Quirk's Blog

The increasing value of shopper technologies

Editor’s note: Erik Olson is the vice president and senior qualitative research consultant at Market Strategies International, Conn. This is an edited version of a post that originally appeared here under the title “Shopper technologies come of age.”

Intercepting or tagging along with consumers as they chase through the store on a shopping trip has been the go-to methodology for us “in-the-moment” researchers for decades. For the most part, it’s still a good way to build insight about shopping behaviors through observation, inference and discussion.

But in this age of “retail activation,” also known as generating immediate sales transactions, casual interpretations aren’t good enough. We need better ways of getting closer to shoppers’ decision making at the point-of-sale, seeing shelves through their eyes, knowing which visual features have the greatest impact and understanding what triggers their moments of truth. Here is a breakdown of two of the more promising innovations: instant micro surveys and eye-tracking glasses.

Instant micro surveys

A year ago, Apple introduced iBeacon technology to help iBeaconthe retail industry simplify payments or enable on-site offers. One or more low-cost beacons (Bluetooth® Low Energy or BLE transmitters) are placed in a retail environment and transmit a unique signal. When a shopper who has opted-in with an iBeacon-equipped smartphone (Apple or Android) passes within a few meters of the signal, it enables the device to perform an action, such as present a recipe, offer a promotional coupon or share a link to a mobile research opportunity (you may not be shocked to learn that we think the latter application is the most important).

For the first time, this allows shoppers to:

  • instantly share an opinion,
  • rate a shopping experience,
  • take a picture of the offer or pack design that is catching their eye or
  • record a snap video about that particular moment of truth for our research team to analyze.

Respondents need not wait for an interview following the shopping trip nor try to reconstruct the experience in a focus group or online bulletin board. They capture their attitude and action immediately while they are standing directly in front of the shelf we’re most interested in discussing.

Importantly, shoppers opt in to the research for a small incentive, like a free gallon of milk. The devices don’t track users and they don’t push content to annoy shoppers. Shoppers collaborate because we create a benefit-reinforced incentive rather than offering a 10 cent coupon which presents little relevance and virtually no value (like so many mobile surveys offered today).

We are currently working with vendors that have deployed a network of iBeacons in retail locations across several metro areas, and the deployment is growing each day. We’re also testing individual iBeacon placements in single stores to supplement other micro-qualitative and quantitative research activities in the market. The methodology is delivering insights fresh, fast and hot!

Eye-tracking glassesSMI Technology

We have known for many years that shoppers don’t have insight into what they do or don’t want, and they don’t know what motivates them to buy. Even with sophisticated shoppers, relying on qualitative data from “shop arounds” and post-shop interviews can be misleading.

Early eye-tracking glasses were clunky and obstructed respondents’ peripheral vision. But the latest versions of the glasses are lightweight, less obtrusive and allow researchers to “watch” shopper interactions from the front of the store. They let us literally get inside shoppers’ heads and peer through their eyes as they shop. We no longer have to rely on rationalizations about what they did – we can see respondents’ fast-thinking behaviors in action.

eye-tracking

Eye-tracking glasses use miniature video cameras to fixate on a shopper’s pupil then superimpose a target over streaming video precisely where the shopper’s eyes look. The optical alignment is so fine that the researcher can distinguish whether the shopper is looking at the brand name, sub-brand or ingredients on a chewing gum label or whether they are searching for a familiar brand name or a great price as they approach the shelf.

Typically researchers interview shoppers prior to the study about their immediate goals and expectations. The researcher fits and calibrates the glasses and then the respondent shops as they normally would. The research team watches streaming video of the shopper’s gaze as she moves through the aisles and makes purchase choices. A debrief afterward gives the team preliminary information, but the analysis of the eye movements of all the shoppers in the study delivers detailed metrics on viewing, holding and reading activities in the shopping process.

The true value of eye tracking is the data gathered that can support the real decision-making brand marketers must do. Too often, old qualitative eye tracking studies only went halfway and provided cookie-cutter analytics and heat maps like the ones shown below which simply show what the majority of shoppers looked at on this sample display (red is the greatest area of focus).

tracking study

Consider some of the following metrics we now generate using advanced analytics such as clustering and factor analysis enabled with proper data collection:

  • How products in the consideration set funnel to purchase or, more importantly, how to disrupt a product in the consideration set to get your brand in the shopping cart;
  • exactly what shoppers notice, evaluate, select and buy – and why;

insights table

  • which element of the message, placement, design or marketing mix influenced the purchase decision;
  • how stimuli placed in the shopping environment drive shopper attitudes toward their favorite brand (see example below of quantifying the impact of shelf placement);

shelf placement impact table

  • what competitive brands have done to steal your share and which of their brands may be vulnerable to your attack; and
  • which features of displays, signs, POS, packages, shelves or price tags actually drive performance.

Posted in Behavioral Economics, Brand and Image Research, Consumer Research, Product Research, Qualitative Research, Retailing, Shopper Insights | Comment

When reviews matter: Netflix goes social

Editor’s note: Rachael Genson is the North American public relations manager at Bazaarvoice, Texas. This is an edited version of a post that originally appeared here under the title, “Netflix goes social with movie recommendations.” recommendation

Earlier this month, Netflix announced a social update allowing users to privately recommend video content to Facebook friends. After watching a movie or TV show, the site will ask users whether they want to suggest the content to a friend, giving them the ability to provide viewing suggestions without broadcasting that recommendation to their entire Facebook friend list.

With the number of social posts bombarding our news feeds numbering in the hundreds of thousands each day, this kind of selective recommendation service seems sensible. But for those of us in the reviews industry, the update begs the question: Are friend-to-friend reviews the right approach for social recommendations?

This entire system is driven by the assumption that friends know their friends well enough to recommend movies and TV shows that align with their viewing preferences. But how well does that assumption actually hold up? Bazaarvoice found that, at least in regards to products, over half of Millennials (consumers aged 18 to 34) trust the opinions of strangers online over those of friends and family.

Recommendation limitations

Consumers don’t always agree with people they know. The beauty of online reviews is that they give consumers access to the opinions of like-minded individuals – those people whose recommendations on a product, service or movie may ring truer than a friend who assumes that your preferences perfectly align with theirs.

Whether by Netflix or any other brand, limiting recommendations only to select friends eliminates the opportunity for users to discover useful information while scrolling through their Facebook news feed. But it’s more than just the audience alone; the recommendation itself warrants further consideration. Rather than simply asking consumers to suggest a friend who would like the content, brands (Netflix included) should dig deeper to get to “the what” and “the why,” as that is the information that makes a recommendation truly useful – why is this movie/product/service worth recommending and what specifically makes it something your friend(s) would be interested in?

And just as making a recommendation to only one or two Facebook friends limits its visibility, so does restricting content only to a user’s Facebook audience. It’s important to allow user recommendations to span as wide an audience as possible, so brands and retailers should give consumers the option to broadcast to their larger Facebook network and post their recommendation directly to the company Web site. Increasing the recommendation’s visibility increases the chances that it will be shown to the right people – the friends, family or strangers that will find true benefit from your words. Plus, research from our Conversation Index, Vol. 3 shows product opinions contributed on a Web site and shared to Facebook generate a 5 percent higher rating compared to those that are not shared.

This is not to say there is no place for private friend-to-friend recommendations or that Netflix’s update is misdirected – in fact, there are advantages to allowing friends to recommend things to friends. But in the larger scope of ratings and reviews, it seems ineffective to decrease the value a good, thoughtful recommendation can provide by limiting its reach to only a select group who may or may not appreciate its content.

Posted in Brand and Image Research, Consumer Research, Public Opinion/Social Research | Comment

Online qual: building a better respondent guide

Editor’s note: Ray Fischer is the CEO of Detroit-based online marketing research platform Aha! This is an edited version of a post that originally appeared here under the title, “How to create a successful qualitative research study: Building a better respondent guide.”

Online qualitative is a powerful tool. Used properly for creating a marketing research study, it can generate rich consumer insights from engaged and willing respondents. Used improperly it can create a mountain of useless data that was painful for the respondents to generate and is exponentially more tedious and time consuming for consultants to analyze.

The key to creating a great online research study is understanding the objectives and then creating a series of activities that humanize your respondents and encourage them to openly share thoughts and feelings in a way that does not feel like work but something respondents look forward to doing.

You know you have achieved this research nirvana when the online qual study is over and you receive unsolicited notes from respondents saying how much they enjoyed the study and that it made them think about themselves and the subject at hand in ways they had never anticipated. A more pragmatic and bankable indicator of an effective guide is a 95 percent successful completion/compliance rate with nearly everyone completing all of the tasks on time with quality responses.

What makes an online respondent guide great?

Follow these simple guidelines and you are on your way to creating a better qualitative study with higher respondent completions rates:

Provide full disclosure. Make sure respondents know what they are doing and why they are in the study. Tell them what is expected, what they will be doing, the schedule of events and when things are due. This takes the mystery out of the process and makes them feel a sense of responsibility to provide you with focused and connected responses.

Bend ‘em but don’t break ‘em. Challenge their creativity and push their introspection but don’t overwhelm them with too many questions and tasks. Avoid anything that will dull their senses and make them feel like they are working on a term paper. Our prevailing thought is that 20-30 minutes is the optimal amount of time for a respondent to engage in an activity at one time. Beyond 20-30 minutes the law of diminishing returns sets in for the respondent and the researcher – and tired respondents drop out.

Design with analysis in mind. The data from online studies can be overwhelming if the study has too many activities and too many questions. For example, think about 50 respondents answering each question in a study. Ask the right questions, encourage them to elaborate on the important stuff and don’t use this method to ask every question a client may have. It can seem like an unlimited opportunity to ask as many questions as you createwant … resist the temptation.

Be creative – straight Q-and-A can be boring. Using methods such as storytelling, “letters to friends” and “collage” can make things interesting and engaging to the respondents and more importantly provide rich symbolic insights for researchers. Well planned open-ended activities will generate more learning for researchers. Respondents love to talk about themselves and creative activities allow then to emote more freely than in straight Q-and-A approaches.

Successful online research studies take some planning. Getting off to great start with your respondents is one of the keys to finding deep and meaningful insights.

Posted in Consumer Research, Market Research Best Practices, Market Research Techniques, Qualitative Research | Comment

Money talks: Should research respondents receive cash incentives?

Editor’s note: Mark Hughes is the Manager, Global Payment Solutions at global payments provider hyperWALLET Systems Inc., Vancouver, Canada.

It goes without saying that researchers encounter many problems during the research process. One of their biggest frustrations? Finding people willing to participate in the data collection process. Whether it’s answering a survey, completing a series of tests or taking part in a clinic trial, persuading people to engage in your research is crucial. Without high quality data, you won’t be able to test your hypothesis or validate your findings.

But as we all know, encouraging participation calls for more than enthusiasm – it often requires an incentive.

Incentives 101: What are you offering?

What is an incentive? According to the Market Research Society, an incentive is defined as “any benefit offered to respondents to encourage participation in a project.” A subsidy, gift or reimbursement that is presented to a respondent in return for their input, incentives should be carefully monitored by research ethics committees in order to ensure that they’re used in a reasonable and proportionate manner.

One size doesn’t fit all

This is an important thing to moneyremember when proposing a project compensation approach. Demographics of the expected respondents, how specialized the subject matter is and how time-consuming the data collection process will be are just a few factors you’ll need to consider when deciding if and what kind of incentive is necessary. Ultimately you want to place an appropriate value on the time and input of the respondents without going over budget or burdening your team with unnecessary administrative oversight.

Traditionally, there are two basic ways to incentivize a research project:

  • offering something to everyone who participates and
  • conducting a free draw where a small number of respondents have the chance to win a prize.

Up until now the latter has proven to be a favorable option for many researchers, especially those conducing survey samples. The reason for this is simple: giving something to every participant can become administratively and financially taxing. There’s just one problem – research shows that respondents prefer to receive a guaranteed incentive, specifically a guaranteed monetary incentive.

“Show me the money”

According to research from Eleanor Singer of the Survey Research Center at the University of Michigan, incentives increase response rates to surveys in all modes, including the Web, panels and cross-sectional studies. What’s more, Singer’s research has also found that monetary incentives increase response rates more than gifts, and incentives that are prepaid increase response rates even more than promised incentives or lotteries.

Expanding payment types the hassle-free way

In the past market research firms have avoided cash incentives partially due to the administrative frustrations they entailed. In most cases, issuing a cash incentive as part of the research process has required printing and distributing paper checks – a costly and cumbersome undertaking, particularly for smaller value payments and global incentive programs.

As a result additional incentive options have been utilized by market research firms in an effort to find more convenient payment methods. Common alternatives have included restrictive closed-loop gift cards, vouchers, coupons and/or charitable contributions. While more convenient for the survey issuer, these incentive options do not typically provide participants with their preferred incentive: cold, hard cash.

Fortunately, a new wave of incentive fulfillment systems (like ours here at hyperWALLET) is making it easier and more affordable for researchers to issue cash incentives. This includes a proliferation of flexible cash incentive payment options that are particularly well-suited to the market research sector and its survey participants, including prepaid and virtual cash cards and payment onto already existing debit or credit cards.

Finally research firms can reduce the administrative and transactional costs of their incentive fulfillment at the same time participants can enjoy the benefits of redeeming their incentives via several cash payout options.

But is paying cash for consumer input ethical?

When payments are problematic

Paying a person for their participation in a survey makes sense. After all, it places value on the respondents’ time in a way that’s similar to an hourly wage. That being said, researchers need to be careful about how they issue these payments. Cash payments may have implications in terms of participants’ benefits or taxation, specifically if the compensation is determined to be awarded as income rather than an incentive.

While that may seem like a convoluted case of semantics, it’s actually a very serious concern for ethics committees. As Alderson and Morrow identified in The Ethics of Social Research with Children and Families, the standards of the 1947 Nuremberg Code state that no persuasion or pressure of any kind should be put on research participants. The way in which incentives are presented to research participants is thus extremely important and shouldn’t be open to interpretation. Failure to exhibit this information properly could cause your incentives to exert undue influence on potential participants’ decisions about whether to take part in the research project. In this case, the argument could be made that participants’ consent was not truly freely given but obtained through coercion. The data collected in the process is now considered inadmissible by the ethics committee.

But has your work actually been tainted? Surprisingly enough, it isn’t.

Numerous research studies have shown that incentives, while an effective recruitment tool, do not affect response quality. Papers by Cantor, O’Hare and O’Connor (“The use of monetary incentives to reduce nonresponsive in random digit dial telephone surveys,” 2008); Singer and Kulka (“Paying respondents for survey participation,” 2002); and Singer and Couper (“Do incentives exert undue influence on survey participation? Experimental evidence,” 2009) all offer evidence to this effect.

So yes, money does talk. Money just doesn’t impact what is ultimately said.

Building ethics into your research process

In order for incentives to be considered ethical, they cannot override the principles of freely given and fully informed consent. As such, participants should know before they start the research that they can withdraw from the study at any time without losing their payment. Additional guidelines, as suggested by David Wendler, Jonathan E. Rackoff, Ezekiel J. Emanuel and Christine Grady in their 2002 paper, The Ethics of Paying for Children’s Participation in Research, include:

  • developing clear guidelines for when and how payment will be made;
  • ensuring you have provided clear and explicit justification for paying participants, to be given to the ethics committee;
  • ensuring that participants who choose to withdraw from the research will still receive payment;
  • carefully reviewing whether there is a chance that people are consenting because of payment and not because they wish to take part; and
  • developing a general policy on describing payments and incentives in the consent process.

 

The final take-away? The use of cash payments as an incentive to participate in a market research project is a great way to encourage higher levels of engagement, reduce administrative costs and alleviate operational hassles, without having an unintended impact on the quality of your responses.

So what are you waiting for? Go ahead and make Rod Tidwell happy – show ‘em the money!

Posted in Consumer Research, Data Collection/Field Services, Market Research Best Practices, Market Research Findings, Market Research Techniques, Marketing Research Resources, Online Surveys and Research, Research Recruiting | Comment

Does your tracking study account for a sampling bias?

Editor’s note: Joe Hopper is the president of Versta Research, Chicago.

The next time you analyze the results of your customer satisfaction or brand loyalty tracking study and you notice an upward or downward shift, ask yourself this: Is it groupreasonable to think that certain customers – either the happy ones or the unhappy ones – were more willing to give you their opinions than the other group?

If so, your results may be an artifact of non-response bias, and it may be a problem that is far more common than we think. Consider this conclusion from a study of political polling by Andrew Gelman, a prominent statistics and political science professor at Columbia University:

[We conducted] a novel panel survey of 83,283 people repeatedly polled over the last 45 days of the 2012 U.S. presidential election campaign. We find that reported swings in public opinion polls are generally not due to actual shifts in vote intention, but rather are the result of temporary periods of relatively low response rates by supporters of the reportedly slumping candidate. After correcting for this bias, we show there were nearly constant levels of support for the candidates during what appeared, based on traditional polling, to be the most volatile stretches of the campaign. Our results raise the possibility that decades of large, reported swings in public opinion – including the perennial “convention bounce” – are largely artifacts of sampling bias.

So what’s a tracking study manager to do?

  1. Always examine the sample composition carefully. Compare personal and business demographics of your respondents from wave to wave to ensure consistency and/or to ensure that any changes reflect real changes in the population being sampled.
  1. Weigh the data on strong correlates. This is what Gelman and his colleagues did to correct for the hypothesized bias they were seeing in response rates for their data. If you know from previous waves, for example, that women give you better scores than men, track the response rates by gender, then weight and adjust the data at the back end.
  1. Caveat your conclusions. Remind your management that tracking opinions over time is no easy task, not even for high-budget, high-profile pollsters who track voting intentions during presidential campaigns.

In short, don’t rest easy just because the fieldwork team says they got the required 1,500 interviews for the current wave of your tracking study. Instead, do the difficult work of analyzing whether the samples are really comparable over time and then make smart statistical adjustments to compensate.

Posted in Brand and Image Research, Consumer Research, Customer Satisfaction, Data Collection/Field Services, Data Processing, Market Research Best Practices, Statistical Analysis | Comment

Tech update: What the Apple Watch means for MR

Isaiah Adams is the manager of social media development at marketing research and analytics firm Optimization Group, Mich. This is an edited version of a post that originally appeared here under the title, “What the Apple Watch means for market research.”

Smart watches are nothing new. They even date back to as early as 1972. On Tuesday, Apple’s highly anticipated iPhone 6 launch party unveiled their “next big thing” – the Apple Watch. Other powerhouse companies such as Samsung, Sony and Motorola are already players in the smart watch space. So why are people flipping over cars in the streets with excitement over Apple’s latest announcement? Besides the fact that Apple has an incredible track record for creating products that revolutionize our daily lives, Apple’s latest release is exciting because it shows us that they still understand what it takes to make “magic” happen.app

When the iPhone was first released it was not great because it had a clean design, intuitive user interface and new apps; but rather it furthered our ability to integrate and sync our lives together. Not only could we now automatically sync our phone’s treasured files seamlessly with our desktop computer but apps were now communicating with each other better than ever before. That’s where the magic happened. Apple gave us the ability to sync what were previously separate worlds into one, unified universe.

As I watched the recording of the unveiling of the Apple Watch, I started to wonder how this next evolution in smart watch technology would impact people on a day-to-day basis and eventually how it might affect market research.

If you’re one who would stop me by saying, “Why are we even talking about this? The Apple Watch is a niche accessory at best,” let me first explain why I make the assumption that this will soon impact people’s daily lives on a large scale.

Yes, the known features of the Apple Watch are not a reason to jump for joy. These features are generally available through different wearables already on the market. What makes this different is Apple’s superior marketing and distributing power. They’ve already begun to leverage this by striking deals with some of the leading health systems, in an effort to diversify their HealthKit.

Apple has a history of defining a category.

Posted in Behavioral Research, Big Data, Business and Product Development, Consumer Psychology, Consumer Research, Health Care Research, Lifecycle/Lifestyle Research | Comment

Why e-com needs to provide true personalization

Editor’s note: T.J. Gentle is the CEO and president of Smart Furniture, Chattanooga, Tenn.

Personalized experiences engage customers. That principle has been well-known to merchants for hundreds of years – maybe even longer – ever since they discovered that learning the names of customers and greeting them personally resulted in repeat business. Learning customer preferences and showing them merchandise that appeals specifically to them results in greater loyalty.

That’s a fairly simple concept, but the idea of shoppingpersonalization is still emerging in the world of e-commerce. Personalization almost always results in increased engagement. However, when interaction is happening between a person and a computer, the challenge faced by retailers is much larger than hiring a smart and friendly sales staff.

The rewards of besting that challenge are great. Web shopping experiences enhanced through prescriptive personalization have been shown to increase conversion rates twenty times, increase revenue per visit by a factor of 22.9 times and increase average time spent on site by 700 percent. And that’s in the current environment. Over time, retailers who fail to personalize their sites will start to see their numbers spiral into decline.

Though personalization is in its infancy, there are already several methods being explored. Choosing the right method is important to optimizing its impact.

Know your audience

Netflix was an early adopter of online personalization. The digital video provider hastened the decline of physical video rental stores by providing quick and easy search for mail-order DVDs and on-demand digital streaming content. But it could not duplicate the experience of browsing shelves at a local shop or getting recommendations from employees. Netflix addressed this shortcoming by providing suggestions based on what customers watched and how they rated the content.

When a Netflix customer rates a movie, an algorithm using a “wisdom of crowds” methodology looks for other customers that rated the movie the same way and then makes recommendations based upon what those customers rated highly. Even with something as subjective as media tastes, this crowd wisdom logic works well for Netflix.

Amazon uses a similar premise for the “you may also like” feature, which provides recommendations based on what customers who follow similar click paths ultimately purchase. This form of personalization works for these retailers because it adequately simulates the experience customers would receive in a physical setting. Simple, qualified recommendations are perfectly suitable for movies and consumer durables.

When to get prescriptive

Things get more complicated with products that customers spend a great deal of time researching and expect knowledgeable retailers to help them navigate. Few people start the search for a product like furniture with a clear idea of what brand, style and color they want. They visit stores and look at what appeals to them, talking to sales staff about their preferences, budget and expectations. Successful stores hire salespeople who listen carefully to customers and lead them to products likely to appeal to them and fit their needs.

Since online shopping journeys are entirely self-led, this puts e-commerce at a disadvantage. A personalized shopping experience cannot be effectively duplicated with a “wisdom of the crowds” approach because:

  • stylistic taste is only one of several components that guides a purchase and
  • the complexity of products offered requires expert knowledge to create meaningful recommendations.

Achieving personalization for furniture product categories relies on robust customer and product knowledge equal to what a seasoned salesperson is capable of delivering. The best way to extract customer preferences and match them with product attributes using an algorithm is through prescriptive personalization – combining expert product knowledge with information about what individual customers prefer.

Profiling customers

In a brick and mortar retail environment, sales staff can learn about customers by engaging them in conversation and asking questions, as well as looking for body language and other hints to help guide the experience. Web sites have not traditionally engaged visitors in this way, but it is possible to ask customers questions and store their answers in a database tied to their accounts. This is the first step in prescriptive personalization.

By offering an incentive, retailers can draw customers into taking online quizzes that classify them into a specific customer segment. On SmartFurniture.com, customers can take a short “this or that” quiz that simply asks them to make a selection from three images. After answering just ten questions – which most customers can easily do in less than two minutes – an individual profile is created that indicates stylistic preference, budget, size constraints and lifestyle.

Classifying products

Once customers are properly segmented, the personalization algorithm can begin matching them to products most likely to fit their needs and wants. To do so, however, requires exhaustive quantification of each individual product’s attributes. Building this data set requires a team of experts to break down each product and assign numeric ratings to features such as style, build quality, materials, size, etc. Accuracy of matches between customers and products increases with the level of granularity associated with product attribute quantification.

Because they are based on specifically targeted questions and expert analysis, the intricacies of the customer and product profile databases that result from prescriptive personalization eclipse those that are possible using a wisdom of crowds approach. This creates the specific, meaningful product matches that are appropriate for larger-risk purchases and those for which a curated shopping experience is expected.

The evolution of personalization is advancing to machine learning, with algorithms that are capable of analyzing the relationship between shopping journey click paths and conversions. Paired with available data from inbound referring links and IP information, it is likely that fully curated prescriptive personalization experiences will become possible without the need for customer quizzes in the near future. That level of precision will further increase shoppers’ experiential expectations.

Online personalization is becoming more scientific and easier to institute, with technologies that are more reliably duplicated than brick and mortar personalization. The time for static Web sites has passed and the path forward is through highly personalized Web-based shopping.

Posted in Advertising Research, Behavioral Economics, Consumer Research, Customer Satisfaction, Retailing, The Business of Research | Comment

Is MR standing still?

Editor’s note: Jeroen Rietberg is the director at analysis and reporting company Intellex, Netherlands.

There is no denying the fact that the market research industry is changing and changing fast. There are those who claim that the industry might even cease to exist as technology advances. Big data, mobile, strategic relevance, signdata protection and survey quality are just a few items on a long list of factors that might reshape the industry over the next three to five years. In order to identify and grasp these changes and processes, but also to be able to predict what kind of changes there are to come, we decided to set up and maintain an ongoing discussion about the future of market research. In this article we outline what steps we’ve made to start and keep this discussion going.

Inertia in the industry is being seen as a big problem. Merriam Webster’s Collegiate Dictionary defines inertia as ‘indisposition to motion, exertion or change.”

During Marketing Week Live (formerly the Insight Show) in London Intellex spoke to some 50 market research professionals about their ideas on the current challenges and future of market research as an industry. Based on these opinions, we found out that this resistance to change is a real issue in today’s MR industry.

Gathering insights

“Research agencies don’t seem to grasp that, with technology advancing the way it is, there will come a time when we don’t have to ask questions anymore.”

“Big data is just another imploding buzz word.”

Two random quotes picked from the many we collected during the Insight Show in London. As you can tell from these quotes, opinions vary wildly.

The fact that market research industry is drastically changing is one of the few points that a majority of the people we spoke to, actually agree on. The only other almost unanimous conclusion that we found, is that no, they don’t think the industry is ready to face these changes.

The quote that probably summarizes the collected opinions on the industry best was, “The biggest issue with the MR industry is its inertia.” There is a shared worry that the industry, in spite of recognizing the changes in the market, is somehow unwilling or incapable to adapt.

Interestingly enough, the biggest challenges market research professionals see for the coming three to five years are only partly technology driven. Big data was mentioned, of course, as well as the advance of mobile platforms and data protection. But the challenge that was mentioned most often was the strategic relevance of MR in combination with data quality.

“People are tired of market research.”

“I’m not confident about the quality of work of MR agencies.”

The conclusion is that not only research buyers but also research providers question the long-term relevance of the industry in the context of the upcoming changes. If a majority of our interviewees worry about relevance and don’t feel the industry is ready to cope with the upcoming challenges, it is about time we start a collective brainstorm about how to tackle the future. We must take one step at a time and keep inviting the MR professionals who are not indifferent to the future of the industry to also join the discussion and share their thoughts.

 

Posted in Big Data, Public Opinion/Social Research, Qualitative Research, Quantitative Research, The Business of Research | Comment

Social data: An interview with eDreams ODIGEO

Editor’s note: Europe’s eDreams ODIGEO is the world’s largest online travel company in the flight sector and the largest publicly traded European e-commerce company by profitability. Emilie Rose, international client success director at Bazaar Voice, Texas, recently had the chance to sit down with Amaryllis Liampoti, Group Head of SEO at ODIGEO Barcelona, to learn how their team is gathering, analyzing and leveraging user-generated content to improve their business. This is an edited version of a post that originally appeared here under the title “Using social data in the travel industry: an interview with eDreams ODIGEO.”

What sort of data are you able to glean from reviews?travel

For Best Airlines we are able to pull an overall score based on a 1-5 rating that travelers provide post-travel. This overall ranking is a combination of review factors which include: cleanliness/condition of the aircraft, space between seats, in-flight entertainment, air steward service, check-in/boarding, traveling with children, luggage handling, value for money, VIP lounge, etc.

For Best Airports we also pull an overall score based on the same 1-5 scale and we also provide airport ratings by categories like shopping, bars & restaurants, waiting lounges. We are also able to show the contrary, using the worst rated airports and providing customers with a ranking of the Worst Airports in the World.

How have review trends impacted your business decisions?

Because we understand the importance of showing reviews to our customers, we have created a technological infrastructure across our pages to be able to have better visibility and easier access to these reviews. For example, we have included schema.org structured data so that searchers can see ratings even before they enter the Web site.

What are the toughest challenges in converting social data into usable information?

We have over 30 Web sites that we collect reviews for but obviously our core Web sites have a higher amount of reviews. When creating global content studies the challenge is to present the data in a way that does not just focus on these core markets. Another challenge is the truth behind the matter that statistically clients that have had a negative experience with an airline or at an airport are more likely to share their experience than those that traveled issue-free. We must take this into account as we need to show the most realistic sentiments, both good and bad.

How do you measure the ROI of your efforts?

We measure the ROI on our efforts by looking at many factors, but three are key: social media engagement with our content studies, online value through high authority Web sites linking back to the pages created to host the studies and also the offline value through PR.

What advice do you have for someone who wants to make social data a bigger part of decision-making across their business?

Companies that wish to make social data a bigger part of decision-making across their business should create a work flow where the social data is not only collected and published, but rather digested and transformed into marketable actions. These marketable actions should be creatively presented both in the form of data-analysis studies and display of social data on the Web site to make it accessible and attractive to customers.

How do you get executive buy-in for your social or data programs?

We know the importance of having unique content site-wide and we have done many A/B tests that prove that conversion is positively affected when social data is present. Approval is a no-brainer when increased revenue for a company is the outcome.

Do you have any tips on working with people that rely on intuition and experience over data?

It is important to combine both intuition and experience with data. Intuition and experience allow us to create human-oriented products, but the data we use to analyze ideas formed from intuition and experience is the proof to show if an idea is working or not for what we want to achieve. For example, as an e-commerce company we obviously are interested in higher conversions, we rely on intuition to implement new ideas to set us apart from the competition and the data to see if we are achieving positive monetary results.

How important is the user-generated content topic especially for your specific industry? (Emotions, …)

In the travel industry user-generated content is key. It is true that price is also a key factor for travelers, but also safety, comfort, quality and value for their money when planning a trip. For example, if travelers see that previous trip-goers have had a bad experience with a certain airline and there is not a large price difference to choose a competing airline for the same trip then they will go with the higher rated airline.

What are your future plans regarding social data?

Our plans for the future regarding social data are to provide more content studies, like Best Airlines and Best Airports. We are also in the process of providing our worldwide customers with localized opinions. For example, if you are buying on eDream.co.uk, you will only see reviews from our British customers. Into the future we are also looking into basing our product offering on real-time suggestions from reviews and tapping into the power of our peers across social networks.

Posted in Consumer Research, Customer Satisfaction, Data Collection/Field Services, Market Research Best Practices, Social Media and Marketing Research, Statistical Analysis | Comment

Mobile technology and data are making a difference in health care

Editor’s note: Maura Keane is the online communication intern at GeoPoll Research, Washington, D.C. This is an edited version of a post that originally appeared here under the title “Mobile healthcare in the world.”

While at a restaurant last week, the guy sitting at the table next to me pulled out a razor flip-phone. I couldn’t believe what I was seeing. Aren’t those in museums now?scatered old cell phones

Mobile technology has come such a long way since its development in the 1970s. In just the past decade the advancement mobile technology has made is astonishing. In the Western world, our smartphones do everything for us: schedule meetings, manage our bank accounts, check Facebook and even pay for our Starbucks. The list keeps going and it seems there isn’t anything our cell phones cannot do. If our phones can do all that, shouldn’t they be able to help us with our health?

Health care has always and will always be an important issue in the world, for good reason. Being active and eating the right food is vital to maintaining a healthy body and protecting yourself from illness. In America, citizens are increasingly struggling with obesity but modern medical and phone technology are advancing every day making it easier to stay healthy. With new technology and apps, our phones can make it easier to manage our health and weight loss, with apps that can calculate BMI, track fitness, or remind you of a diet plan. Tech giants like Google and Apple are pairing up to “reinvent” health care: Apple’s new app, Health Kit, combines all the features offered on multiple apps for monitoring your health in one hub. Apple is also partnering with the Mayo Clinic to notify your doctor if your blood pressure rises above normal levels. It appears a lot of cell phone giants are also joining the health app bandwagon, including Samsung, who has developed a fitness band, the Gear Fit.

In developed nations a majority of health concerns are not life threatening, but when looking at developing nations, access to health care could mean life or death. There is a growing trend in these countries to use mobile phones to improve access to medicine or doctors and educate on general medical knowledge. In Africa, over 80 percent of people own cell phones. App developers are taking advantage of this growing market by creating applications for “dumb” phones, cellphones which have few advanced features. In Zambia, the Ministry of Health is pairing with IBM to improve the health care system through IBM MobileFirst, which will allow health care facility staff in three Zambian districts to use mobile devices to scan barcodes to record and transmit medical stock. Not only will this allow better access to vital medication, but it will enhance the awareness of usage patterns of medications. In Bangladesh, mothers are using their phones to access health information and get weekly text updates on childcare.

This kind of access to health information teaches people the importance of vaccines, check-ups, prenatal care, postnatal care and general medical knowledge and can improve the lives of millions of people. A recent poll ran highlights the importance and desperate need for better health care in Africa. GeoPoll ran surveys in 10 African countries asking respondents “Did anyone in your family need to see a doctor in the last seven days?” Over 52 percent of respondents said yes. Everyone knows that developing countries need better access to health care and drugs and with mobile technology growth brings hope that new apps can provide a solution. The kind of health care access apps provide can change the lives of many people in developing nations and the difference mobile technology will make in these emerging markets will be exciting to witness.

Posted in Big Data, Consumer Research, Health Care Research, Lifecycle/Lifestyle Research, Mobile Interviewing | Comment