involving decision making.

In the context of market research, increased automation is focused on operational efficiency, gaining speed and costs savings, but it limits us to thinking within the parameters of work that is being accomplished today. When we consider the quality issues the industry faces with poor online data collection, professional respondents, frauds, etc. my main concern is that speeding data collection automation will just scale the size of the problem. That could be our greatest fear!

However, if we look into advances in automation from a different perspective: what new accomplishments may market researchers reach if they had better-thinking machines to assist them? As David Autor, an economist at MIT, says: there is an immense challenge of applying machines to any tasks that call for flexibility, judgment, or common sense. Also, he states: “tasks that cannot be substituted by computerization are generally complemented by it”. Fortunately, computers aren’t very good at many sorts of things, and here are some examples where market researchers can win upon machines:

1)  Analysts – bring strengths to the table that are not about purely rational, codifiable cognition, with more big-picture thinking and a higher level of abstraction than computers can provide. Let the machine do the things that are beneath you, and take the opportunity to engage with higher-order concerns;

2)  Data Scientists –understand how software makes routine decisions so you monitor and modify its function and output. You can interfere as necessary in special cases or experiments, as well as to improve the algorithms;

3)  Story Tellers – you are better at considering the big-picture than any software. Use your intuition and creativity to tell the story behind the data;

4)  Specialists – specialize in something for which no computer program has yet been developed. People who can go deep in their particular area of expertise have more chance to win: an anthropologist, for example, has deep expertise in observing and interpreting human behavior than any computer; a good moderator will be in need to lead a group conversation, even that is held on a computer platform;

5)  Innovators – build the next generation of market research applications or smart machines. A digital innovator takes hold of new ways to use data and optimize its usage for key decision-making.

So, my conclusion is that a lot of focus on market research automation nowadays has been dedicated to data collection, and it will continue growing and improving. However, the industry should put more focus on fixing the problems with poor online data quality, before investing much in automating such processes.  On the other hand, we can see rising possibilities as we reframe the threat of data collection automation as an opportunity for expansion of the industry into the new data avenues, innovation in artificial intelligence, advanced analytics and reporting.

Hence, smart machines can be our partners and collaborators in creative problem solving. Let’s take advantage of that! 


Our Automated Future (The New Yorker):

Beyond Automation (HBR):

Welcome to the Third Age of Focus Groups

Recent reports of the death of the focus group have been greatly exaggerated. Jamin Brazil, CEO of FocusVision explains why the focus group is even more relevant today than it’s ever been.

By Jamin Brazil

In the Wall Street Journal late last year there was an extensive article that explored innovations in technology, big data and social media monitoring. It argued that given the growth of new ways of listening to customers, focus groups are no longer a relevant way of finding insights. But I would argue that in the advent of this tech explosion, focus groups are an even more powerful tool.

The focus group is nowhere near dead.  In fact if you look at the new technology available to set up, run and communicate the results of groups, it’s easy to see we are entering the third age of Focus Groups. There have been massive progressions in digital sharing, storage and streaming. We can now run and record groups from multiple locations like never before – bringing people together to get a mix of views and finding people in out of the way places.

But more than that, technology is really democratizing the focus group, giving voice to people who would not be historically have been able to take part in research and allowing people to set up and run groups who would previously have found them impossible. Given the new technology, anyone can run a group, from anywhere, with participants the world over. This convenience has significantly improved the opportunity for listening and engaging with consumers.

But most importantly, in the world of big data and social media listening described by The Wall Street Journal, the focus group is now even more vital in helping us to understand not only ‘what’ is happening in the minds and lives of consumers but ‘why’ – and therefore what actions to take. In fact, I am certain that with the growth of big data the focus group will become even more important.

Let’s just look at last year’s election. The amount of big data we were supplied with was not a problem. In fact we saw an awful lot of quantitative polling data bandied around from a myriad of sources. Daily polls scrutinized the candidate’s performances at every turn. The polls fed off the media and were in turn fed by them. In this heated atmosphere when the numbers and the stakes are so high, it’s easy to dismiss a bit of qualitative research or the good old focus group as small, old fashioned and behind the curve.

But only looking at the big data of the polls meant many of the pollsters called it wrong – or said it was too close to call. The same happened with the Brexit election in the UK earlier in the year. By using the new tech advances in focus groups, the polling organisations would have gotten a much deeper understanding of what the great US public was really saying. They might have heard the voices of really disenfranchised and disaffected, those who responded to the Trump rallying cries and voted for change.

In addition, having new video technology around focus groups is bringing the true voice of the customer right into the boardroom for the first time.

How? Well, with new 3600 voice activated digital cameras like FV360, you can be in the heart of action of a group when you are not even there. Placed in a room with a physical group, these cameras are triggered by the voice of who is speaking, and the speaker is filmed, so that you will not miss their comments, expressions and reactions ever again. The result is a single video stream of each group (rather than multiple streams, as with static cameras) so less actual video to be reviewed, but with more actual detail, meaning it is much faster and easier to edit into a cohesive film. As a result the moderator and client can together create impactful video from each session at the click of a button.

Once tagged, these films can now be stored by key word, brand name or whatever term you wish, making for simple archive storage and access to key word searches.  So now those not at the group can see the edited and structured video, with zoomed in footage of participants, bringing the experience to life. The ease of editing these tagged films means users can supply the three minute version for the C-suite and the 20 minute version for the marketing team without video editing expertise. And as we all know, the impact of video is far, far, stronger than using a verbatim or even a photographic vox pop approach. Even non-research stakeholders get a much better grasp on the lives and concerns of consumers and their relationships with brands, products and services, than ever before: as we might have seen had some of those pollsters used focus groups during the election.

So, sorry Wall Street Journal, the focus group is far from dead. In fact, we are entering the third age of groups and I for one am very excited to see where it takes us.

Why Pie Charts are Better Than Bar Charts

The implications of the research studies used to criticize pie charts are greatly over-stated. And some are junk science.

By Tim Bock

Ok, ok, this blog’s title would be a bit more accurate if the word “often” appeared in the title.  In my defense, all the anti-pie chart trolling provoked me! Troll HQ, Wikipedia, writes “Statisticians generally regard pie charts as a poor method of displaying information“.  Ouch! And a curious error of logic hides here. Let me give you a hint: who hires statisticians to design visualizations?

Before I jump into the detail of my thesis, let me jump straight to some examples, as many people that hate pie charts really just hate ugly pie charts. Below I show both an ugly and an amazing pie chart. I am sure we can all agree that one of these deserves contempt. But, are they both so bad?

Back to the debate. The redoubtable Michael Friendly has written a 14 page treatise, Save the pies for dessert, denigrating the pie chart, in which he says:

I have read every research study that I could find that tested the effectiveness of pie charts versus other means of displaying quantitative data … and have found only one advantage that can confidently be attributed to pie charts. Unfortunately, this one strength is rarely if ever useful.

Despite this denigration, businesses use them all the time. Why? Is it that business people are dumb, and that they are all making the same mistake? No. It is not. The problem is that the implications of the research studies used to criticize pie charts are greatly over-stated. And some are junk science.

Compare the column chart of the same data. Yes, it is better than the ugly bar chart. It is, however, markedly inferior to a pretty pie chart.

A simple visual experiment demonstrates the power of the pie chart.

Pie charts are better than bar charts

Look at the two bars. How long are they? There is no way you can tell without labels. You cannot even tell their relativity without a ruler. If I were to tell you that the bar above was one-quarter the length of the one below, you may well believe me. Short of using a ruler, you will never know for sure. Now look at the pie chart on the right. It is clear that the missing slice is 25%. Not 27% and not 23%. Sure you cannot tell if it is 24.5%, or perhaps 25.3%, but you can readily see that it is very close to being precisely 25%.

Pie charts tap into our instinctive ability to assess proportions when we look at things. As a result, we should consider the pie chart whenever we need to communicate proportions. There are lots of situations where proportionality is key. For example, as we can all recognize a straight line, a pie chart showing voting preferences is the safest way to communicate whether a political party has a majority or not.

Our instinctive love of pies

Our ability to interpret proportions is hard-baked into our brains. Surviving on the savanna frequently required us to look at objects and assess proportionality. How much of the apple have we eaten? How much water do we have left in the gourd? How much of the cake is left? Evolution has given us the skill to assess proportions instinctively.

We continue to train this skill teaching fractions using pie charts. This is why in the example above you get to exactly 25%, as your brain reaches back to junior high fractions and geometry. Watches and clocks require the same skill, which is why some people use watches without numbers and ticks. Most importantly, we regularly practice these skills when dividing up a pizza.

So, the first great strength of the pie is that we are really good at reading them. Of course, it is lot easier to make a bad pie chart than a bad pizza. Consequently pie charts often get a bad rap.  The biggest problem with normal pie charts is the labels. You will see in the example below, that with a bit of love (from my colleague Michael Wang), this is a solvable problem. Nevertheless, the pie chart is still far from perfect, but this one makes it easy to see that there are many browsers out there, with Chrome 48.0 dominating the market.

If you want to play around with these examples, or plot your own data so that it looks like the examples in this blog, click here.

Sorting helps

If we sort, we end with something a whole lot better. Our brain can easily work out from this chart that two browser versions, Chrome 48 and IE11, make up more than half of the market in our data. Again, we can do this instinctively, as we can see that their combined shares are bigger than a semi-circle. The only way to get that from the comparable bar chart would be to add up all the numbers. The point of a visualization is to let the viewer see the patterns, not to provide numbers that they can then add up.  Thus, the pie chart wins hands down for data like this.

Even the brands that are too small to plot are taken care of. We end up with a beautiful visual effect as they fade into obscurity on the left-side. However, you can hover over them with your mouse to see the tooltips, thus losing no information. In a bar chart, these would likely have been merged into an unhelpful “others” category.

Donuts are even better when you have lots of categories

We can also scoop out the middle of the pie to create a donut, and use the new-found space to add more labels, if we have the need.

As shown at the beginning, we can add even more clarity by nesting a pie chart within the donut. This final visualization allows us to quickly see that Chrome is more than half the market, and that the lion’s share of this is achieved by Chrome 48.

If you want to play around with these examples or plot your own data so that it looks like the examples in this blog, click here.

Originally posted here

Jeffrey Henning’s #MRX Top 10: Uncool Brands, New Speakers, and Questions to Ask Before Asking Questions

Of the 5,177 unique links shared on the Twitter #MRX hashtag over the past two weeks, here are 10 of the most retweeted...

By Jeffrey Henning 

Of the 5,177 unique links shared on the Twitter #MRX hashtag over the past two weeks, here are 10 of the most retweeted…

  1. UK Teens “Fed Up With Brands Stereotyping Them” Research Live reports on a FreshMinds survey of 500 teens: brands should concentrate on improving products and services and not “try too hard to be “
  2. Research Methods – 14 Questions Before Planning Market Research – Mike Brown of Brainzooming wants you to ask your team 14 questions before your next #MRX study. Make sure to ask questions about previous market research, explore research others have done, anticipate surveys others might be doing, then consider preliminary research to
  3. Edward Appleton’s Impressions of IIeX EU 2017 – Edward Appleton of Happy Thinking People appreciate that this year’s IIeX discussed more qualitative techniques and included more new speakers. Five key themes were crowd wisdom, automation, artificial intelligence, implicit methods, and stakeholder
  4. IIeX Europe Was So Great, We’re Doing a New Speaker Track in Atlanta! – Annie Pettit continues her work to broaden participation in market research conferences with a call for first- time speakers for IIeX
  5. Rapid Growth Continues at Join The Dots as Revenue Hits £9.8M – Writing for Research Live, Robert Langkjaer-Bain discusses Join the Dots’ third consecutive year with growth above 25%.
  6. Remesh Brings AI Research Tool to Latin America – Remesh has partnered with eCGlobal for studies in South America and Central
  7. The Five Rs of Marketing – Nigel Hollis of Millward Brown argues that the Five Rs of marketing are Reach, Relevancy, Reaction, Resonance, and
  8. How Barnes & Noble College is Cracking the Code on Millennial and Gen Z Needs – Writing for Quirks, Lisa Malat, the CMO of Barnes & Noble College, discusses their student panel, which fueled almost 60 research studies and 100 polls. One key innovation that grew from this research were “Freshman VIP” events, which helped freshmen make their first friends at
  9. A Word with the Speakers for the Upcoming QUAL360 North America 2017 Conference – The conference will focus in part on “Big Qual”, “learning how to utilize large amounts of qualitative data”.
  10. CRM Isn’t ‘Dumb’, But It Does Need More Intelligence! – Writing for Sales Initiative, James Reid of Artesian Solutions argues that CRM systems need to get beyond storing static data, a la traditional databases, and incorporate automated intelligence gathering for a dynamic 360° view of customers and

Note: This list is ordered by the relative measure of each link’s influence in the first week it debuted in the weekly Top 5. A link’s influence is a tally of the influence of each Twitter user who shared the link and tagged it #MRX, ignoring retweets from closely related accounts. Only links with a research angle are considered.

It’s 3AM, Do You Know What Your Distinctive Brand Assets Are?

Do you know which of your brand identity elements are driving the distinctiveness of your brand?

By Jonathan La Greca

Can you identify some of these brands? Why are some of them so easy to recognize? What emotions do you feel when you recognize them?

What is a Distinctive Brand Asset?


Distinctive Brand Assets are consistent sensory & semantic cues that make it easier for consumers to identify your brand and recall the associations related to it.

Any element within your brand identity that is unmistakably recognized as belonging to your brand and elicits associations that are “on-brand” is a Distinctive Brand Asset. These include and are not limited to colors, shapes, scents, sounds, tastes, textures, fonts, taglines, packaging, products, logos, claims, tones of voice, brand characters, and celebrity endorsers.

Why are Distinctive Brand Assets important to you and your Marketing team?


Most global leadership brand building organizations are trying to implement Byron Sharp’s “Laws of Growth” to build distinctive and coherent brands.

Thriving brands know that consistently activating their Distinctive Brand Assets across all marketing touchpoints builds and reinforces memory structures, creating mental availability for their brands, while building long-term brand coherency.

Distinctive Brand Assets drive brand growth by improving brand linkage in your advertising while making your brand more familiar, easier to find, and easier to buy!

Do you know which of your brand identity elements (e.g., brand color, font, logo, brand character, etc.) are driving the distinctiveness of your brand?

Maybe it’s time to pick up a copy of How Brands Grow. In the meantime, if you’d like a free copy of our summary of How Brands Grow, please contact Jonathan La Greca.


Voted among the top global insights consultancies for 3 years in a row, Hotspex is working with 15 of Top 20 advertisers in over 30 countries because we leverage the most innovative approaches from behavioral sciences, combining System 1 and System 2 measures to truly understand WHY consumer behave the way they do. We then apply marketing sciences, such as the Laws of Growth, to help you find out HOW to apply your insights in an actionable way to build distinct and coherent brands that accelerate growth.

Information Addiction: The Implications for Society, Brands, Advertising & Research

Researchers are going to make sense of a society that is fragmenting not by age and traditional demographic, but by political and social attitudes.

By Jon Puleston

My name is Jon Puleston and I am addicted to information. From the moment I get up in the morning until I go to bed at night, I am immersed in information gathering.

News was something I used to read once a day. Ever since I got a smartphone, my propensity to consume news has slowly increased month by month. With the ever- increasing proliferation of news aggregation apps, it’s becoming something I dip into almost every spare moment during the day. The first thing I do when I wake up in the morning and last thing I do at night before switching off my phone is check the “news”.  It has become a total addiction. In addition to news, there is social media, which I consume with equal levels of hunger, be it Facebook or Twitter or LinkedIn.

Where I am foraging news information from, and the way I am processing and using news information, is changing too. And it is also fascinating to observe the changes in the news information I am consuming.

In days gone by, I would pick up a newspaper and carefully read it through from cover to cover on my commute to work. I might read 80% of the content. The news content I read in this “highbrow” paper could be likened to consuming a relatively well-balanced meal. I would get a fairly rounded picture of what was going on in the world, albeit from the probably quite biased and subjective perspective of the editor of my paper.

Now I am scanning through hundreds of headlines, from multiple editorial sources on news aggregator apps, looking scantly at the headline and pictures and making instant judgments about whether or not to read them.  My content read ratio has dropped to below 5% and what’s more, my diet has changed too. I consume highbrow and lowbrow news content side by side. I self-select news, hunting out very specific things I am interested in. And to be frank, a lot of it is cheap hits, often fairly salacious news stories that I might never have been exposed to nearly as much in the past.

With my researcher’s hat on, self-observing this change, I began to take a wider interest in understanding the character of news being consumed more generally these days by the wider public, how are people navigating through this sea of information, and what is actually cutting through. So earlier this year I got my team to scrape data on 30,000 Reddit headlines. We examined how many upvotes each headline got and how many comments they solicited, and I started to analyse them.  To understand the character of the news that was cutting through, I then creamed off the top 5% and tried to take an objective look at the content of these headlines, trying to segment and classify them.

As you can imagine, the stories that get to the top of the new pile are a real cabinet of curiosities. A heady mix of genuine news and what might be described as unbelievable truths, headlines that at first glance are so unlikely to be true that you are forced, like passing a road accident, to stop and read them e.g. “I think I found a U-Boat in Somalia” ; or of car crash observing nature e.g. “A beautician removing blackheads”. Something deep and primeval inside you forces you to click to and view. In the very process of analyzing this content, I would find myself being sucked into reading them just out of curiosity.

Amongst all these salacious stories there was, in fact, a fair amount of quite serious content.  I was surprised by the high number of health and wellbeing stories, epiphanies and home truths, self-learning and general tips for getting on in life; there were also a large number of stories of a political & social campaigning nature, and people protesting against things that they thought were wrong.

The remaining volumes, probably half of the headlines, were made up of a diverse range of headlines that are saying essentially, read this and you will be entertained. Funny, often celebrity dominated stories, and perhaps not surprisingly, a huge number of pet-related content!

I then began to think about some of the background reasons and motivations for reading all this stuff…

I observed that a lot of the successful headlines heavily relied on content juxtaposition, presenting two conflicting ideas that at first glance did not make sense, triggering a curiosity response, for example: “When your cat has a drinking problem”. I think this highlights how we process all forms of information – we are primed to notice differences and oddities. You could describe these as trick headlines.

I think this is the reason why health and wellbeing stories cut through, they tap into the basic human survival instinct.

You could describe a lot of the rest of the content as pure “information porn”, stories that deliver the reader an opportunity to feel some emotions and feelings – we are using the news as a means of getting a quick dopamine hit and so the consumption of it becomes an addiction similar to smoking.

But I think, for the more political and social campaigning content, it’s more than just getting a quick hit.

From a personal perspective, I observe myself getting so much more emotionally involved in the news these days, in the same way, perhaps, that you get hooked into soap operas if you watch them every day.

The major news stories like Brexit and the US election and more recently Trump’s antics, have all completely hooked me in. I have literally mainlined news content from these political stories.

…and how I am using and processing this information goes way beyond objective information gathering.  What I am looking for so often are arguments and evidence that support my point of view and active process of confirmation biasing myself!  I am highly practiced in SCHADENFREUDE, delighting in reading stories about the downfall of political foes, people with opposite opinions having their arguments skilfully met. I am also good at ignoring news stories that I suspect are going to say something that I don’t believe.

News stories are like picking out chocolates from a variety box, you pick the ones you know will taste nice, and rather avoid the ones you think will taste bad.

The impact of this is that find I am far more drawn into politics than I have been in the past.  The campaigning and social nature of information content is so much more significant than it once was.  Politics for me is replacing soap operas literally.  I could go as far as saying I feel like I am involved in some sort of news information war, sharing stuff I want others to see and themselves propagate out.

And it’s not just me, the high number of posts of a social campaigning nature cutting through on Reddit seem to support this idea.  There is further evidence of this in a poll we conducted of 1,000 consumers in the US to understand how they processed news information during the US election, which could be described as one of the greatest political soap operas of all time.

During the election, over 80% of the electorate we polled used online new sites in supplement to traditional mainstream news, the majority (55%) on a daily basis. So many expressed their frustration at not being able to access the right type of news they wanted to consume in conventional new media such as TV, radio, and published newspapers. Over 75% believed the mainstream media to be biased.  Over 55% said they used alternative news sources to get their news fix, but also to help readdress the balance.

We are picking up and running with this news information.  We are socially sharing what we consume en masse, what we think is important. Politics, as a result, is becoming a whole lot more resonant with elements of our social discourse. Once upon a time I might have discussed a news story I read in the paper over a pint in the pub with one or two friends, now I share a news story with across a social network that reaches hundreds of people.

For many, Facebook is becoming one of these primary battlegrounds for news sharing and delivery. During the election, the average Facebook user in our poll estimated that they saw between 50 and 100 political news stories shared by their friends.

The level of self-selecting of news stories was also very apparent from this survey. The chart below illustrates this beautifully we asked how many of the news stories they saw were positive about the candidate they also supported and both sides had a completely myopic viewpoint on the election.

As Adam Curtis, the filmmaker has observed in his compelling documentary Hypernormalisation, we are using online as a refuge, a place where we go to get our ideas re-assured. The chart below illustrates the tribal nature of this discourse during the Brexit vote. This is a map of news stories distributed on Twitter:

This clearly has some profound implications for society. What we are witnessing is social cults emerging, communities isolated not by geography but by opinion. We are all essentially preaching to our own converted communities.

The force behind this is the strong desire to belong. Research conducted by The New York Times exploring the psychology of sharing highlighted how news stories were being treated as a currency for building our social status: if I share this then people will like me!

New morality frameworks are emerging. Where once we were morally led by religious leaders and our family, we are now lead by a new form of social based morality – what is right or wrong not being reinforced in churches and temples for most people but by our friends on Facebook.

Where this could lead it potentially quite worrying.  Emergence potentially of social cults and warring communities made up of opinion tribes does not seem like a big imaginative stretch.

There are important implications in the commercial arena too.

Brands and business are going to have to be increasingly wary of these emerging tribal social communities which are a lot more politically motivated and easily mobilized and cross connected globally. Woe betide the social crowd’s outrage, the power of social campaigning will present a real threat to brands in the future. Brands are going to have to build stronger social consciousness to protect themselves. You might also imagine brands in the future becoming more political to appeal to different social tribes.

Advertisers are going to have work out how to cut through all this sea of information – they are going to have to build their own carnival floats to stand out and get noticed.  They are going to have to become more entertaining, and I see a return to a lot more old school feature benefit advertising.

Researchers are going to have to define new social segmentations and build new influence models that make sense of a society that is fragmenting not by age and traditional demographic, but by political and social attitudes.

Are you addicted to information?

if you feel you are affected by any of these issues visit:

See It First At IIeX

Posted by Leonard Murphy Friday, March 10, 2017, 16:53 pm
Posted in category General Information
IIeX North America is coming up June 12 - 14 in Atlanta. Check out this video to see why it's a special event in the industry landscape.


What makes IIeX… IIeX?

Check out this video for a peek into our world (and some words from our friends at Merck, ZappiStore, Sentient Decision Science, Fetch Rewards, VoxPopMe, Gen2 Advisors, and your’s truly!); it even has drone footage!

Check it out:

We want to see you at IIeX this year. Be there to discover new technologies and game-changing startups. Learn from thought leaders in the industry, and meet corporate researchers on the lookout for their next business partner.

Register today or learn more about our events:

IIeX North America –
IIeX Health –
IIeX Europe –
IIeX Forum on Nonconscious Consumers –
Attribution Accelerator –

See you this June 12-14 in Atlanta?


Walking The Rainbow Bridge To Insights Asgard With OdinText: An Interview with Tom H. C. Anderson

Posted by Leonard Murphy Wednesday, March 8, 2017, 9:12 am
Posted in category General Information
My interview with text analytics guru and market research iconoclast Tom H.C. Anderson and marketing master Tim Lynch of Odintext on the state of text analytics, applications in market research and other enterprise groups, and how to successfully guerrilla market.

Few folks in the market research are as well known as Tom Anderson. Whether through his role as the primary evangelist of text analytics in insights via OdinText, as the founder and moderator of the NGMR LinkedIn Group, or his frequent speaking engagements all over the world most everyone knows who he is. But knowing who he is and knowing what he is all about and the great work he is doing in helping to transform insights via the application of text analytics are two different things.

Over the years I have come to not only like and respect Tom, but to actually be in a bit of awe when it comes to the genius ways he combines technical and strategic thought leadership, personal passion, and marketing savvy.

Take a look at just a few of the recent posts from the OdinText blog for example:






Not only are those all cool examples of use cases for text analytics as a primary insights generation tool, but they are also fun, topical content hooks to drive brand awareness. It’s a pretty perfect one-two punch for a young company out to change an industry.

Here is why all of this is important and I’ve chosen to highlight Tom. The insights industry is changing fast due to the forces of technology, new competitors, evolving business models and client demands. In that environment the secrets to success are:

  • Having a great product that has demonstrable impact
  • Delivering flawlessly
  • Building a strong, differentiated brand
  • Being a masterful marketer

Tom is pretty much the template for those attributes, and the rest of the industry should pay attention to him as such.

Now, lest we let my man crush get in the way of objectivity lets be clear; anyone who knows Tom also knows he is outspoken, has a wicked (and politically incorrect sense of humor) and like yours truly can sometimes be a bit too honest. Those are always struggles when a company has a dynamic CEO that is deeply integrated into the brand itself and sometimes it can backfire, so there is a lesson there as well to be careful not to let the personal brand eclipse the company brand.

I recently sat down with Tom and his new partner in crime Tim Lynch (who is also a major industry mover and shaker) to catch up on OdinText, the recent Insights Association CEO Summit, and his take on the future of the industry and what’s next for he and his company. Bearing in mind my lead in on this interview, I suggest you watch it and pay close attention: you’ll learn a lot from both he and Tim that could be important to your business, not least of which is that text analytics can do some pretty amazing stuff to enhance your insights capability.

Here is the interview. Enjoy!

Bias and the Election: What No One is Talking About*

Bias impacts all of us, even pollsters, researchers, and decision makers.

By Katja E. Cahoon

Since the November 2016 election, much has been written and said about the discrepancy between polling results and the actual outcome. But one topic is almost completely ignored, and I personally realized it the hard (or shall I say, unpleasant) way.

There have been important discussions about sample size and sample representativeness, sampling and non-sampling error. About using better methodologies and approaches that bypass the rational mind and what people say (e.g., Implicit Association Testing). About simpler ways of getting data (e.g., text analytics), and accounting for the lack of ability or willingness to answer a question truthfully (e.g., because it might not be politically correct). The latter brings us back to better methodologies and asking non-biased versus biasing questions. Even the challenges around understanding probabilities and different models have been discussed.

During the excellent ARF / Greenbook Election 2016 Debrief – Research & Analytics Event, many of the above topics were discussed by the speakers and panel members[1]. This event provides insightful responses about what went right and wrong. It is also relevant for market research in general, especially given high product failure rates (it is not 80%, that is an urban myth, but it is still high enough[2]).

One topic was mentioned in passing by a few of the knowledgeable speakers and panelists, especially Melanie Courtright, EVP at Research Now, which brings me back to my uncomfortable wake-up call:

Two days after the election, still reeling from the surprise, I had the pleasure of doing an in-depth IDI with a delightful man in his forties from the Mid-West about a topic related to work and finances. He had a Master’s degree, was a manager for a small company, and happily married with two young children. He was the kind of dream participant qualitative researchers hope for – open about his life, finances, fears, and hopes, generous with his time, and both thoughtful and able to discuss his emotions. His main concern, reiterated over and over, was to provide for his children and wife combined with his fears about not being able to do so because of rising health care and living expenses. My heart went out to him. And then he revealed that he voted for Trump.

It is rare to experience undiluted cognitive dissonance, but that is exactly what I felt. For months on end I had considered Trump voters to be largely the confederate flag waving poor white males, the uneducated, the disenfranchised – a frame influenced by the media. This man was none of these things (except white and male). I am grateful for my training as a psychotherapist and my experience as a researcher, which helped me to catch myself. I was able to continue to listen to his challenges with real empathy. After the interview ended, I reflected on my experience and realized: it is not just about having the right data (there were indications that Hillary was not the clear-cut winner most pollsters and publications made her out to be, some indeed correctly called out Trump as the winner[3] as did Michael Moore). It is just as much about being able to see all the data and its implications, as opposed to be being blinded by our own frames, cognitive biases, and media generated impressions.

And that is precisely what is not talked about enough: bias impacts ALL of us, not just voters and consumers, but also pollsters, researchers, and of course decision makers. Melanie Courtright puts it best, “they were all wrong in the same direction, that indicates a bias.” A “democratic bias,” as Raghavan Mayur, President of TechnoMetrica Market Intelligence points out. This bias is reflected in the media. It certainly impacted me; I have a suspicion I am not the only one. This is the “echo chamber.” I should know better as a psychotherapist and highly trained researcher but as the wonderful Daniel Kahneman puts it in Thinking, Fast and Slow, neither intelligence nor experience protects from falling prey to cognitive errors.

And decision makers are impacted as well. Overconfidence in the Clinton camp, especially toward the end, points to that. This is certainly not limited to politics, it happens all the time in business as well. All the way back in the 1970s Irving Janis wrote his ever-relevant book Groupthink. Without being privy to what exactly led to the systematic faulty forecasting and overconfidence I suspect aspects of groupthink played a role (indeed, overconfidence is one of the hallmarks of groupthink).

So, what can we do in addition to becoming better and better at collecting data? It is pretty well accepted at this point that consumers (and especially voters) are not rational beings and are impacted by cognitive errors and biases. But have we – marketers, researchers, and decision makers – truly accepted that we are as well? This is precisely the first step of the three steps of overcoming cognitive bias: true understanding and acceptance that we have them as much as any other human being. A Mistakes Were Made, but not by me kind of attitude does not serve us here. In the next article, I will dive deeper into the three steps of overcoming cognitive bias.




*The use of hyperbole is deliberate. Of course, some, but very few, researchers are talking about this explicitly.