Tag Archives: big data

How the Entertainment Industry is Using Data Collection

Hollywood is learning what those in the market research world have known for years: follow the data. For years, film studios have had only a vague understanding of who’s buying tickets to their films. As mobile becomes more popular, however, the entertainment business is using the technology to capture what was lost in the relationship between the studios and the consumer, and convert that data into meaningful insight into what works and what doesn’t.

While advertising “The Greatest Showman”, a musical about the P.T. Barnum’s efforts to build a circus show featuring bearded ladies, dwarfs, and the like, Fox executives thought it would be a shoo-in with the same audience who loved “La La Land” and “Les Miserables”. When they looked at the data, however, they found that 75% of the people who viewed the trailer online bought tickets to “Beauty and the Beast”, “Pitch Perfect”, and “Cinderella”. After further analysis, they realized all of those films featured characters who were shunned by society, and ultimately found themselves embraced by certain communities. With this information, they altered their advertising campaigns and pressed the message of inclusion.

Previously, the data segmentation the movie industry used was very high-level: gender, age, income. Now, by using the digital breadcrumbs we leave online, they are able to create profiles that more accurately represent the modern audience. Richard Maraschi, global leader of advanced analytics at IBM, is helping studios leverage the feedback consumers put online to make better creative and marketing decisions. “Now we can get down to micro-segments,” says Maraschi, “like soccer moms in Florida that are really passionate about action films. You can start to get higher fidelity on understanding the audience. You need predictive analytics tools to do that stuff.”

77% of Americans have smartphones, and Fandango is working to make its app more smartphone-friendly in hopes of gathering more data from its users. It launched a Fandango functionality into Apple iMessage and Facebook Messenger, because it believes that’s how younger consumers are communicating with friends. Atom Tickets, a mobile ticketing app, is taking notes from Netflix and Amazon and deploying algorithms to suggest movies that are similar to ones the customers previously enjoyed.

Data analytics has opened a number of new avenues that the entertainment industry can use to analyze past data, make creative marketing decisions, and predict the turnout for upcoming movie releases.

QuestionPro Audience provides our clients with access to more than 22 million active respondents, who are strategically recruited to participate in quantitative research and live discussions. By implementing various recruitment methodologies, we make sure to provide the right kinds of respondents for your research. With industry knowledge and innovative tools, QuestionPro Audience always meets the rigorous demands of our clients. Contact us for your next research project.

Alumni of top national universities: Buying Habits

A survey was conducted by Alumni Reader Panel and qSample to investigate the buying habits of alumni of top national universities. 1,964 respondents completed the survey. Universities represented in this survey are: University of Chicago, Yale, University of Pennsylvania, Princeton, Harvard,  Dartmouth, Cornell, and Brown. Succeeding three charts summarize the demographics of the respondents by each school:




In a bigger picture, 4.4% were Millennials, 23% were Generation X, 72.6% were a mix of Boomers and Silent Generation. In addition, survey respondents were predominantly males (66.5%). Prior to discussing the buying habits of alumni, an important limitation to acknowledge is that there is an insufficient amount of data to categorize the demographic of respondents from the results. For instance, if respondents were asked a question about brand loyalty and given four choices, the results were simply netted by counts. Thus, we could not identify what percentage of the total counts stemmed from which generation or gender. With that in mind, here are the findings (note: data are shown in average of eight schools as there were no significant statistical outliers – margin of error is approximately +/- 5%):

They are brand loyal:


91.6% of respondents agreed that when they find a brand they like, they will stick to it. Furthermore, 90.4% agreed that if a product is made by a company they trust, they are willing to purchase at a premium price. These two independent results revealed a correlation coefficient of 0.994. What this indicates is that brand loyal consumers become price desensitized, allowing the brands to obtain greater pricing power. In addition, 66.1% of consumers are aware that brand name is not the best indication of quality (see below):


Although the survey revealed that these consumers are highly brand loyal, behavioral data portion of the survey showed what might be advantageous to competitors with potential substitute products. 99.1% of respondents indicated that they value “curiosity wanting to explore and learn about new things”. Since a mere 25.8% agreed that they are one of the first among their friends to try new product, word of mouth (through peers) would likely be their most trusted source of advertisement.

They are willing to pay at premium for quality not image:


Respondents were asked to answer the following: “I am typically willing to pay more for high-quality items” and “I would pay extra for a product that is consistent with the image I want to convey”. As there is no direct correlation between these two factor, the correlation coefficient is 0.224. Although we do not have to access to the respondents’ income distribution, as 88.7% of respondents are willing to pay at premium for quality, it may be safe to assume that price is not much of a concern as long the product quality meet their standards. Interestingly, even though only 42.8% agreed to buy products to convey self-image, a striking 65% had expressed that they buy from brands that reflect their style (see below):

styleTherefore, it is critical for brands to identify the lifestyles of their target audience to effectively form bonds and trust with the consumers.

They prefer American products:


60.5% of respondents agreed that purchasing American-made products is an important factor. “Made in America” label has its strong manufacturing reputation, and considering that majority of these consumers value trust and quality, they are most likely willing to pay premium price for American-made products. As a matter of fact, 82.9% agreed that their purchase decision is solely based on quality rather than price.

Moving forward, blog posts will focus on buying habits and decision factors in specific industries (technology, travel/hospitality, healthcare, etc.).







5 Digital Tech Trends Transforming The Pet Industry In 2016

This year promises the continuation of valuable digital technological trends. There will be a new iPhone and there will be a lot of talk about big data. The flying car will probably not arrive nor will the true version of the hoverboard.

Digital technology will certainly benefit the veterinary world. It might even move the veterinarian world up to date with all other worlds. We’ve listed here some of the chief digital veterinarian trends for 2016 and beyond, largely based on the excellent ebook How Digital Technology Is Revolutionizing Animal Health.

Some of the listed trends have been present in some form or another, but this year they fully integrate with both veterinarian practices and pet owners. This happens just in time, as some estimates state that 60% of all pet-care sales will ultimately be facilitated by digital channels, with 20% of sales occurring online by 2018 (versus 10% today).

1. Big Data lands on the veterinary world. Okay, maybe it’s not exactly big data; but the reality is that farmers sit on a lot of data concerning their animals that remains unharnessed to the fullest potential. For example, the ability to efficiently mine and share the effects of hormones or what diseases are affecting pigs in different regions could be a game changer. Companies like Bayer HealthCare Animal have introduced apps that allow farmers and veterinarians to track body conditioning using photos of animals; these apps can then assesses the animals for potential signs of diseases.

2. Communication tools shrink the veterinary world. Even if data is leveraged, communication needs to be nimble in a global market. Connectivity between pet owners and veterinarians will be fully forged as well in 2016. Digital tech like Pet+Pixie fosters seamless communications, promising to streamline the pet health industry long fragmented and paper-based. These tools will enhance everything from the timely delivery of vaccines to sending alarms on emerging illnesses that threaten livestock. Just as important, they can prevent global disease outbreaks.

3. Wearables take foot in the veterinary world. This trend was inevitable, between the reality of microchipped pets and the unreality of such dazzling gadgets like Fitbit and Apple Watch. Pet wearables, along with apps, allow users to monitor such pet health habits as exercise and nutritional intake. Even socialization and playtime can be monitored. Lastly, built-in calendars can transmit alerts for routine care like as vaccines or heartworm prevention.

4. Pet insurance becomes seamless in the veterinary world. Pet insurance has been around for a while, indeed, but it hasn’t exactly been Bo-care (naming it after President Obama’s dog, Bo). In fact, Bo-care has been as cumbersome as Obamacare in many respects. However, 2016 promises to offer the same advanced operations for pet insurance as with human insurance. For example, pet insurer Trupanion allows veterinary hospitals to file claims and be reimbursed directly by the company. Bo knows insurance.

5. Video comes to the veterinary world. Video rules the internet, from entertainment to marketing. By 2018, an estimated 79% of internet traffic will be video content. Why shouldn’t video rule the world of pets? Video will at least modernize the relationship between veterinarians and their clients. Vet On Demand, as an illustration, provides virtual visits between veterinarians and pet owners. Apps like Fetch are interactive, diagnostic tools that bridge the first lines of concern of pet owners.




The digital technologies mentioned should make 2016 a very good year for pet owners, veterinarians and animal producers. And certainly for savvy marketers and entrepreneurs, since the pet industry is currently a $58 billion industry. Maybe the flying car won’t arrive this year, but at this rate pigs will fly.

Vet panel Book

The Top 5 Market Research Trends In 2016 (Infographic)


The Holidays are over, the decorations are coming down, and the weather isn’t getting tropical anytime soon.

That doesn’t mean festivities need to be done, though. Marketers have much to celebrate with potentially game-changing trends paving the way for a bright new year. We can go right back to the future of energetic research. Enter our infographic, based on the data and tea leaves from our two recent articles:

2016 Tech That Will Make You A Market Research Blade Runner

Market Research Trends To Follow In 2016 Or Die

This year certainly seems a time when the balance of technology and human experience, paired with the blurring of quantitative and qualitative research, become major themes in market research.

As always, this or last year, we hope you find the infographic useful in your quest to become a market research Dr. Who. We also hope to hear from you if you have any feedback on these predictions or anything else.

infographic with a list of market research trends in squares

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Market Research Trends To Follow In 2016 Or Die


Okay, the headline might be a tad sensationalistic. Your market research position is probably as safe as the video store or the phonebook. But just in case, palpable trends loom in 2016 that require your attention. These shifts  will alter the landscape of market research—and perhaps to infinity and beyond (depending on the data).


Surveys Will Have To Be Better


The online survey business is booming like a Star Wars box office. It seems everyone is getting in on that quantitative action. Many tech giants are now offering integrated surveys, the latest example being Twitter and its nascent Twitter Polls. The field is getting crowded.

What’s more, budget-conscious companies are demanding surveys in the name of caution. The result is a watering-down effect. As we reported, this is causing participation rates to drop, with some studies “showing participation rates averaging 2 percent.”

We’re not alone in our findings. Market research veteran Leonard Murphy recently wrote:

Market research surveys are increasingly alienating customers and citizens. As a consequence, response rates for commercial market research are fast reducing below 1%. This means most surveys annoy people and it means they are reflecting the views of a tiny minority.

Between online surveys becoming akin to Nigerian email spam and every company deparment potentially having the ability to provide polls, the solution is not desperation at the glut but just a better, more customer-exciting execution from market researchers.

The question many in the industry are concerned with is not whether surveys are dying, but, as one market researcher put it: “Who will own surveys within the organization in 5 years from now: Marketers, Technologists or Market Researchers?”

I’m betting on market researchers who take this article to heart.


Market Research Will Be More Human


Advances in technology should not mean a less humane approach. After all, tech giants like Amazon or Apple seem to increase customer experience with every tech evolutionary step. The same should go with market research.

In his GreenBook article, Are You Alienating Your Customers With Spam Surveys? Ray Poynter details the robotic attitude of market researchers. Drawing upon data and thought leaders, he proposes two obvious way to improve the industry:

Treating customers like people
Engaging with customers over time

That certainly goes for sample providers. The GreenBook Research Industry Trends Report states that only 40% of researchers are very or completely satisfied with their provider.

We all gotta step it up. (Although, to be fair, at qSample we’re ahead by being a boutique company with an always direct pipeline of communication to our clients).


Market Research Goes Fully Mobile


Everyone has been saying it, but it’s time to fully accept it. More Americans are using mobile devices to browse the internet than on PC’s; and already 60% of cell phones are smartphones. The data will only tilt more in 2016. We’ve written extensively about the advantages and trending of mobile surveys.

As market researcher JD Deitch wrote on the important of going mobile (also in GreenBook):

Research buyers, if you’re still running long desktop-only studies, you are a fundamental cause of this problem. Blaming your suppliers for the quality of their panelists is like blaming the bartender for your hangover. I get that the change is difficult, but unless you really don’t care about people under 35 or moms with kids or ethnic minorities, you’re increasingly buying junk. This has to be part of the 2016 plan.

I can’t think of anything to add to this quote, except to quote Deitch again in the article, who said that all research should be “device agnostic and optimized for mobile by design.”

Just like every website will be by the end of 2016.


Market Research Will Still Be Talking About Big Data


There was a lot of this palaver in 2015, but no actionable illustrations from market research. It looks to be 2017 before Big Data can make even a small difference.

Big Data is still just too big and too costly, unless you’re Microsoft, IBM or Tylor Swift’s wallet.

Take, for example, the words of research executive Annie Pettit:

Big data caught the attention of market researchers and the search for people who know statistics and data and consumers is now full steam ahead. Given that big data is massively relevant to our clients in that it is their consumers, their data, and their intelligence, we need to be ready to merge insights from traditional research with insights from big data.

That’s a lot of talk leading nowhere…

One of our executives, I feel, put it best when it comes to Big Data:

It’s like teen sex. Everyone talks about it, everyone wants to do it, everyone thinks they know it, but no one is doing it.

Like I said…2017…


Market Research Will Focus On Experience And Convenience


The points mentioned above on customer treatment and survey experience should be enough to understand this notion. To highlight this idea even more, take the words of qualitative marketer Rhiannon Price:

Market research is founded on unpicking human character, but this has perhaps become a little lost as research and respondents have become more and more commoditized.

The issue is broader and more prevalent. In our recent breakfast with Google, one of the tech giant’s marketers told us in essence that “consumers are now more convenience-loyal than brand-loyal. Making it easy for consumers to find and buy your product is imperative.”

The same goes with respondents.

Consumers (and respondents) want an experience as much as a product—as much as they want convenience more than a brand. As Eye Faster CEO Kirk Hendrickson recently stated

Retailers are focusing more on what goes on while their customers are in the store and focusing research efforts on the entire experience as opposed to interactions with a given product or category.

As many market researchers have predicted, the lines between qualitative and quantitative are blurring, often on the screens of a mobile device held in a store aisle.

In short, the proverbial journey matters as much as the proverbial destination.




Experience, Mobile, humanity…these overarching themes will continue to sparkle in 2016. They are all interrelated. One could add video, but that’s part of the mobile era. Regardless, keep this in mind and you won’t be the next video store owner—alone and unemployed in Greenland,  moping about and talking about…Big Data perhaps?

The Advantages of Mobile Research

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Quiz: Are You A Market Research Expert?


There’s no doubt your data surfing and number-grinding have produced stellar results for your company or client. There’s no doubt that your qualitative Sauron-eye has continually mined the deepest shafts of your focus groups’ subconscious.

But are you a Market Research Expert? Do you know the system as well as the history? Do you thrive in the backend of surveys as well as the vanguard of mobile studies?

That may be settled today with qSample’s interactive quiz. I hope the quiz entertains you, for I believe in infusing humor into work to make for a better user experience. When I tell this to my boss, his response is always: “Great. When are you going to start?”


Regardless, please give qSample some feedback on the quiz and share with your peers. We hope it sharpens your already razor-mind.

Oh, and note that you can only take the quiz once (unless you erase cookies or use another browser, that is):


Sex Doesn’t Sell, Part 2 (and why)

Picture of kid in suit shocked at sex in advertising

There was quite a reaction to our recent article New Studies Make It Official: Sex Doesn’t Sell. That’s not surprising, considering the topic: the relentless trope of sex in advertising. Some marketers even emailed me objecting to a point the research; they even presented data from advertising campaigns where sexual imagery and content bolstered a brand.

Their statistics were sound, I must admit, so what is going on? Does the babe or stud holding your beloved product work or not? Out of work actors and checkbook-holding CMO’s want to know.

I would contend, based on the studies I cited, that sex still doesn’t sell. Having said that, I can accept that at one point sex did potentially sell. Let me expand, specifically by expanding on one of the studies mentioned in the previous article.


The coupling of sex and big data

why sex doesn't sell part 2 2

The expansion comes from the insights of a recent Newsweek article, written by the authors of the cited Psychology Bulletin study in the previous article: Robert Lull and Brad Bushman.

To support their initial analysis, Lull and Bushman took sex in advertising to big data levels. They conducted a meta-analysis—or quantitative review—of existing studies on the impact of sex and violence in advertising. They processed 53 studies that qualified for inclusion, involving a total of 8,489 participants.

According to the article, this the sampling of what they found:

  • Brands advertised alongside violent media content were remembered less often, evaluated less favorably and less likely to be purchased than those advertised in nonviolent contexts

  • – Brands advertised using sexual themes were evaluated less favorably than brands advertised using nonsexual images

  • – As the intensity of sexual ad content increased (from suggestive poses to full frontal nudity), memory, attitudes and buying intentions decreased

  • – There were no significant effects of sexual ads or violent ads on memory or buying intentions

  • – However, when media content and ad content were congruent (eg, violent ads in violent programs, nonviolent ads in nonviolent programs), memory improved and buying intentions increased.

In the end, Lull and Bushman stand by the notion that sexual (and violent) programs and ads do not increase brand value. The exception, they admit, would be when media content and ad content occurred together; however, these measures of ad effectiveness were either insignificant or actually somewhat negative. The authors furthermore admit there is much research to be done when it comes to the sexual advertising on the internet, but as things now stand…

Does that settle the issue of sex in advertising?


The Divorce of Sex and Human Awareness

sex doesnt sell and why

As mentioned, I could certainly accept the idea that at one point sex in advertising worked effectively for brands. Perhaps the game has changed in this digital age where consumers are savvier than ever in filtering media missives. In fact, there are theories that support a paradigm change:

The Evolutionary Theory

This theory is proposed in the Newsweek article by Lull and Bushman. In short, the theory states that our minds are hardwired to be attentive to sex and violence. They were a vital way of life for our ancestors. As the authors state:

Attending to violent cues prevented our evolutionary ancestors from being killed by enemies or predators, while attending to sexual cues attuned our evolutionary ancestors to potential opportunities for reproduction.

The problem is that the human attention span is now focused on other, more cerebral notions, as we continue to evolve. Sex and violence capture our attention, but they ultimately don’t keep it when presented alongside other competing messages.


There are many studies claiming that exposure to sex and violence ultimately desensitizes the human mind.

I am not going argue any moral grounds in this article. Nevertheless, it simply makes sense that the more competing sexual imagery being broadcast the less effective it will serve a specific brand. As qSample has presented: 5 minutes is the average attention span of a person (dropping from 12 minutes in the course of the last ten years). There are simply more choices, more media bombardment, and less room to make a connection with consumers.

Believe it or not, even sex can be watered-down in the human consciousness.

Conservative Nation

The U.S. has become more progressive in the last few years, according to Gallup. However, Gallup also states that the country still tilts heavily towards more conservative values, a trend that occurred as the economy soured in blue-collar states after the 2008 economic crash.

The media may be shelling consumers with sexual imagery and content, but it makes sense there would be resistance by a more traditional population more accustomed to being frugal in a new economy.

With all of this in mind, it’s reasonable to understand why sex doesn’t sell (even if, according to the emails I got, it once sold well years ago in well-planned campaigns).

Could sex sell again in the future?

Perhaps. But at the moment it’s certain that sex is formidable for seducing consumer attention, but rather limp when it comes to actually promoting a brand.

Hard to reach audience button

Big Data is Science Fiction Already Here

Big data is a tech buzzword that instills varied emotions in the business community, from excitement to cynicism. To some, it’s a new era that is either:

An incoming apocalypse (there goes our privacy!)
An incoming paradise (there goes their privacy!)

The hype has arrived, but the era of big data is not exactly here although it’s here—yet organizations better be ready for it or they’ll go the way of the Myspace dodo (or something like that, according to some digital prophets).

Okay, but what exactly is big data?

Big data may seem like actualized science fiction, and in actuality science fiction is a suitable means of crystalizing technological advances (and sometimes inspire them, such as in the case of some of the first cell phones, inspired by Star Trek). By taking a look at some groundbreaking science fiction movies, one can easily (and perhaps ironically) demystify the notion of big data.

First, a technical definition of big data: There isn’t one.

To illustrate the murkiness of defining big data, Forbes published 12 Big Data Definitions: What’s Yours? The piece proffered several characterizations, from bland Wikipedia to eccentric scientists conjuring terms when pausing in their search for the next God particle. Nobody fully agrees, and in fact nobody even knows if the term should be capitalized.

In the most simplistic way, big data could be defined as this:

A lot of big-ass information floating around in digital form that if corralled could be useful for data research and statistical analysis…but it takes a big ass a machine as large as Skynet to successfully store, handle, and make sense of all this big ass information.

To wit: The big-ass information is basically a universe of records, forms, surveys, applications, and what not, just waiting to be organized and analyzed. This, in theory, can potentially make an organization near-prophetic (and others maybe just efficient). Big data could be a boon to such bulky industries like healthcare, military, human resources, and consumer insights.

At an American Marketing Conference, Justin Massa, CEO of Food Genius, adroitly defined big data as having five “V’s”:

Volume: The most obvious of the 5, there’s lots of data!
Velocity: The data grows and changes quickly.
Variety: Data comes in a variety of structures, creating complexity.
Veracity: “Dirty” data may need to be cleaned up.
Value: All that data is only useful if you can extract value.

(Perhaps coming close to the most suitable definition of big data, Massa added that it is any data that is too large to fit into an Excel file).

All of this ought to be useful. But again, glancing at science fiction movies we can see the allure and even potential of big data:

The Matrix

Matrix and big data

This iconic movie about rebellious machines is typified by those green digital numbers floating before the screen. The numbers clearly represent big data. Even the Matrix itself cannot fully manage this big-ass information with all its data mining  (as seen by mathematical anomalies, rebellious programs like the Oracle and the Merovingian, and its many (many) climaxes in the plot). In the end (or after the first and third movie of the series), it’s actually the protagonist Neo who is able to process all the big data, becoming the ultimate tragic hero.

Lesson: No matter how efficient the technology, it still takes a human to understand the big picture of big data.


Pi and big data

Many might not remember Darren Aronofsky’s directorial debut. The film is certainly an engaging exercise in understanding big data. The plot centers on the protagonist Max and his computer Euclid’s ability to predict the future movement of big data anywhere (something already in our world, called predictive analytics). As an example, Max is able to make stock predictions based on the calculations of Euclid. Could this eventually get him to unravel the secrets of the cosmos, all one big mathematical equation? In any event, all of this gets Max in some trouble with the authorities, business moguls, and even Jewish Kabbalists.

Lesson: The universe is one big, big data processor, unmatched by any mortal device. Be nice to it.


Transcendence and big data

The latest bomb by Johnny Depp deals with the concept of Transhumanism, where computer and human become united in byte bliss. Depp’s character is the first to undergo this phenomena, immediately enjoying access to almost limitless information while struggling to retain his humanity (and girlfriend). Ultimately, it’s humanity’s ignorance that aborts so much potential, not the information being gathered and utilized.

Lesson: Turning back the clock on big data could be unwise, but not as much as not raising one’s empathy in any new era.


Lucy and big data

In this movie, it’s not curiosity or miffed machines that causes the leverage of big data. It’s motherhood. Lucy (played by Scarlett Johansson not being the Black Widow) is accidentally injected with massive amounts of CPh4, a drug found in expectant mothers that accelerates brain activity. Lucy acquires so much brain activity that she is able to tap into all the information of the planet and become basically divine (and still able to karate-kick bad guys, as happens in any Luc Besson film).

Lesson: Intelligence has to be nurtured like a child even before birth, so does big data.

None of the mentioned films really grants a pedantic definition of big data. Yet in a very Joseph Campbell-style, they make the idea of big data approachable, understandable, and even romantic. Part of the function of mythic art is to bestow humanity’s a workable relation the changing environment. These films are certainly mythic art; and science fiction additionally offers possible results in didactic flavors without us having to undergo them.

Ultimately, big data is nothing but a natural stage of the information era, another tool of qualitative market research. It’s just not as sexy as social media or smartphones (and no one still agrees on capitalizing those two).

There is one specific future we can depend on when it comes to big data, and all the cited movies agree: It’s not so much how big data acts that matters, it’s how humanity reacts to it that will make the difference.

The path to big data will certainly be a fine path between an apocalypse and a paradise.

button panel book second


Is Predictive Analytics the Next Minority Report for Businesses?

One of my favorite cultural tropes has to do with one of my favorite writers, Philip K. Dick, and his work Minority Report (also adapted as a blockbuster movie, with Tom Cruise and directed by Stephen Spielberg). The storyline essentially deals with law enforcement having the ability to predict a crime before it happens (and arresting a suspect before he or she becomes a suspect!).

Predicting behavior before it happens: a trope many beyond the authorities would like to see as a reality—certainly in the corporate world where management eternally clamors to market research departments for the ultimate crystal ball.

In our tech era it seems science fiction is regularly an actuality, and predictive analytics is being considered as the (next) ultimate crystal ball.

Is it? What exactly is predictive analytics?

The Matrix and Big Data

I know that you know that I know what you’re going to buy

First, it should be mentioned that in order to be prescient, predictive analytics needs to be paired with big data (a tech buzzword that, like the word “gluten” in the food industry, many still don’t know what it is). Big data is basically information too unwieldy to be addressed by traditional databases and software. Massive data centers that look like the inside of the Death Star are required to store big data. Often the firepower of the Death Star is necessary to process big data.

I like how a tech expert simply defined big data:

It’s all about sorting variables and tracking them, piecing together things that humans can’t. Computers are very good at sifting tremendous quantities of information (with the right software, of course), and that’s the core of big data.

Google data center, where the Arc of the Covenant is also stored

Google data center, where the Arc of the Covenant is also stored

More or less going back to science fiction, in order to understand predictive analytics, picture all the digital numbers cascading down in The Matrix, with the business world attempting to be Neo after his resurrection. So far not many in business have become “The One” in their efforts to corral big data into consumer meaning.

Morpheus might actually represent predictive analytics, though, the carrier of the Red Pill to tap into big data. According one source, predictive analytics is:

Predictive models and analysis are typically used to forecast future probabilities. Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. It uses a number of techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts.

In essence, it appears this is something close to the ultimate crystal ball. In the Huffington Post’s Can Big Data Save World? the author illustrates the potential in the marriage of big data and predictive analytics:

Online retailers not only know what you bought, they know what you considered buying (viewed); where you came from (prior URL); what path you took through their site; what you finally bought; and how you paid for it. They can even suggest products that appeal to your personal tastes and interests. In other words, they now have the information to create a unique shopping experience just for you.

Seems the Oracle instead of Morpheus might be a better illustration of predictive analytics (and if big data can’t save the world, at least we still have The Avengers). In fact, the company Oracle already provides predictive analytics software (as do Microsoft, IBM, and Microsoft), as well as other smaller companies in what is a blooming market.

Does predictive analytics work

I see dead shopping people

Here are some other ways other major players in the tech world are using predictive analytics to augur your very future:

Google: from trying to finish what you’re typing in the address bar with autocomplete, to selling its proprietary software platform, this company spends a lot of time kissing everyone’s kismet.

Facebook: Not a surprise to see this name as well, for your News Feed is all about knowing what you want to read at before even logging in. As an article in Forbes reported, researchers have concluded that Facebook “could predict our personality more accurately than most of our close family, friends, and maybe even our therapist.”

The Video Game industry: Okay, not surprising either, considering the amount of information that gets injected into the various companies from an industry that is larger than Hollywood. As an example, one source stated that:

EA games generate a whopping 50TB of data per day. This data is in the form of gameplay data, micro-transactions, time stamps, in-game advertising, multi-player information, and much more.

The piece concluded that video game companies “see the huge opportunity to customize gameplay, find new ways of monetizing games, and even enriching the gaming experience by making it social.”

Not leaving the basement, Mom, and I'm busy with important predictive analytics

Not leaving the basement, Mom, as I’m busy with important predictive analytics

All of this may indeed sound futuristic, and perhaps bordering on Orwellian, but the reality is that predictive analytics has been going on since someone told someone not to eat a fruit because they might venture on a fig-leaf shopping spree. Market research has been in the prophecy business for generations, crunching numbers in various capacities to understand consumer conduct.

As one MIT Professor put it, predictive analytics is basically “a way to predict the future using data from the past.”

All of us continually use the past to measure the future of those around us all the time, like during Thanksgiving with our families. The difference is that predictive analytics, along with big data, takes prophesying in a scope never seen before in the far reaches of the internet clouds. Not exactly science fiction, perhaps, but it certainly is a report that is not minor in any way.

Mobile Surveys: The Pandora’s Box of Awesomeness

In market research any new trend often feels like a Pandora’s Box: something a company feels it needs to open but is then blindsided by the outpouring results. Big data, social media, and content marketing are some examples—even as many are finally being harnessed for decipherable benefits. Mobile technology is certainly in this category; as an example, we reported that 71% of businesses employ mobile apps yet almost half of the respondents find it “extremely challenging.”

The reality is that the Pandora’s Box that is mobile technology is already open. As CNN reported, more Americans are using mobile devices to browse the internet than on PC’s, and already 60% of cell phones are smartphones.

This should not be the case where surveys and mobile technology intersect. The one danger coming out of this Pandora’s Box is the efficiency in data collection, and there is a box-full of research as proof.

This qSample’s SlideShare on some of the advantages of mobile surveys (and we will get more below):

In our Mobile Vs. Online White Paper, two panels were recruited to conduct a survey on preferences in chewing gum. One panel used mobile technology, while the other used computers. The conclusions not only underscored the benefits of mobile surveys, but deduced the behavioral differences between consumers using mobile technology and those who primarily stayed online:

Mobile data collection has an advantage over online surveys in cooperation rates (i.e., likelihood to participate) and in speed of response. Twice the data was collected in half the field of time. The mobile survey had to be shut down earlier than the online one, which was left open nearly a week to achieve the desired sample size of 300 completed surveys. For short surveys, mobile data collection can reasonable replace online data collection. In addition, the quality of data could be expected to be superior because the methodology is still a novelty and respondents seem more engaged. Because of this, field times can be shortened as well.

Even Wikipedia agrees, stating: “Apart from the high mobile phone penetration, further advantages are quicker response times and the possibility to reach previously hard-to-reach target groups.” Last but not least for any business feeling their budget might be another Pandora’s Box, and as a market search company explained—mobile surveys offer a “significant drop in production costs.”

From a marketing standpoint (and referring back to the SlideShare), the research also revealed these insights:

–   Mobile respondents are generally younger and work full-time.
–   Mobile respondents generally earn more.
–   Mobile respondents tend to buy more capriciously, such as making a decision in the checkout lane instead of planning.
–   Mobile respondents are more open to changing brands.

This all points to the reality that mobile technology is fertile ground for many companies. To wit: mobile surveys are more efficient and reach an audience that can be better influenced.

Of course, there are some disadvantages to mobile surveys, as our article demonstrated:

–   Surveys need to ensure they are calibrated to various mobile platforms, from IPad to Kindle Fire, from IPhone to Android phones.
–   Questions need to be as short and concise as possible, because of the limited space in mobile platforms.
–   Apps that conduct surveys need to be as light as possible, because of the restricted size of mobile technology hard drives.
–   Because of better wireless network services in cities, surveys can potentially be skewed, limiting the responses from those living in suburban settings.

These disadvantages will likely become moot, though. Cloud technology, an expanding range of wireless networks, enhanced devices being produced every year, and more people buying mobile devices will gradually erase these concerns. As for length and bulk of questionnaires, our recent piece provided a key to the best possible surveys in any medium: write short and sweet questionnaires. In other words, mobile surveys are already a suitable platform for effective online surveys.

However, the reality is that online surveys is still king as it relates to data collection; it’s the mode of choice for research data collection and continues to surge (even beyond online sampling). Industry purists predicted that mobile would surpass online, and that has yet to happen.

In the myth of Pandora’s Box, the one concept that was left after the forbidden container was opened was hope. Needless to say, when it comes to mobile surveys (and all mobile technology), hope is certainly out of the box and into a potentially epic future.