Visualize Response Patterns and Survey Flow Using Sankey Diagrams

Where the survey has skips and routing, so that different people answer different questions, validation can be painful. When there is missing data, it can quickly become a nightmare. Unless you use a Sankey diagram.

By Tim Bock

If you have spent much time analyzing survey data, then you have probably spent a lot of time validating it. This normally entails checking that the number of people answering the different questions in a survey make sense. Where the survey has skips and routing, so that different people answer different questions, it can be painful. When there is missing data, it can quickly become a nightmare. Unless you use a Sankey diagram.


Men don’t do much at home!

The Sankey diagram below shows gender (q1) by work status (q3) for fans of Desperate Housewives, a TV show that ran from 2004 to 2012. On the left side we can see that the viewers were predominantly female. Hovering your mouse over the bars will show you how many. On the right side, we also see that most viewers work full time, with less than a quarter on Home Duties. The defining characteristic of the Sankey diagram is the flows  between the different variables’ values. Accordingly, the flows show that 99 of the 100 people on home duties were women! (Hover your mouse over the flows to see the numbers.)


You can create your own Sankey diagram in Displayr, by adding a data set (Home > Data Set), clicking on the Sankey diagram you can see in the middle of the page, and changing the selected Variables.


Understanding skips and missing data

The next example shows the flow between three questions: cell phone ownership (q1), work status (q2), and occupation (q3). Looking at the right-most set of columns, we can see that around half of people have missing data, shown by a NA, for q3. The Sankey diagram allows us to quickly see where these missing values have come from.


The biggest pattern relates to q2. If people are fulltime workers (q2), they all have an occupation in q3. If they are not working, nearly all have missing data recorded.

Quite a few data integrity problems are also evident. About a third of part-time workers have occupations, suggesting inconsistency in the administration of the survey. A few students have occupations, which also suggests a problem.

Looking at the bottom, we also see that “No” in q1 (phone ownership) leads to missing data in q3.  This seems odd.

We can also see that if people have missing data in either or both of question q1 or q2, they also have missing data in q3. This suggests a data cleaning problem because people with incomplete data on the first three questions in a survey should probably not be included in the main analyses from the survey).


TRY IT OUT
You can easily create these diagrams yourself in Displayr, by adding a data set (Home > Data Set), clicking on the Sankey diagram you can see in the middle of the page, and changing the selected Variables. You can create a new diagram by selecting Insert > Visualization > Sankey Diagram. These are a great tool for understanding the response patterns in your survey data.


Acknowledgements

The Sankey diagrams are created using a modified version of networkD3, created by Kenton Russell (timelyportfolio/networkD3@feature/responsive). networkD3is an HTMLwidget version of Mike Bostock’s D3 Sankey diagram code, which is inspired by Tom Counsell’s Sankey library.

Key Takeaways from 2017 #SXSW

The key topics from the South by Southwest (SXSW) Interactive Festival provided signals for how we can all approach reaching audiences in innovative ways.

By Joe Piteo

It’s 2017 and President Trump is wrapping up his first 2 months in office. Texas, a longstanding and notoriously Republican state, is hosting the most forward-thinking meeting of the minds, South by Southwest (SXSW) Interactive Festival. Some of the smartest people in the world gather to share ideas and set the foundation for the rest of the year’s innovations. The key topics from the event provided signals for how we can all approach reaching audiences in innovative ways. My colleague, Johanna Moonan, and I had the opportunity to attend this inspiring conference and below are a few of our key takeaways:

Diversity: How Can Innovations Power People, Places & Perspectives?

Diversity was a prominent theme throughout the event with many inspiring presentations on how we need more of it in our workplaces. How do we welcome more third-world tech entrepreneurs, support women in leadership and represent marginalized groups in the work that we do? The answer lies in market understanding, mentorship, flexibility and financial support for new and varying voices.

Throughout the week-long event we heard leaders stress that diversity is good business. Businesses need diverse perspectives when creating technologies and communications so that they reflect humanity and resonate with real people. I walked away from SXSW optimistic that diversity not only inspires innovation, but it also just makes good business sense.

The Socialization of Food

Austin is a foodie’s paradise. Whether enjoying a perfect slice of brisket at Franklin Barbecue, salivating over a plate of artfully prepared sushi at Uchi or crushing a bacon-and-maple-syrup doughnut at Gordough’s, the culinary options are endless.

Having attended SXSW over the past 3 years, food finally entered the discussion during the interactive portion. In an “always on” digital world, we crave connection offline. This desire plays out particularly in our cultural obsession with food—part of our cultural glue. As online behavior informs more and more of our real-life choices, food culture acts as one of the biggest influencers of our offline activities.

Many of the food related sessions I attended at SXSW explored the ways online food discovery shapes real world behavior, with an emphasis on the millennial obsession with food and how it influences their offline habits and experiences. To better understand this food revolution and to read a few case studies on how food manufacturers have figured out how to profit from these trends, check out our white paper: The Future of Food: Are You Ready for the Millennials?

Virtual Reality (VR): What will VR Revolutionize Next?

My first encounter with VR was last year at SXSW with Samsung’s roller coaster experience. Fast forward 12-months and VR is table stakes at this year’s conference with numerous tech companies showcasing their credentials. Hearing from some of the most well-known tech gurus, VR headsets will soon become the most popular consumer technology product on the market. However, there are still issues around privacy and security that may stand in the way of this growing phenomenon. VR’s location services, ability to continuously record data, and issues around privacy and security could result in consumer uncertainty and slow adoption.

A panel discussion lead by Facebook’s Oculus, Google, R Institute and the Consumer Technology Association stressed that brands need to address safety and privacy issues impacting VR and ensure that user data is not being misused to build trust among consumers.

To learn more about how VR will change your business going forward download our free white paper: 12 Ways Virtual Reality will Change the World for the Better.

Artificial Intelligence (AI) + Human Intelligence (HI): The Real Future of Intelligence

With the line between what’s a tool and what’s a talent blurring, the future of intelligence is being deeply contested.

There is a barrage of articles citing that up to 47% of Americans are at risk of losing their jobs due to technological advancements and automation – is human intelligence (HI) and artificial intelligence (AI) in direct competition? Can we co-evolve brain and machine learning to lead to unimaginable productivity?

A panel featuring thought leaders in HI and AI set out to answer and energetically debate technology’s role in our lives. The one big theme that the panel agreed on is that the brain is the master of it all. It creates everything. Having listened to this brilliant panel of speakers, I walked away feeling that the convergence of biology and technology will lead to many new beneficial technological paradigms. Technology provides the tools and biology the ability to solve problems, so the two should enjoy a happy marriage.

Social Good at Scale

A number of speakers aimed to debunk the myth that purpose-driven companies cannot also be scalable and profit-driven. Sustainable brands can scale rapidly without compromising their core values. How? By focusing on great stories that resonate; stories that center on people and leverage the right channels.

Surprisingly, these sessions made the task seem simpler than it can sometimes seem, with the core message being that people buy for people. People work for people. This principal can effectively be applied to anything and it is something we practice at Maru/Matchbox.

One example that was pointed to was ANZ Australia Bank’s #EqualFuture campaign by agency TBWA. The campaign brings the financial gender inequality conversation to a personal, everyday level by paying daughters less than sons for chores around the house.

The adorable but thought-provoking campaign videos were shared across ANZ’s social media channels – Facebook, Twitter, LinkedIn and Instagram – with the #EqualFuture hashtag around International Women’s Day and were a big success.

Sweetgreens’ CEO also showed us how his fast, healthy food chain has scaled to over 60 stores since opening just ten years go by tracking ethical standards that people love, not just revenue.

We look forward to next year’s event and we’ll be sure to report back then!

Originally posted here

What’s in Store for International Research?

The UK is the place to be for international research.

By Julie Aebersold, Marketing and Content Executive, Keen as Mustard Marketing

Last month, an article about the 2017 Insight Show in London raised the question of whether London can substantiate its claim as the world’s capital for market research. So after attending the UK’s largest event dedicated to research and insight professionals, and as an American currently resident in Britain, I’d like to provide my thoughts on the state of market research in the UK.

Is London now the world capital for market research? Although statistically the UK is still a smaller market than the US with a market of $7,344 million compared to US’s $19,097 million, the UK is most certainly the place to be for international research. The UK leads the world in global research with 36% of projects completed at an international level, compared to the US where most projects are completed at a domestic level (according to the ESOMAR GMR report). This was shown throughout the two days of the Insight Show, predominantly on the International Stage, where speakers from Dubai, Germany, India, Nigeria, Italy, Belgium and the US flew over to give a unique perspective on cross-cultural research.

There was frequent chatter in the audience about the percentage of international attendees, alongside speakers and multiple cross-border case studies presented on all four content stages. In particular, the International Stage offered insight and guidance for those research companies and clients looking to discover new markets. A presentation by Heineken explained the importance of simultaneously thinking global and acting local when performing research in emerging markets. Despite the challenges there are still many benefits to completing research in emerging markets, such as in Africa and the Middle East. Ultimately, Heineken grew the brand in question by 20% after launch through hard work, dedication, flexibility, global protocols, local field partners, local translation, and most importantly, strong partnerships both client and agency side.

The International Stage closed with a presentation of the 2016 ESOMAR Congress award winning paper, ‘New visions – pushing the frontiers of the eyewear business,’ which gave unique insight into the perceptions of eyewear in India, China and Brazil. The stereotypes associated with eyeglasses in these cultures were rather shocking. Over a quarter of the population in India believe it isn’t appropriate for young women to wear eyeglasses as it makes them unattractive. Other cultures believe glasses are dangerous and lead to drastic health failures or a lack of beauty standards. Due to these stereotypes, only 31% of those who need eyeglasses in these countries actually wear them. And, although India makes up 17% of the world population, it only accounts for a mere 1% of eyewear sales. Strive Insight told us how they helped Italian eyewear company Luxottica understand the barriers behind this resistance in order to determine the solution, which was found to be through luxury brand promotion of world leading brands like Prada and Dolce&Gabbana. Associating eyewear with high-end brands proved to be valuable enough to rewrite the harsh eyewear stereotypes across different cultures.

Another interesting discussion on international market research came during a debate about Brexit and the election of Donald Trump, and how these two political events might have an effect on international research in the UK and US as we know it‎. Moderator Tony Dent from AIMRI stated that the UK has been the leader in international research for the past 12 – 15 years. Overall although the value of sterling has dropped making buying research in the UK cheaper, Brexit can’t make selling research any easier, said Richard Sheldrake. And as a result of the election of President Trump, Jim Whaley of Gazelle Global said he’s aware of many projects being put on hold or moved into the re-planning mode, primarily due to the 17,000 tariffs affected by the election and the renegotiation of international trade. Overall the research industry saw a big loser and a big winner after the two votes. The big loser is traditional online research as we began to question the validity of online polling. On the other hand, the winner was data analytics and behavioural sciences – or big data combined with attitudinal research.

As an outcome of this debate on the US election and Brexit, I think it begs the question of what the future has in store for international research both in the UK and the US. Will it continue to grow? Will Germany take on the mantle of leading international research? As the debate moderator Tony Dent put it, “Unless we pull ourselves together, we may lose this title in the UK.” It will be interesting to see the repercussions (if any) of Brexit on international research in the UK, but is its status as the leader in international projects really in danger?

On top of this international perspective, attendance was up by more than 50 percent year on year at the Insight Show. Could this be an indication of future growth within the market?

If you missed the Insight Show this year, keep an eye out for next year’s event on 7 – 8 March 2018. The 2018 Show is already 50% sold and is increasing in size by 30% to accommodate even more presenters and visitors from across the globe. Find out more by visiting www.insightshow.co.uk

Better Marketing for Market Researchers: Lessons from Insights Marketing Day

Lightspeed's Stefanie Mackenzie recaps her experience at IMD London 2017.

By Stefanie Mackenzie 

I was fortunate enough to attend the Insights Marketing Day event presented by GreenBook; the full day event included eight guest speakers, two panel discussion groups and networking opportunities covering marketing trends and opportunties including:

  • why we should look to move to in-house marketing and PR
  • the most effective ways to improve start and open rates on email campaigns and getting the communication right
  • what marketing automation can do for you
  • what clients really think of marketing
  • the future of social media
  • how people can be influenced and persuaded

Without a doubt my favourite two presenters were The Cat’s Lifejacket: Thought Leadership in a Thoughtless World presented by Tom Ewing (Brainjuicer) and 7 Ways to Nudge Your Company Towards More Conversions by Dan Brotzel (Sticky Content Ltd.)

Dan Brotzel brought the presentation to life, opening our eyes to the simple manipulations and tricks, used by copywriters designing websites, to sway users in a certain direction. The result being higher conversion rates and number of purchases made. It was interesting to see how simple things such as wording, layout and display of options or offers can influence us to think and act differently. The fear of missing out on a good bargain or not having to make a decision/form an opinion is all subtly producing the desired outcomes.

The principles are simple, make it easy on the brain, believable, provide credible options and make it fun/gamified where possible. Outside of the online environment, where exclusivity, social proof, anchoring, offers and discounts can help persuade a user to convert from browsing to purchasing, another effective method is story telling. Telling a story that the purchaser can identify with can help with purchase conversion. For example, if you are deciding between two types of trainers, which would you buy? The cheap one or the slightly more expensive trainer that is the choice of pro-athletes?

Tom Ewing’s presentation started off by paraphrasing Daniel Kahneman, “Thinking is to humans as swimming is to cats: they can do it if they have to, but they try to avoid it.” That set the scene to how most of us make decisions on a daily basis. The presentation talked around the emotional part of the brain, which is used most often when making decisions, to help understand how to plant a seed and grow it.

Here are a few simple principles that can be applied in the work and social environment.

  • repetition, to as wide an audience as possible
  • positive messages, ideas and stories stick better
  • do not try and introduce an entirely new idea, instead package it up with something that’s already familiar. Others will identify with this, recognize the subject matter, can process it faster and already have feelings towards the subject.

Marketing researchers have adapted Mobile First best practices; but are we also looking to benefit from the same engagement, openness and flexibility that marketing initiatives offer? The art of storytelling and making content relatable to others is a skill anyone seeking to influence or persuade should practice and polish, marketers and marketing researchers alike. Whatever we decide to do, in order to succeed, we must be committed, focused, make it simple and be bold…if we can learn from our failures, commit to a purpose and try something different every so often, the end result can only be positive.

Sankey Diagrams: A Better Way to Visualize Decision Trees

Sankey diagrams are perfect for displaying decision trees

By Tim Bock

I used to think that Sankey diagrams were just one of those cool visualizations that look amazing at first, but then don’t turn out to be useful for any real-world problems. I am happy to report I have this wrong. They are perfect for displaying decision trees (e.g., CHART, CHAID).

Perhaps you have not come across Sankey diagrams before? The most famous of them all, created by Charles Joseph Miniard in 1861, shows the ill-fated march of Napoleon to Moscow and back. The tree-branch-like image that goes across the visualization is proportional to the size of Napoleon’s army. Brown represents the advance of Napoleon, with the army shrinking the closer he gets to Moscow. Black shows the retreat from his Pyrrhic victory.

 

1280px-minard


A more typical Sankey diagram

A more typical example is the load energy flow Sankey diagram below, which shows UK energy sources and applications.

Cool? Yes. However, I tried to apply these to a whole host of problems, and I kept getting results completely devoid of insight. Then, in an epiphany, which no doubt means that I have stolen the idea from somebody else (perhaps Kent Russell?), it occurred to me that Sankey diagrams are the perfect solution to an age-old visualization problem: how best to represent data from a classification tree.

You can can inspect the code, and play with the examples used in this post by clicking here.


The standard, difficult-to-read, tree output

The tree below is the standard output from the R tree package. This example shows the predictors of whether or not children’s spines were deformed after surgery. The tree predicts the Presence of Absence of deformation based on three predictors:

  • Start: The number of the topmost vertebra operated upon.
  • Age: The age in months of the patient.
  • Number: The number of vertebrae operated upon.

With a bit of effort you can discern from the tree above that it has identified two segments of children for whom the probability is 50% or more:

  • Start ≤ 12 and Age  ≥ 128 and Numbers ≤ 4
  • Start ≤ 8 and 35 ≤  Age and Number ≥ 5

Compare the meagerness of these findings with what we obtain from the Sankey tree below.


A Sankey tree

The branches are color-coded, on a continuum of blue to red via grey.  Blue means 100% chance of a deformity, grey 50% chance, and red means 0% chance. Thus, we can readily conclude the following things which could not be known from the traditional tree. For example:

  • As most of the visualization is red, most children do not experience a deformity after surgery.
  • The best indicator of deformity is Start. If Start is 12 or less, the chance of a deformity is comparatively low, except for the small segment for whom Start is either vertebrate 13 and 14, and age is from 60 to 157 months. If you hover your mouse pointer over this node (the second from the top, on the far-right), you will see that only 7 children fit this category, and of these 2 (29%) had a deformity.


TRY IT OUT
You can inspect the code, and play with this example using Displayr.


Acknowledgements

The data used in the Sankey tree is kyphosis from the rpart package. The Sankey tree code was a collaborative effort involving Kent Russell, Michael Wang, Justin Yap, and myself, based on a fork of networkD3, which is itself an HTMLwidget version of Mike Bostock’s D3 Sankey diagram code, which is inspired by Tom Counsell’s Sankey library. The load energy flow example is from networkD3, which is a reworking of a Sankey library example, using data from the UK’s Department of Energy & Climate Change.

Originally posted here

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! 

References:

Our Automated Future (The New Yorker): http://www.newyorker.com/magazine/2016/12/19/our-automated-future

Beyond Automation (HBR):

https://hbr.org/2015/06/beyond-automation

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.

TRY IT OUT
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.