Posts in Tom- H- C- Anderson
OdinText Voted #1 Most Innovative Market Research Company in North America and #4 Worldwide!

GRIT Industry Survey Ranks OdinText #1 Most Innovative Market Research Services Provider in North America and #4 Worldwide, Up 32 Places to Become Fastest Rising Company! I am thrilled to announce that the GreenBook Research Industry Trends (GRIT) Report just came out today and the industry has ranked OdinText the #1 most innovative research services provider in North America and the #4 most innovative research company in the world!

GRIT Top 5 Marketing Research Firms 2017

It’s only been one year since we first debuted on the list—and only two years since OdinText launched—and we’ve already jumped 32 spots, making us the fastest rising company on the list.

As a start-up, it’s a huge honor to appear alongside venerable research giants like Nielsen and Ipsos. We’ve come a long way in an incredibly short time, but to be ranked as the most innovative research provider in North America by members of the industry really raises the bar for us.

I’m so very grateful to our users and fans for voting for us, but honestly our research industry clients are the real innovators. We simply provide the tool; you make the magic happen. I’m frequently blown away by the creativity many of you bring to bear using OdinText to unearth insights in ways even I hadn’t thought of.

Thanks also to GreenBook Blog’s Editor-in-Chief and Publisher of GRIT Lenny Murphy for all of his hard work and for calling OdinText “a stand-out example of a technology-enabled solution based on established, applied research principles” and “definitely one to watch!” (Check out our press release for more details.)

Lastly, my congratulations to the other fantastic and innovative research providers named to the GRIT Top 50. All of the companies on this list are worth a close look, and some of the new up-and-comers may be top the list in coming years (check all 50 firms and the full report here).

Thanks again for your support and congratulations to the GRIT Top 50!

@TomHCAnderson

About Tom H. C. Anderson

Tom H. C. Anderson is the founder and managing partner of OdinText, a venture-backed firm based in Stamford, CT whose eponymous, patented SAS platform is used by Fortune 500 companies like Disney, Coca-Cola and Shell Oil to mine insights from complex, unstructured and mixed data. A recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research, Anderson is the recipient of numerous awards for innovation from industry associations such as CASRO, ESOMAR and the ARF. He was named one of the "Four under 40" market research leaders by the American Marketing Association in 2010. He tweets under the handle @tomhcanderson.

Marketing Research Blooper Reveals Lots of Surprises and Two Important Lessons

April Foolishness: What Happens When You Survey People in the Wrong Language?

I’m going to break with convention today and, in lieu of an April Fool’s gag, I’m going to tell you about an actual goof we recently made that yielded some unexpected but interesting results for researchers.

As you know, last week on the blog we highlighted findings from an international, multilingual Text Analytics Poll™ we conducted around culture. This particular poll spanned 10 countries and eight languages, and when we went to field it we accidentally sent the question to our U.S. sample in Portuguese!

Shockingly, in many cases, people STILL took the time to answer our question! How?

First, bear in mind that these Text Analytics Polls™ consist of only one question and it’s open-ended, not multiple choice. The methodology we use intercepts respondents online and requires them to type an answer to our question before they can proceed to content they’re interested in.

Under the circumstances, you might expect someone to simply type “n/a” or “don’t understand” or even some gibberish in order to move on quickly, and indeed we saw plenty of that. But in many cases, people took the time to thoughtfully point out the error, and even with wit.

Verbatim examples [sic]:

“Are you kidding me, an old american who can say ¡adios!”

“Tuesday they serve grilled cheese sandwiches.” “What the heck is that language?”

“No habla espanol”

“i have no idea what that means”

“2 years of Spanish class and I still don't understand”

Others expressed themselves more…colorfully…

“No, I don't speak illegal immigrant.”

“Speak English! I'm switching to News 13 Orlando. They have better coverage than FT.”

Author’s note: I suspect that last quote was from someone who was intercepted while trying to access a Financial Times article. ;-)

While a lot of people clearly assumed our question was written in Spanish, still others took the time to figure out what the language was and even to translate the question!

“I had to use google translate to understand the question.”

“what the heck does this mean i don't speak Portuguese”

But what surprised me most was that a lot of Americans actually answered our question—i.e., they complied with what we had asked—even though it was written in Portuguese. And many of those replies were in Spanish!!!

We caught our mistake quickly enough when we went to machine-translate the responses and we were told that replies to a question in Portuguese were now being translated from English to English, but two important lessons were learned here:

Takeaway One: Had we made this mistake with a multiple-choice instrument, we either might not have caught it until after the analysis or perhaps not at all. Not only would respondents not have been able to tell us that we had made a mistake, but they would’ve had the easy option of just clicking a response at random. And unless those random clicks amounted to a conspicuous pattern in the data, we could’ve potentially taken the data as valid!

Takeaway Two: The notion that people will not take the time to thoughtfully respond to an open-ended question is total bunk. People not only took the time to answer our question in detail when it was correctly served to them in their own language, but they even spared a thought for us when they didn’t understand the language!

I want to emphasize here that if you’re one of those researchers (and I used to be among this group, by the way) who thinks you can’t include an open-ended question in a quantitative instrument, compel the respondent to answer it, and get a meaningful answer to your question, you are not only mistaken but you’re doing yourself and your client a huge disservice.

Take it from this April fool, open-ended questions not only tell you what you didn’t know; they tell you what you didn’t know you didn’t know.

Thanks for reading. I’d love to hear what you think!

@TomHCAnderson

P.S. Find out how much more value an open-ended question can add to your survey using OdinText. Contact us to talk about it.

About Tom H. C. Anderson

Tom H. C. Anderson is the founder and managing partner of OdinText, a venture-backed firm based in Stamford, CT whose patented SAS platform is used by Fortune 500 companies like Disney, Coca-Cola and Shell Oil to mine insights from complex, unstructured and mixed data. A recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research, Anderson is the recipient of numerous awards for innovation from industry associations such as CASRO, ESOMAR and the ARF. He was named one of the "Four under 40" market research leaders by the American Marketing Association in 2010. He tweets under the handle @tomhcanderson.

You Asked for It. Here’s a Chance to Learn More about Our International Culture Poll…

It’s True: You Only Need One Open-Ended Question and Language Doesn’t Matter!

First of all, thank you all so much for the incredible response to this week’s multi-country, multilingual Text Analytics Poll!

I’ve received a flood of email and calls for additional information and I’m always happy to share, so if you have questions or want to geek out with me, please feel free to contact me on our website, LinkedIn or Twitter.

While so many of you thought the findings of our poll were remarkable, I was pleased that the implications for researchers weren’t lost on anyone, notably:

  • A single analyst, speaking English only, can today analyze data in eight different languages,

and

  • In an age of steeply declining response rates, one can gather deep insights on a multi-dimensional subject with just a single question!

This analysis of more than 15, 500 text comments spanning 11 cultures, 10 countries and eight languages really showcased the power and practicality of modern text analytics.

So much so, in fact, that I am delighted to announce that I’ve been invited by the Insights Association to present on this topic at their inaugural analytics conference, NEXT: Advancing Insights Through Innovation & Research, May 9-10 in New York.

For what it’s worth, I really got a lot out of attending the Insights Association’s CEO conference earlier this year (I blogged about it here).

Anyone interested in conducting international, multilingual research on the scale of our poll this week easily, quickly and affordably will not want to miss my presentation. Please feel free to use my speaker code [NEXTTA15] to register at a 15% discount.

If you won’t be able to attend NEXT, or you can’t wait until May to learn more about what OdinText can do for YOU, please request additional info or a demo here.

Thanks again for your readership, support and interest in what we are doing!

@TomHCAnderson

About Tom H. C. Anderson

Tom H. C. Anderson is the founder and managing partner of OdinText, a venture-backed firm based in Stamford, CT whose eponymous, patented SAS platform is used by Fortune 500 companies like Disney, Coca-Cola and Shell Oil to mine insights from complex, unstructured and mixed data. A recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research, Anderson is the recipient of numerous awards for innovation from industry associations such as CASRO, ESOMAR and the ARF. He was named one of the "Four under 40" market research leaders by the American Marketing Association in 2010. He tweets under the handle @tomhcanderson.

 

Text Analytics Explores Whether All Culture Is Becoming American? Part 3
Emotion Speaks Louder than Words Across 11 Cultures, 10 Countries and 8 Languages!

Welcome to Part 3 of our international, multilingual exploration of culture using text analytics!

In Part 1 of this series, I provided a topline analysis of comments from more than 15,500 people spanning 11 cultures in 10 countries and eight languages in response to one question:

“How would you explain <insert country> culture to someone who isn’t at all familiar with it?”

Part 2 took a deeper dive into the key similarities and differences among cultures in our study, revealing how respective members see themselves.

But things got really interesting when OdinText analyzed people’s comments for emotion. Here we have a bit of a surprise. One might expect people’s descriptions of their cultures to be generally positive and for the range of emotions to be fairly narrow, but this was hardly the case. In fact, the emotional analysis revealed much more than just people’s impressions of their own cultures; this exercise tapped into state of mind! You’ll see what I mean in the spider charts for our emotional analysis and verbatim* comments included below.

*Note: Verbatim comments are either translated or [sic]

U.S.A.  (High Positive Sentiment)

Americans are Angry! Twice as Angry as the international average. The Anger is accompanied by high levels of Fear/Anxiety and even Disgust, an emotion we don’t see often outside of food categories and which in this case appears to be related to the recent presidential election.

Joy is also lower than average (and trust is slightly below average), which begs the question: How could we also have a somewhat higher than average overall positive sentiment? The answer lies in a very polarized/divided populous, almost half of whom are bullish and joyful in their descriptions!

[USA Emotions Blue - International Mean Red]

Verbatim examples:

“Expect cordiality and indifference equally, as well as politeness and kindness that may turn to anger and malice. We are all different, and reflections of the world around us. We expect to be treated fairly and bear grudges beyond what is necessary. Racism is a dread poison that has seeped into the veins of our country. While none truly want to take the antidote. There is no standard in our country, people are all different as America breeds individuality.” – FEAR/ANXIETY (and mixed emotion)

“the expression of self in the most obnoxious form one can think of…Fat, dumb and ugly, Loud and obnoxious, Donald Trump - the ugly American” – DISGUST

“I honestly don't know what American culture is. We're such a large country, not at all homogenous. I think we have regional cultures and I would be comfortable explaining southern culture to someone. In the south, most people are neighborly, incredibly polite, and have a strong sense of pride for their region. I would have said a unifying feature of American citizenry was out unified devotion to country, but even that is questionable at times. Overall, I think it depends where in America one is.” – TRUST

“Freedom. Even with all the stuff going on, we still have the best country in the world because we have freedom of speech, choice, and worship…” – JOY

 

UNITED KINGDOM (Average Positive Sentiment)

In the UK, emotion around culture scored pretty average with one notable exception: Fear/Anxiety registered almost twice as high as the international average (although neither was as pronounced as what Americans expressed).

Verbatim examples:

Difficult to say as different parts of Britain have different cultures… difficult to understand Polite hypocritical compassionate confusing people” – FEAR/ANXIETY

“We have a prime minister we didn't elect, England messed up Scotland independence, Brexit is a disaster but we never give up.” – FEAR/ANXIETY

Unsure, confused and variedIt's dead” – FEAR/ANXIETY

[NOTE: comments like “unsure, confused and varied” is a common theme in many of the cultural descriptions, not just for the UK]

AUSTRALIA (Very High Positive Sentiment)

Australians described their culture as laid back, and the emotions they expressed back it up. Their comments contained far less (about half as much) Anger than the international average, lower Sadness and significantly higher Joy. Australian comments also don’t reflect much Surprise, with very few using terms such as “amazing.” Comments are more often relaxed (and often mention this term).

Verbatim examples:

“Its full of kindness, reslectfuly, courageness and happy” - JOY

“limited. But great mateship” – JOY

“Inclusive, relaxed, full of laughter” – JOY

“Laid back, relaxed and able to laugh at ourselves” – JOY

 

BRAZIL (Low Positive Sentiment)

Even though Carnival was a frequently mentioned feature in descriptions of Brazilian culture, life for Brazilians isn’t one big party. Brazilians’ culture comments are significantly more likely than average to contain Anger. They also contain fewer Trust mentions. Most of these sentiments involved frustration with corruption and/or crime. Paradoxically, at the same time, we found low instances of Anticipation and Fear/Anxiety, indicating Brazilians have somewhat resigned themselves or have grown accustomed to these conditions. Moreover, Joy is neither significantly lower nor higher than the international average.

Verbatim examples:

“…Because of the [income] distribution … very Robin Hood, ie acceptable to steal from large companies and also the government. So bank robberies without victims are not perceived negatively by the population, stealing TV signals, tax evasion, political and corruption in general is high, there is strong prejudice against the poor. unqualified civil servants are lazy (stealing their government salaries) High use of pesticides in food, eliminating its nutrients.”  – ANGER (multiple examples)

“A mixture of cultures, and now with evil people in charge making it very difficult to live with the current culture” – ANGER

“good. I believe in Brazil, that one day it will be great” - JOY

 

FRANCE (Average Positive Sentiment)

French comments contain less Surprise than average. In other words, they are less likely than average to use terms like “amazing” and “extraordinary” to describe their culture. This may be because French culture, conceptually, is so familiar and established in the minds of the French, yet the opposing emotion to Surprise—Anticipation—is also not significantly higher than average. French comments describing their culture are also somewhat less likely than average to contain Anger.

Verbatim example:

“We cannot explain French culture. We can only share its ideology, although doing so has evident limitations. I consequently, and personally, see it as wealth gained by mixing cultures: extraordinary traditions gained through the people who have lived here before us. – SURPRISE (rare example)

 

MEXICO (High Positive Sentiment)

Mexicans exhibit a high level of positivity in describing their culture, with their comments containing almost twice the amount of Joy as the international mean. Similarly, their Anger is also almost half that of the ten-country aggregate. Mexicans are also notable for their amount of Surprise—almost three times the average!

Verbatim examples:

“It is very rich and has many very beautiful and amazing things, traditions are super beautiful and have much biodiversity” – JOY and SURPRISE

“As a wonderful and amazing and different gift to what can be seen elsewhere in the world.” – JOY and SURPRISE

“Full of diversity and incredible things that transport you back in time to a magical place” – SURPRISE

“Mexican culture as a set of traditions and art that defined not only the beauty but the feeling of the nation is very particular as we have a very cheerful culture.” – JOY

 

SPAIN (Low Positive Sentiment)

When describing Spanish culture, the Spanish are three times less likely than others to mention issues related to Trust. Surprisingly, they also exhibit almost twice the average level of Sadness. And importantly, we found significantly higher amounts of Anger in Spanish comments about their culture, often related to corruption.

Verbatim Examples:

“For me, the Spanish culture is summed up in the torture of an animal (bull) and very rich food like potato omelette and paella” - ANGER

“bulls, crisis, corruption, political thieves, injustice, cachondeo” – ANGER

“Culture rather low and in many cases ridiculous. Eat and drink like monkeys and hang as much as possible with whoever is around. Idiots, political vermin, thieves and plunderers posing as big cahunas, big wealthy guys, the magnates of oil companies. These guys at the oil companies, they are just clowns but because they work there they become very wealthy, they steal and get a lot of money from the oil companies. They are thieves, corrupt. They become rich. They call this success. Like Rafa Mora or Belen Esteban they are very mediocre people in this country. I am ashamed of these people.” – ANGER and SADNESS

 

GERMANY (Low Positive Sentiment)

Germans have far less positive sentiment in descriptions and about half the proportion of Joy compared to the international average. Like the French, there is also very little Surprise in their comments. It’s not that negative emotions like Anger and Sadness are significantly higher, but rather the lack of positive emotions is significant.

Verbatim Examples:

“Well organized, industrious, intelligent, technically well developed.” – JOY (infrequent example of German Joy)

“Conservative, many rules, precise but also pleasure in little things, family” – JOY (infrequent example of German Joy)

 

JAPAN (Very Low Positive Sentiment)

By “Very Low Positive Sentiment” we do not mean that Japanese sentiment was negative, but that the Japanese sentiment was absent. The Japanese are very reserved and conservative, so it should come as no shock that the degree to which they expressed emotions, generally, was significantly lower than average.

Verbatim Examples:

“Though it is the culture of an island isolated by sea, it is special in its ability to ‘mimic’, and therefore it has developed into a simultaneously unique and multifaceted culture” – JOY

“The origins of the great culture of the Samurai” – JOY

“Japanese culture is special in that it is mellow and refined and is characterized by many gorgeous things. For example, tea ceremony, calligraphy, flower arranging, etc., at first appear to be quite quiet and plain endeavors, however such an impression belies a perfection and refined beauty that exists therein.” – JOY

“Japanese culture is a culture of hospitality and care” – TRUST

 

CANADA-ENGLISH (High Positive Sentiment)

Peace of mind doesn’t appear to be much of a problem for English-speaking Canadians, whose comments reflected significantly low Anger and high Trust. They also exhibited significantly less Fear/Anxiety than the international average, and a modestly higher level of JOY.

Verbatim examples:

“Look great from the outside, is great on the inside. But does have its flaws. Not to mention prejudice, inequality and racism is still embedded in large portions of our culture. Media also does a great job of covering stories that don't matter and are not actually informing.” – JOY (mixed/modest)

“Canadians are usually warm and welcoming people. We are mostly immigrants and understand peoples needs and desires to strive for a better life. We tend to supposrt one another yet respect peoples privacy.” - TRUST

“Like America only with gun control, socialized health care, and French on the packaging. And a much cuter leader.” – TRUST

“Friendly, fair, safe and welcoming” – TRUST

 

CANADA-FRENCH (Lower Positive Sentiment)

The Quebecois’ level of Joy is significantly higher than the international average, but it’s accompanied by equally high levels of Anger and Fear/Anxiety. This combination was unique in our data, perhaps as it represents a strong, well-understood and distinct culture that is defensively positioned within a larger, somewhat opposing culture that sometimes feels threatening. Comments from French Canadians—in contrast to those of the actual French from France—contained quite a lot of emotion. There were also significantly higher levels of Trust, and Sadness scored slightly above average.

Verbatim examples:

“People welcoming, open and proud. rich and diverse culture.” – JOY

“Mixture of French European roots in a North American context. Culture which developed from a difficult kind, hard winter. But a warm and supportive culture, proud of its language on an English-speaking continent.” – JOY

“A welcoming culture, which focuses on French and fights for its rights. Who are past present and future is important. Which is multi-ethnic” – ANGER

“people proud of its language and its history. Quebec is slightly open, yet desperate to preserve its values.” – FEAR/ANXIETY

“We are tolerant but do not humiliate us. Our history is full of situations where we have been crushed but wounds heal slowly. We are proud revelers but we lack confidence in us. We need to assert ourselves in the world and we are receiving from everyone so obviously there is no danger for us.” – FEAR/ANXIETY

What Have We Learned?

First of all, thank you to everyone for the incredible interest you’ve shown and for joining us on this journey!

While I’ll leave the final word on the cultural impact of globalization to anthropologists and others specializing in the study of culture, this surface-level read strongly suggests that we are becoming more alike. Multiculturalism, in particular, has become an important component of cultural identities across many countries and cultures. The data also obviously show that 1. significant differences endure, 2. their dimensions and 3. the degree to which they matter.

Somewhat surprisingly, the hero today may have been the emotional analysis, which told us that cultural identity is not necessarily a static construct, and that how people think about their culture at a given point in time is strongly influenced by current affairs and circumstances, hence the variation in emotions expressed and their intensity.

But what’s really striking about this exercise is that we were able to run these analyses and visualizations and glean all of these insights from data collected from a SINGLE open-ended question.

Look at how much we learned!

Imagine for a moment trying to collect this same information using a multiple-choice instrument. You’d need more than one, and I still don’t think it would be possible to achieve the same insights.

Then there’s the scale to consider. We analyzed responses from more than 15,500 people in their own words.

Lastly, we accomplished this using OdinText across 11 cultures, 10 countries and eight languages in fewer than two hours! (It actually took longer to prepare this blog post than it did to translate and analyze the data!)

In summary, research innovation today is generally assessed in three questions:

  • Is it better? Yes! This approach yielded insight that would have been impossible to achieve with a conventional, multiple-choice survey.
  • Is it faster? Yes! Manual coding alone would’ve taken days or weeks. OdinText did it in fewer than two hours.
  • Is it cheaper? Yes! This international project was affordable enough to conduct on a whim.

Whatever the size of your organization or your resources, this project demonstrates that you can now conduct, translate and analyze a multinational, multilingual study among key consumers in key markets and capture meaningful insights quickly, affordably and easily without even getting up from your desk using OdinText.

Contact us here to talk about it.

Thanks for reading. I’d love to hear what you think!

@TomHCAnderson (@OdinText)

About Tom H. C. Anderson

Tom H. C. Anderson is the founder and managing partner of OdinText, a venture-backed firm based in Stamford, CT whose eponymous, patented SAS platform is used by Fortune 500 companies like Disney, Coca-Cola and Shell Oil to mine insights from complex, unstructured and mixed data. A recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research, Anderson is the recipient of numerous awards for innovation from industry associations such as CASRO, ESOMAR and the ARF. He was named one of the "Four under 40" market research leaders by the American Marketing Association in 2010. He tweets under the handle @tomhcanderson.

Text Analytics Identifies Globalization Impact on Culture

International Text Analytics Poll™ Explores 11 Cultures in 10 Countries and 8 Languages! [Part I]

When pundits declare that the western world is  now in the throes of a globalization “backlash,” they’re generally referring to the reversal of decades of economic and trade policy, things like Brexit.

But what of other concerns typically associated with globalization? What about culture?

Specifically, there are those who argue that globalization will mean the end of cultures, that the various cultures of the world will over time dilute and blend until there is ultimately just one global melting pot culture.

They may be right.

When we think about culture, it’s often in terms of food, music, customs, etc., but it turns out that when you ask people in countries around the world to describe their own culture in their own words, one nearly universal and unexpected attribute rises to the top: diversity/multiculturalism.

In fact, multiculturalism/diversity was one of the primary and most frequently mentioned attributes used by over 15,500 people to describe 11 different cultures across 10 countries and eight languages!

Text Analytics on a Massive, Multilingual International Scale

Last week on this blog, we published the results of a Text Analytics Poll™ for the favorite movie of all time across six countries and five languages. The project generated a flood of inquiries.

Since everyone is so interested in what can be accomplished on an international scale, we increased the scope of this project significantly.

This time, we asked more than 15,500 people (at least n=1,500 per country) in 10 countries and eight languages the following:

“How would you explain <insert country> culture to someone who isn’t at all familiar with it?”

Then we ran their comments through OdinText, which identified the top 200 cultural markers or features from more than 15,500 text comments and also analyzed those comments for significant patterns of emotion.

How We Translated AND Analyzed the Data (In Less Than Two Hours)

Author’s note: If you’re not interested in methodology, please feel free to skip ahead to the results down below!

Many of you contacted us asking for more details last week, so I’ve provided some additional nuts and bolts here…

Step 1: Data Prep (Translation)

I usually limit total analytical time for any of these Text Analytics Poll™ projects to fewer than two hours. I admit that’s going to be a challenge today, as I’m looking at more than 15,500 comments across 11 cultures from 10 countries in eight languages.

The first challenge is translation. I happen to speak a few languages in addition to English, but in this case I’m faced with seven languages that I don’t understand well enough to analyze. If I did understand each of the languages, or were working with analysts who did, we could easily conduct the analysis in OdinText in the native form.

I’ll point out that while some corporations claim to be “global” in everything they do, in reality there is never enough language fluency at corporate to handle this type of analysis, so analyses are typically divvied up and entrusted to local divisions—a time-consuming and imperfect task, especially when the goal in this case is to make head-to-head comparisons across these countries.

Therefore translation is necessary. While less precise than human translation, machine translation lends itself quite well to a project like this and is more than sufficient for OdinText to identify patterns and even to determine which quotes should be of interest. Nothing has a better ROI. Case in point, it took two minutes to translate the data. For those keeping track, I’m at

Above we have an example of machine translated raw data vs. the original French from the multi-country movie analysis I conducted last week. In the case above I’m looking at all mentions of “La Ligne Verte,” a title OdinText identified as appearing frequently among comments from French respondents. I don’t speak French, so I prefer to work with machine translated data on the left, which translated “La Ligne Verte” literally to “The Green Line” –the French title for the U.S. movie “The Green Mile.”

Step 2: Topic Identification

Using the top-down/bottom-up approach we teach in OdinText training and which we’ve blogged about here before, we identify 200 or so topics/features for analysis. This is a semi-supervised approach, and so a human is involved.

Given this somewhat larger multi-country data set, I allowed about 45 minutes for this task, so we’re at 

Step 3: Artificial Intelligence and Structuring the Analysis

Structuring the analysis is the most important and the most difficult part of any project, especially an exploratory mission where you don’t know what you are looking for at the outset.

You may be surprised to know that artificial intelligence and advanced machine learning algorithms can be a lot less useful than one might think. They have a tendency to identify the obvious—the attribute/topic “tradition” in this case—or, in cases, the unexplainable. For instance, terms like “French,” “American,” “Japanese,” “Spanish,” etc., came up in responses to our question. These are, of course, very useful if you’re building an algorithm to predict where comments originate, for example, but they aren’t terribly illuminating for us here.

Examples of other topics auto identified as ‘of interest’ by our AI include “friendliness,” “relaxed/laid back,” “freedom,” and “equality fraternity liberty.” (You can probably guess where that last one came from.) Some of these other, less expected ones warrant a closer look and will be included in the analysis.

We could move right into an exhaustive analysis of each country, but I’m looking to quickly find any interesting patterns in this data, so I elect to use a quick visualization first.

Cultural Differences and Similarities Vizualized

Cultural Differences and Similarities Vizualized (A Few Key Descriptive Dimensions Added)

These visualizations (above) plot cultures that were described in more similar terms by people closer together and those that were described more differently further apart, yielding some interesting patterns. The USA, UK, Brazil, France and even Spain look quite similar. Two countries—Germany and Japan—cluster slightly away from this main bunch, but very close to each other. Then there are those that appear to be most dissimilar from the rest—Mexico, French- and English-speaking Canada, respectively, and Australia.

To my earlier question about whether or not globalization is having a homogenizing effect on cultures, it would appear so at a glance. We’ve noted that several countries cluster closely around the U.S. But look again—the U.S. appears to occupy the center of the cultural universe here! That’s no coincidence, I suspect, as U.S. culture could in many ways be considered the “melting pot” model and, as we saw last week, culture is a major U.S. export.

Analytical time to review multiple visualizations and decide that this is a repeating pattern was 10 minutes. Total analytical time =

Given that we have a full hour left (remember I did not want to spend more than two hours on this analysis), as a next step we conducted a little bottom-up work to look at what makes each country unique from the international aggregate/total and to see whether the pattern in the visualization makes sense.

Example: Why do Germany and Japan look so similar to OdinText?

A glance at the two charts below shows significant differences between how the Japanese and Germans describe their cultures. For instance, the Japanese were 11 times more likely than Germans to say their culture was something that needed to be experienced in order to be understood, and they were four times more likely than Germans to mention their history. They were also 14 times less likely to mention certain places of interest and three times more likely than Germans to mention food.

In contrast, Germans were 27 times more likely to mention beer and eight times more likely to describe their culture as rule-abiding and orderly. (Of course, this does not mean that Japanese culture is any less rule-abiding or orderly; rather, it suggests that for the Japanese these are not defining cultural characteristics.)

Respondents from both countries were more likely than average to mention language, tradition, and politeness, BUT the similarities between these two cultures actually lie primarily in the extent to which they both differ from the other cultures sampled, notably by how infrequently certain features mentioned by people from other cultures appeared in comments from German and Japanese respondents.Total Analytical Time =

This concludes Part 1 of our cultural safari. In Part 2 tomorrow we’ll take a deeper dive into each of the 11 cultures in our study individually, exploring how their members define themselves and the extent to which key cultural drivers differ from or are similar to the international aggregrate. Stay tuned!

Tomorrow: Part II – Key Cultural Drivers in Their Own Words

@TomHCAnderson - @OdinText

PS. Have questions about today's post? Feel free to post a comment or request more info here.

About Tom H. C. Anderson

Tom H. C. Anderson is the founder and managing partner of OdinText, a venture-backed firm based in Stamford, CT whose eponymous, patented SAS platform is used by Fortune 500 companies like Disney, Coca-Cola and Shell Oil to mine insights from complex, unstructured and mixed data. A recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research, Anderson is the recipient of numerous awards for innovation from industry associations such as CASRO, ESOMAR and the ARF. He was named one of the "Four under 40" market research leaders by the American Marketing Association in 2010. He he tweets under the handle @tomhcanderson.

 

Mush Aside, Top Things that Bug Us about Our Sweethearts

Valentine’s Day Text Analytics Poll™ Uncovers What People Really Think about their Special Someones Ah, February 14th—the one day of the year when anything you want to eat comes shaped in a heart!

Yes, love is in the air today, friends. We show it with cards and candy, roses and Build-a-Bears, theater tickets, dinner reservations and sexy unmentionables…

On Valentine’s Day we express our true feelings for that special someone!

Well, maybe we profess our love, at least. But what do we hold back?

The truth is, anyone who’s been in one can tell you that relationships aren’t all sweet nothings and love songs. (Except mine. My wife is a reader. I love you, honey! You’re perfect!)

So, at the risk of cynicism on the ultimate Hallmark holiday, we decided to get a little real here with some help from OdinText. We asked each of three randomly-selected gen pop samples of 1,500 a question designed to give us the good, bad or the ugly about their sweethearts—stuff you might not find in a card store.

What Irks Me about You

I love being married. It's so great to find one special person you want to annoy for the rest of your life. — Rita Rudner 

We asked 1,500 Americans to reply to the following question in their own words in a comment box:

“What do you like least about your significant other?”

Omitting a significant number of liars and honeymooners who said “nothing,” here are the responses after running all 1,500 comments through OdinText…

Ok, who did not predict “hair” would be the number three response? Especially against common relationship problems like money/financial issues and lack of communication (which came out relatively low)?

What I Bring to this Relationship

My friends tell me I have an intimacy problem. But they don't really know me.  — Garry Shandling

Valentine’s Day is all about appreciating the way our sweethearts enrich our lives, but we all like to think we have something special to offer in return.

We asked people one of two questions:

  1. “How would your significant other describe you to a good friend?”

Or

  1. “How would you describe your significant other to a good friend?”

Here’s what they told us, with responses to question 1 in white and question 2 in red:

As you can see from the results, it appears a lot of us consider our sweethearts to be our best friends and we value them for their love and support. But we’re twice as likely to describe ourselves as being the funny one in the relationship (and the crazy one, too).

Life is Lonely without You

If we take matrimony at its lowest, we regard it as a sort of friendship recognized by the police. —Robert Louis Stevenson

They say distance makes the heart grow fonder, so we asked people this:

“If you were without your significant other for an entire week, what things would you miss the most?”

And there you have it. I think the responses to this question show overwhelmingly why our sweethearts put up with so much from us.

Wishing you and your special someone a lovely Valentine’s Day!

And for you single folks out there, take heart: You’re not only saving money today; you’re not shackled to a snoring, messy, flatulent sweetheart with a bad attitude.

@TomHCanderson

PS. Could a Text Analytics Poll™ answer your burning marketing questions?  Contact us to see if a single-question open-ended survey makes sense for you! Using OdinText is easy.

About Tom H. C. Anderson

Tom H. C. Anderson is the founder and managing partner of OdinText, a venture-backed firm based in Stamford, CT whose eponymous, patented SAS platform is used by Fortune 500 companies like Disney, Coca-Cola and Shell Oil to mine insights from complex, unstructured and mixed data. A recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research, Anderson is the recipient of numerous awards for innovation from industry associations such as CASRO, ESOMAR and the ARF. He was named one of the "Four under 40" market research leaders by the American Marketing Association in 2010. He tweets under the handle @tomhcanderson.

Text Analytics Picks the 10 Strongest Super Bowls Ads

New Text Analytics PollTM Shows Which Super Bowl Ads Really Performed Best Well, it’s been five days since the Super Bowl, and pretty much everyone has cranked out a “definitive” best-and-worst ad list or some sort of top 10 ranking. And frankly, I think a lot of them are based on the wrong metrics.

Without a doubt, what makes a Super Bowl ad great differs from what makes a “normal” ad great. So what exactly qualifies a Super Bowl ad as a success or failure?

We could look at purchase consideration or intent, likelihood to recommend, or any of a dozen or more other popular advertising metrics, but that’s not what Super Bowl advertising effectiveness is really about.

Word of mouth has always been a big one and nowadays that means social media buzz. But does buzz equate to success? Ask the folks at Budweiser or Lumber 84.

Bottom line: This is a very expensive reach buy, first and foremost, and it’s a branding exercise.  I’ve shelled out $5 million (plus production costs) for 30 seconds to make a lasting and largely unconscious impression on the world’s biggest television audience.

As far as I’m concerned there need only be three objectives then:

  1. I want you to remember the ad;
  2. I want you to remember it’s my ad;
  3. I want you to feel positive about it.

Whether or not my ad met all of these criteria can be answered with one single unstructured question in a Text Analytics PollTM and quickly be analyzed by NLP software like OdinText with more valid results than any multiple-choice instrument.

Why a Text Analytics PollTM ?

Using a Likert scale to assess recall or awareness will only provide an aided response; I can’t ask you about an ad or brand without mentioning it. So I don’t really know if the ad was actually that memorable. And while a quantitative instrument can tell me whether or not you liked or disliked an ad, it also won’t tell me why.

Conversely, I can get the “why” from traditional qualitative tools like focus groups or IDIs, but not only would those insights be time-consuming, labor-intensive and expensive to gather, they wouldn’t be quantified.

But if I ask you to just tell me what you remember in your own words using a comment box, I can find out which ad was truly memorable, ascertain whether or not you truly recall the brand, determine whether the ad left a positive or negative impression on you and get a much deeper understanding of why. I can achieve all of this using one open-ended question. And with text analytics software like OdinText, I can quantify these results.

Which Super Bowl Ads Did “Best”?

We asked a random, gen pop sample of n=4,535 people (statistics with a confidence interval of +/- 1.46) one simple question:

“What Super Bowl ad stood out the most to you and why?”

Author’s note: We ran this survey Sunday night and closed it Monday night. We were originally planning to post the results on Tuesday, but decided to postpone it in favor of sharing what we felt were more pressing results from a Text Analytics PollTM we had conducted around President Trump’s immigration ban.

As you can see in the table below, this one simple question told us everything we needed to know…

Top 10 Super Bowl Ads: Memorability of Ad & Brand, and Degree of Positive Sentiment

The following ads are ranked according to memorability—respondents’ unaided recall of both the ad and the brand—accompanied by positive/negative sentiment breakout (blue for positive, orange for negative) in reverse order. Author’s note: The verbatim examples included here are [sic]

#10 Pepsi

 

 

As the sponsor of the Lady Gaga halftime show, one might expect Pepsi to do very well, but Lady Gaga may have literally stolen the show from Pepsi! In fact, the halftime show was actually mentioned more often in the comment data than Pepsi, and the two were infrequently mentioned together. Meanwhile, Pepsi’s ads were relatively unmemorable and much of the awareness we saw was in the form of negative sentiment.

Author’s note: Interestingly, social media monitoring services like Sprinkler had reported Pepsi “owned” the Super Bowl ad chatter on social media. I’ll say it not for the first time: social media (aka Twitter) can be full of spam often generated by agents of the brand.

 

#9 Buick

This is a case where the star of the ad, Cam Newton, didn’t eclipse the sponsor. People liked the pro footballer playing with the little kids and the tie-in to football seemed to work well. We saw this with Tom Brady in a different ad, too.

Buick with Cam Newton, cute and funny

I like the Buick ad because it let a bunch of kids play football with Cam Newton.

So what’s not to like, you say? How did it garner even a 13% unfavorable rating?

cam newton pushed little kids

The buick commercial, the concept was boring

Buick, it was not even funny

 

#8 Skittles

 

Skittles, made my kids laugh

The Skittles ad because it was funny and sort of relate-able. It shows how far one is willing to do something for someone.

Humor generally always does well, so what’s not to like?

The skittles commercial it made no sense

skittles, stupid with the burglar

Skittles, it was creepy. And what was with the gopher at the end?

 

#7 T-Mobile

Popular and a little risqué… [Note Also, Sprint Ads were often mis-remembered as T-Mobile, perhaps Halo effect and a reason Sprint didn't make the Top 10...]

The T-Mobile ‘fake your own death to escape Verizon bill’ it was very funny, and got its point across very well

T-mobile. very funny parodying 50 shades of gray to Verizon ‘screwing its customers!’

T-Mobile with Justin. Maybe because I'm a T-Mobile subscriber? Or Justin Bieber was dressed so well in a suit, and then he starts dancing and jumping like a maniac. The contrast makes it funny.

T mobile add where guy faking death. Most memorable. Light hearted. Got point across.

BUT not everyone is a Belieber

The t mobile justin biber. It was kinda lame

T-Mobile w/Justin Bieber - inane, juvenile, bordering on insulting

T-Mobile Unlimited Moves. It wasnt funny and Justin Bieber looked like the six flags guy.

T-Mobile, awkward dancing as they attempted to appeal to teenagers

 

#6  Audi

Audi took on gender equality with an appeal to fathers of daughters. The resulting ad was memorable in 6th place:

The audi one because it was meaningful

Audi - moving story and loved the message of what to tell daughters!

Audi. I have a daughter

Audi - moving story and loved the message of what to tell daughters!

However, not everyone liked mixing politics or social issues with their football (as we will see again for some of the other top ads):

AUDI and 84 Lumber. Keep your political message out of my entertainment

Least liked Audi because it was a liberal ad

 

#5 Coca-Cola

Ironically, even without sponsoring the halftime show, Coca-Cola beat Pepsi.

The coke commercial was really meaningful and symbolic

Coca Cola because of the embracing of diversity

Coca Cola True portrayal of America's diversity

The coke ad. I liked the pro-refugee stance.

coke america is beautiful commercial, very admirable

Coca Cola Commercial because it's all about being connected

Coke , showing we are still interconnected regardless of ethnicity

I liked the coca cola ad at the very beginning. I've seen it before but I think the message is so powerful and the commercial is beautifully executed.

But the ad was not received well by many, likely in part due to the politically-charged climate. Several advertisers ran messages that struck people as being politically biased or advancing a political agenda—something not everyone cared for…

Didn’t appreciate Coca Cola trying to make a political statement

I didn't like the Coke commercial. They showed it two years ago and the year before.

Google and Coke because they shoved their political views into my face.

 

#4 Mr. Clean

Who would have predicted MR. Clean for fourth place? The brand made good use of humor, and it stood out from the other ads by targeting women (but appealed to members of both genders).

Mr clean, it was funny - Female

Mr. Clean because I'm bald -  Male

Mr. Clean, relatable, memorable, hilarious. -Female

The Mr. Clean commercial, it was funny, tasty, and got the point across. Incredibly well done ad. – Male

Mr clean because my wife pointed it out – Male

mr clean because it relates to family, and parents that stay at home and clean. it was family friendly - Female

mr clean everything else sucked – Gender Not Specified

Some men though didn’t see the humor and or get the point, calling it “weird”. It wasn’t really that they disliked it intensely; they just felt it wasn’t for them.

 

#3 Lumber 84

Not many had heard of this company before the Super Bowl, but I’ll bet you know who they are now. The third most memorable ad, yes, but more than half of those who remembered it had nothing nice to say!

First, among those who liked the ad:

It was so touching

Audi, 84 lumber, both showed compassionate ads

84 lumber - it's the only one I can remember

84 Lumber - Showed what America is actually supposed to be.

they were obviously trying to get across a non- traditional message that didn't seem to be advertising. Also it was beautifully and compellingly produced.

Lumber 84 showed that not everyone wants a wall and that we understand there is power in diversity.

But the execution confused people and whatever the intention, the sponsor stepped into a controversy. Here the emotional sentiment (particularly anger) ran high and was prevalent in comments like “romanticized crime” and “forced politics”:

The Journey 84 ad, it just left me confused

The 84 lumber commercial. It didn't make sense

it was about illegals sneaking into America, i won't be shopping their anymore

Lumber 84 because it was politically offensive

84 lumber, clearly a political statement and uncalled for

84 lumber, Made no sense, Not going to look something up

#2 Kia

Ironically, with other brands going serious and political, Kia poked some fun with help from Melissa McCarthy. Kia’s investment in humor and McCarthy paid off in a big way, scoring the highest combination of memorability and positive sentiment, although to an extent the comedian eclipsed the brand.

Loved melissa McCarthy because she is hilarious and i love her.

Kia it was funny and not somber like most the others

The Buick one, the world of tanks ones and the eco friendly Melissa one because they were the funniest

The one with Melissa McCarthy because it made me laugh

KIA becuase it didn't feel like it was trying to sell me anything, just entertain with brand placement

 

#1 Budweiser

Yes, Budweiser took first place in terms of recall, but the perception of a political bent cost the king of beers. The ad, which featured one of the founders struggling as an immigrant, was apparently in the works before the Trump Immigration Order controversy. But even if that was the case, by choosing to air it Budweiser took a risk.

Likes:

I liked the Budweiser commercial reminded us all that not all white Europeans were always welcome in the US.

Budweiser. I love the reminder that we are all immigrants

Budweiser immigration. Shows Trump is an idiot, but we all know that

The Budweiser ad about how they were founded by an immigrant, because it was actually relevant to their company history

Budweiser, it was a beautiful immigrant's tale. Not overtly political

The Budweiser commercial because it shows what a true immigrant had to go through and even though many people thought it was to take a shot at Trump's travel ban it had nothing to do with it.

Dislikes:

Budweiser. Too liberal.

budweiser, too pro immigration

bud, adolfus was not ILLEGAL !

The Budweiser ad about immigration. Too political.

Budweiser, they shot themselves in the foot being that the man who immigrated into the U.S. did so legally.

Budweiser. Football/all sports should not involve politics. We need to relax sometimes.

So…who won?

Isn’t it obvious? I’d say Kia. Sure, Budweiser scored higher unaided awareness, but a significant portion of that was negative.

But it's all in the data, what do you think?

A Final Note on Text Analytics PollsTM 

It occurred to me in writing this post that about 11 years ago almost to the day I predicted that the survey of the future would be a one-question open-end, because that’s all people really want to tell you, and that’s all you’ll need.

Turns out I may have been right.

This week, we’ve shared results from three such surveys, a technique we've dubbed “Text Analytics PollTM .

These incredibly short, one-question polls allow us to field quickly to large samples with minimal burden on the respondent. And text analysis software such as OdinText enables us to quantify these huge quantities of comments.

But the real advantage to using text analytics polls is that the responses tell us so much more than whether someone agrees/disagrees or likes/dislikes. Using text analytics we can uncover why from respondents in their own words.

Thanks again for reading!

@TomHCAnderson @OdinText

Could a text analytics poll answer your burning marketing questions?  Contact us to see if a single-question open-ended survey makes sense for you!

 

About Tom H. C. Anderson

Tom H. C. Anderson is the founder and managing partner of OdinText, a venture-backed firm based in Stamford, CT whose eponymous, patented SAS platform is used by Fortune 500 companies like Disney, Coca-Cola and Shell Oil to mine insights from complex, unstructured and mixed data. A recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research, Anderson is the recipient of numerous awards for innovation from industry associations such as CASRO, ESOMAR and the ARF. He was named one of the "Four under 40" market research leaders by the American Marketing Association in 2010. He  tweets under the handle @tomhcanderson.

 

 

 

Poll: What Other Countries Think of Trump’s Immigration Order

Text Analytics PollTM Shows Australians, Brits, and Canadians  Angry About Executive Order Temporarily Barring Refugee (Part II of II)In my previous post, we compared text analysis of results from an open-ended survey instrument with a conventional Likert-scale rating poll to assess where 3,000 Americans really stand on President Trump’s controversial executive order temporarily barring refugees and people from seven predominately-Muslim countries from entering the U.S.

Today, we’re going to share results from an identical international study that asked approx. 9,000 people—3,000 people from each of three other countries—what they think about the U.S. immigration moratorium ordered by President Trump.

But first, a quick recap…

As I noted in the previous post, polling on this issue has been pretty consistent insomuch as Americans are closely divided in support/opposition, but the majority position flips depending on the poll. Consequently, the accuracy of polling has again been called into question by pundits on both sides of the issue.

By fielding the same question first in a multiple-choice response format and a second time providing only a text comment box for responses, and then comparing results, we were able to not only replicate the results of the former but gain a much deeper understanding of where Americans really stand on this issue.

Text analysis confirmed a much divided America with those opposing the ban just slightly outnumbering (<3%) those who support the order (42% vs 39%). Almost 20% of respondents had no opinion or were ambivalent on this issue.

Bear in mind that text analysis software such as OdinText enables us to process and quantify huge quantities of comments (in this case, more than 1500 replies from respondents using their own words) in order to arrive at the same percentages that one would get from a conventional multiple-choice survey.

But the real advantage to using an open-ended response format (versus a multiple-choice) to gauge opinion on an issue like this is that the responses also tell us so much more than whether someone agrees/disagrees or likes/dislikes. Using text analytics we uncovered people’s reasoning, the extent to which they are emotionally invested in the issue, and why.

Today we will be looking a little further into this topic with data from three additional countries: Australia, Canada and the UK.

A note about multi-lingual text analysis and the countries selected for this project…

Different software platforms handle different languages with various degrees of proficiency. OdinText analyzes most European languages quite well; however, analysis of Dutch, German, Spanish or Swedish text requires proficiency in said language by the analyst. (Of course, translated results, including and especially machine-translated results, work very well with text analytics.)

Not inconspicuously, each of the countries represented in our analysis here has an English-speaking population. But this was not the primary reason that we chose them; each of these countries has frequently been mentioned in news coverage related to the immigration ban: The UK because of Brexit, Australia because of a leaked telephone call between President Trump and its Prime Minister, and Canada due to its shared border and its Prime Minister’s comments on welcoming refugees affected by the immigration moratorium.

Like our previous U.S. population survey, we used a nationally-representative sample of n=3000 for each of these countries.

Opposition Highest in Canada, Lowest in the UK

It probably does not come as a surprise to anyone who’s been following this issue in the media that citizens outside of America are less likely to approve of President Trump’s immigration moratorium.

I had honestly expected Australians to be the most strongly opposed to the order in light of the highly-publicized and problematic telephone call transcript leaked last week between President Trump and the Australian Prime Minister (which, coincidentally, involved a refugee agreement). But interestingly, people from our close ally and neighbor to the north, Canada, were most strongly opposed to the executive order (67%). The UK had proportionately fewer opposing the ban than Australia (56% vs. 60%), but the numbers of people opposed to the policy in both countries significantly lagged the Canadians. Emotions Run High Abroad Deriving emotions from text is an interesting and effective measure for understanding people’s opinions and preferences (and more useful than the “sentiment” metrics often discussed in text analytics and, particularly, in social media monitoring circles).

The chart below features OdinText’s emotional analysis of comments for each of the four countries across what most psychologists agree constitute the eight major emotion categories:

We can see that while the single highest emotion in American comments is joy/happiness, the highest emotion in the other three countries is anger. Canadians are angriest. People in the UK and Australians exhibit somewhat greater sadness and disgust in their comments. Notably, disgust is an emotion that we typically only see rarely in food categories. Here it takes the form of vehement rejection with terms such as “sickened,” “revolting,” “vile,” and, very often, “disgusted.” It is also worth noting that in cases, people directed their displeasure at President Trump, personally.

Examples:

"Trump is a xenophobic, delusional, and narcissistic danger to the world." – Canadian (anger) “Most unhappy - this will worsen relationships between Muslims and Christians.” – Australian (sadness) "It's disgusting. You can't blame a whole race for the acts of some extremists! How many white people have shot up schools and such? Isn't that an act of terror? Ban guns instead. He's a vile little man.” –Australian (disgust)

UK comments contain the highest levels of fear/anxiety:

"I am outraged. A despicable act of racism and a real worry for what political moves may happen next." – UK (fear/anxiety)

That said, it is also important to point out that there is a sizeable group in each country who express soaring agreement to the level of joy:

“Great move! He should stop all people that promote beating of women” – Australian (joy) “Sounds bloody good would be ok for Australia too!” – Australian (joy) “EXCELLENT. Good to see a politician stick by his word” – UK (joy) “About time, I feel like it's a great idea, the United States needs to help their own people before others. If there is an ongoing war members of that country should not be allowed to migrate as the disease will spread.” – Canadian (joy)

Majority of Canadians Willing to Take Refugee Overflow Given Canada’s proximity to the U.S., and since people from Canada were the most strongly opposed to President Trump’s executive order, this raised the question of whether Canadians would then support a measure to absorb refugees that would be denied entrance to the U.S., as Prime Minister Justin Trudeau appears to support.

(Note: In a Jan. 31 late-night emergency debate, the Canadian Parliament did not increase its refugee cap of 25,000.)

 

A solid majority of Canadians would support such an action, although it’s worth noting that there is a significant difference between the numbers of Canadians who oppose the U.S. immigration moratorium (67%) and the number who indicated they would be willing to admit the refugees affected by the policy.

When asked a follow-up question on whether “Canada should accept all the refugees which are turned away by USA's Trump EO 13769,” only 45% of Canadians agreed with such a measure, 33% disagreed and 22% said they were not sure.

Final Thoughts: How This Differs from Other Polls Both the U.S. and the international versions of this study differ significantly from any other polls on this subject currently circulating in the media because they required respondents to answer the question in a text comment box in their own words, instead of just selecting from options on an “agree/disagree” Likert scale.

As a result, we were able to not only quantify support and opposition around this controversial subject, but also to gauge respondents’ emotional stake in the matter and to better understand the “why” underlying their positions.

While text analysis allows us to treat qualitative/unstructured data quantitatively, it’s important to remember that including a few quotes in any analysis can help profile and tell a richer story about your data and analysis.

We also used a substantially larger population sample for each of the countries surveyed than any of the conventional polls I’ve seen cited in the media. Because of our triangulated approach and the size of the sample, these findings are in my opinion the most accurate numbers currently available on this subject.

I welcome your thoughts!

@TomHCAnderson - @OdinText

About Tom H. C. Anderson Tom H. C. Anderson is the founder and managing partner of OdinText, a venture-backed firm based in Stamford, CT whose eponymous, patented SAS platform is used by Fortune 500 companies like Disney, Coca-Cola and Shell Oil to mine insights from complex, unstructured and mixed data. A recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research, Anderson is the recipient of numerous awards for innovation from industry associations such as CASRO, ESOMAR and the ARF. He was named one of the "Four under 40" market research leaders by the American Marketing Association in 2010. He tweets under the handle @tomhcanderson.

65 CEOs Share Thoughts on Insights

Insight Association’s Inaugural CEO Summit: Future Tied to Collaboration and Technology Writing this at the Miami Airport as I’ve just finished up a great 3 day meeting of the minds at the new Insights Association’s first official event, the Marketing Research CEO Summit.

Though this event was formerly part of the Marketing Research Association (MRA), after the merger between The MRA and the Council for American Survey Research Organizations (CASRO), it is now is part of the greater and brand new Insights Association. This is also the reason I chose to attend the event for the first time this year. I like many others are eager for positive change in our industry and optimistically welcome new initiatives (as I mentioned in a post on their founding earlier this month).

Steve Schlesinger, CEO of Schlesinger Associates and Merrill Dubrow of M/A/R/C Research did a great job putting together and hosting the event.

While the obvious benefit of any event like this is the attendees and not the speakers, we had some other interesting and well respected client guests including Walmart’s Urvi Bhandari, Merck’s Lisa Courtade, Electrolux’s Brett Townsend and Dhan Kashyap from Humana. Their very candid evaluations of how well the industry is delivering *Hint* it’s not even close to as well as we think, was worth the cost of attendance.

Getting back to the attendees though, Market researchers as a breed are a cautious bunch and CEO’s in any industry are likely going to be “Alpha’s”. Quickly gaining trust and enabling sharing among this audience of would be competitors is not an easy task. Partly this was made possible via a fun case study competition sponsored by La Quinta CEO Keith Cline who also spoke at the event.

Another interesting aspect of the event was the Hot Seat interviews wherein a handful of the CEO’s in attendance were asked a series of tough and sometimes semi personal questions. I was one of those selected for this impromptu exercise and was asked what I thought about various aspects of the future of marketing research including digital/social (which I like to separate from other text analytics), and of course the topic of machine learning/AI which seems to be on everyone’s mind. For that reason I’ve decided to do a short blog post on AI and Machine learning later this week.

What I’d like to end this post with though is in re-answering one of the questions which I think Merrill indirectly asked me, and which I was asked by a couple of other attendees. I think the question is also related to the future of research. Do you think of yourself as a Marketing Research co. CEO or a software CEO? [Prior to founding OdinText Inc. in 2015 I ran boutique research firm Anderson Analytics for 10 years]

I admit it’s a tricky question, and obviously if I didn’t consider myself at least in part a marketing research CEO I wouldn’t have attended. Yet many of our software users definitely aren’t market researchers.

So here goes, I think we as an industry have an important skill set and understanding of our clients that no outsider has. I’m proud of this background and like other speakers including ZappiStore’s CRO Ryan Barry and Dan Foreman of Hatted pointed out, the future is not in resisting technology, nor is it necessarily in building your own technology, which can be time consuming and wasteful, but it’s about embracing technology and often learning how to rent or partner with technology experts and adding what you are best at (often data and as importantly consultative insights and strategy).

Several of the CEO’s I spoke with separately admitted having tried various internal technology builds which either weren’t right, or in some cases may have been right when the effort began, but didn’t evolve quickly enough and so was outdated when they did come to market.

Yet it was also quite clear to most of these CEO’s that while it’s critical to watch out for new technology oriented entrants into the market research space, more often than not these simply do not have the knowledge necessary to deliver truly actionable insights. Companies like IBM Watson for instance, certainly have a strong brand name in computers, but their offering as a plug in for marketing research API’s is sorely lacking to say the least.

The point is, knowledge and trust is what we have in good supply at both the event and in our industry in overall. The key to evolving is to remember the knowledge and best practices our industry was based on while being open to understanding outside technologies and ideas, yet resisting the urge to just try to copy them. Importantly as Merrill Dubrow pointed out, there are tremendous benefits in overcoming your fear of collaborating with other research and technology companies and partnering.

This is the idea I’m most optimistic about coming away from the conference. I made several new friends at the event, and I welcome anyone who attended to please reach out if they have are any questions in regard to text analytics and data mining software and discussing potential mutually beneficial relationships.

Until Next Year!

@TomHCAnderson

 

ABOUT ODINTEXT

OdinText is a patented SaaS (software-as-a-service) platform for advanced analytics. Fortune 500 companies such as Disney and Shell Oil use OdinText to mine insights from complex, unstructured text data. The technology is available through the venture-backed Stamford, CT firm of the same name founded by Tom H. C. Anderson, a recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research. Anderson and OdinText have received numerous awards for innovation from industry associations such as ESOMAR, CASRO, the ARF and the American Marketing Association. He tweets under the handle @tomhcanderson. Request OdinText Info or a free demo here.

OdinText Predicts What Television Shows You Will Like

How Text Analytics Rescued Me from a #ShowHole!  My wife and I recently found ourselves in the uncomfortable condition commonly known as a “show hole.” Are you familiar with this?

A show hole refers to the state of loss and aimlessness one experiences after completing—often via binge-watching—the last episode in a beloved TV series without having a successor program queued up. The term was popularized by an Amazon Fire campaign a couple years ago, and you’ll find it hashtagged all over social media these days by people desperately in need of relief.

The show hole is an interesting phenomenon that speaks to how dramatically audience consumption habits have changed with the advent of the DVR, streaming and on-demand services like Netflix, Hulu, Amazon, etc. But what’s curious to me is how such a clearly great need continues to go relatively unmet.

Of course, subscribers to on-demand services have help in the way of recommendations algorithms. Netflix, in particular, has famously invested extensively in developing predictive analytics to suggest other shows to watch.

Still, the preponderance of cries for help on social media would seem to indicate that for many people these solutions have fallen short.

Indeed, it appears that people tend to prefer recommendations from other people, which introduces a different set of problems.

The Problem with Recommendations, Ratings and Reviews from People

In my own disappointing search for what to watch next, I found #showhole aplenty on Twitter, but the platform doesn’t lend itself well to discussion, so most of those who tweet about it get left hanging. Usually it’s just a “Help! I’m in a #showhole!” message from someone after finishing a series, but hardly anyone tweets a reply with suggestions.

Note: Because Twitter isn’t well-suited to this kind of interaction, your standard social media monitoring tool—most of them rely on Twitter data—wouldn’t be effective for the type of analysis we’ll cover today.

I did, however, find a ton of recommendation activity occurring on Facebook, Reddit and a variety of other discussion boards and community-based sites, including surprising places like babycenter.com—a support community for pregnant women and new moms—replete with threads where members actually recommend series’ for other members to try next.

This Yelp-like model for getting out of a show hole has its own limitations, though. How do I know I’ll like what you like? Is it enough to assume that since we’re both new moms that we’ll enjoy the same shows? Or if we both enjoyed one program, that I’ll enjoy whatever else you’ve watched? Similarly, if I ask you on a scale of 1-10 to rate a show, how would that information be useful to me if we don’t have the same tastes? Remember also that we’re looking across genres. Our tastes in dramas might be similar, while our tastes in comedies could be worlds apart.

In short, we have all of these people providing recommendations online, but the recommendations really aren’t any more helpful to the prospective viewer than star-based ratings and reviews. I.e., the show hole sufferer is forced to audition each of these programs until he/she finds one that fits—a time-consuming and potentially frustrating process!

How Text Analytics Can Make These Recommendations Useful

As I pondered the recommendations I saw online, it occurred to me that if I could apply text analytics to identify preference patterns based on recommendations from a broad enough swath of people, I might arrive at a recommendation suited to the unique tastes of my wife and I that we could then invest time in with a high confidence level.

Happily, I discovered that when suggesting new shows to watch via social media, people tend to provide more than one recommendation, and these recommendations usually are not limited to a single genre. This means we have sufficient preference data at the individual level, which, if aggregated from enough people, could form the basis for a predictive model.

In a very short time period, I was able to scrape (collect) several thousand recommendations across a variety of sources online. It’s worth noting that just about every single network that the average American has access to was represented in this data. This is important because someone who uses HBO GO, for example, is obviously more likely to watch and recommend programming from that network than someone does not subscribe to it.

We then layered predictive analytics atop the data using OdinText to see whether text analytics could solve my show hole dilemma. Specifically, I wanted to see what other shows are most frequently co-occurring with shows that my wife and I like in these online recommendations. (OdinText has a few ways it can help in cases like this, including the co-occurrence visualization covered in a recent post on this blog by my colleague, Gosia Skorek, here.)

It’s also important to emphasize here that we accomplished this analysis without asking a single question of anyone, although this type of data could be very nicely augmented with survey data.

OdinText Rescues Tom and His Wife from Their Show Hole!

This data was more challenging than I expected, but OdinText enabled us to find a model that delivered!

Below you’ll find examples of preference clouds based on the co-occurrence of mentions harvested from several thousand recommendations across discussion boards and other social media (excluding Twitter).

Essentially, you’re seeing OdinText’s recommendation for what you should watch next based on the series you’ve just completed.

In our case, my wife and I had completed the most recent episode of “The Walking Dead” on AMC—now on hiatus through February—and, as you can see, OdinText recommended we watch “Goliath” on Amazon.

Not only had I never heard of this series, but when I looked it up I was skeptical that we’d enjoy it because my wife and I are not particularly fond of legal dramas.

It turned out that OdinText’s prediction was spot on; we’re both hooked on “Goliath”!

I'll probably check out "Drunk History" on Comedy Central next...

Attention Show Hole Sufferers: Let OdinText Get You Out!

I think this exercise demonstrates the versatility of the OdinText platform. With a little creativity, OdinText can not only provide breakthrough consumer insights, but solve problems of all stripes.

Here are a few more examples. You’ll note that quite often the suggestions cut across networks. Even though obviously someone recommending something on HBO will be more likely to have seen and to recommend other shows on that network, the model often makes suggestions that are quite surprising, cutting across networks and time. Here are just a few:

Above we have OdinText’s recommendations for anyone who likes “Luke Cage.” (I haven’t seen it and typically am not a fan of super hero stuff, but I ran it as I saw in the data that the show was very popular) “Luke Cage” fans might also like “Daredevil,” “Stranger Things” (which I did love), and “The Flash.” The first three here are all on Netflix, the last one is on CW.

You don’t have to be a premium channel streaming snob to benefit here. If you like the popular sitcom “Big Bang Theory” on CBS, you may well also like their new “2 Broke Girls”, and “Last Man Standing” or “Modern Family” on ABC.

Some of the best shows, in my opinion, are often also ironically less popular and less frequently mentioned. Two such shows are HBO’s “Deadwood,” for which OdinText recommended one good fit—Poldark,” a BBC series--and Netflix’s “Peaky Blinders,” for which OdinText suggests trying “Downton Abbey.

I was honestly so impressed with OdinText’s recommendations that I’m entertaining building a suggestion app based on this model. (And unlike Netflix, I didn’t need dozens of developers and millions of dollars to get the right answer.)

I may also refine the underlying model a bit, as well as update the underlying data in a few months when there are enough new series being mentioned to make doing so worthwhile.

In the meantime, I feel obliged to offer immediate assistance to those poor souls in the throes of a show hole today!

If you’re stuck in a show hole, post the title of your recent favorite series in the comment section of today’s blog. OdinText will tell the first 10 people who respond what to watch next. Then come back and tell us how OdinText did.

I look forward to your comments!

@TomHCanderson

Ps. See firsthand how OdinText can help you learn what really matters to your customers and predict real behavior. Contact us for a demo using your own data here!

About Tom H. C. Anderson

Tom H. C. Anderson is the founder and managing partner of OdinText, a venture-backed firm based in Stamford, CT whose eponymous, patented SAS platform is used by Fortune 500 companies like Disney, Coca-Cola and Shell Oil to mine insights from complex, unstructured and mixed data. A recognized authority and pioneer in the field of text analytics with more than two decades of experience in market research, Anderson is the recipient of numerous awards for innovation from industry associations such as CASRO, ESOMAR and the ARF. He was named one of the "Four under 40" market research leaders by the American Marketing Association in 2010. He tweets under the handle @tomhcanderson.