It does not take super fancy (and expensive) mapping software or specialized firms to create accurate, useful, and compelling maps from market research data.  We recently created maps for a client showing where in a three-county region their best customers lived.  Everything we used to make these maps was free and publicly available for download on the Internet.  Here are the steps we used:

1.  Download shapefiles from the U.S. Census Bureau.  These files contain data to demarcate all legal and statistical geographical areas in the U.S. including states, counties, county subdivisions, census tracts, blocks, and so on.

2.  Edit the shapefiles with a program like QGIS.  There are several high quality, free, open-source software packages that you can use to read and manipulate census shapefiles.  We used QGIS, which is a program created and continually developed by the Open Source Geospatial Foundation.

3.  Link customer data to shapefile data in a spreadsheet program.  We looked at the number of customers in every zip code, then linked that data to county subdivisions in the shapefile by using a minimum distance function based on latitude and longitude coordinates.

4.  Plot the data and create the map using R.  R is quickly becoming the statistics package of choice in the academic world.  It is a free “integrated suite of software…for statistical computing and graphics” and can easily turn shapefiles and data linked to those shapefiles into visual displays.

Ultimately we created a heat map that displays customer location data for the three counties, which are divided into more than 50 townships, as shown in the map above, with darker colors signifying more customers than lighter colors.

As always, the ongoing challenge for researchers working with a burgeoning volume of data is how to interpret all that data, synthesize it, and simplify it into a story that is useful to decision makers.  Maps have always been a useful and compelling way to visually present data.  Finding the path to producing them from your data is now easier than ever.

–Joe Hopper, Ph.D.

Spreadsheets have amazingly powerful and often intuitive capabilities.  They have many of the statistical functions we use every day.  Younger people entering our profession rarely know programs like SPSS or SAS, and we see them turning to Excel to generate frequencies, calculate means and proportions, create charts from data, and so on.  The same goes for our customers.  Many do not have statistical software, so when they need numbers and statistics, they often work in Excel.

But Versta Research continues to invest in advanced statistical software rather than doing our work in Excel for three important reasons:

1. Speed and efficiency.  The tools we use are designed to do exactly what we need.  Spreadsheets require more effort to manipulate data, set logic rules, and write formulas that we can otherwise do with just a few clicks.

2.  Leveraging analytical innovation.  Our statistical software leverages the newest techniques in developing areas of statistical theory and applications, especially from software developers like Sawtooth who are pioneers in choice modeling.

3.  Accuracy.  As anyone who has created a moderately complex spreadsheet knows, it is frighteningly easy to make errors in spreadsheets (data errors, sorting errors, formula errors, copy-and-paste errors, cell reference errors, and the list goes on) and it is often difficult to find, detect, and untangle those errors, if indeed they are ever found.

To be sure, Excel is a powerful tool that we use all the time and every day, in part because it can be used in so many creative and flexible ways.  We use it help us track, manipulate, and visualize statistical output, for example.  We also use it as an efficient way to write multiple lines of programming script that we then paste into our statistical programs.  But when it comes to the core of our statistical analysis, we rely on the best-in-breed software tools that continue to outpace the capabilities of a spreadsheet.

–Joe Hopper, Ph.D.

But I can tell them this:  It does get used, so keep doing it.  It allows people like me to bring new insights and new levels of rigor to the practical and sometimes urgent research questions that our customers need to have answered.

The Journal of Marketing Research has just published a special interdisciplinary issue on Consumer Financial Decision Making.  It is hot off the press, so we have yet to read it all.  But in the coming weeks we’ll be reading, reviewing, and using the findings in these articles to bring deeper insight to the work that we do for our customers.

In the meantime, here are the article titles, with links to the authors’ summaries, from the special issue of JMR that focuses on research in consumer finance:

1. Misunderstanding Savings Growth: Implications for Retirement Savings Behavior
2. Earmarking and Partitioning: Increasing Saving by Low-Income Households
3. Increasing Saving Behavior Through Age-Progressed Renderings of the Future Self
4. Winning the Battle but Losing the War: The Psychology of Debt Management
5. Using Loan Plus Lender Literacy Information to Combat One-Sided Marketing of Debt Consolidation Loans
6. Minimum Required Payment and Supplemental Information Disclosure Effects on Consumer Debt Repayment Decisions
7. Leave Home Without It? The Effects of Credit Card Debt and Available Credit on Spending
8. Axe the Tax: Taxes Are Disliked More than Equivalent Costs
9. Once Burned, Twice Shy: How Naive Learning, Counterfactuals, and Regret Affect the Repurchase of Stocks Previously Sold
10. Fear, Social Projection, and Financial Decision Making
11. Microfinance Decision Making: A Field Study of Prosocial Lending
12. Tell Me a Good Story and I May Lend You Money: The Role of Narratives in Peer-to-Peer Lending Decisions
13. Marketing Complex Financial Products in Emerging Markets: Evidence from Rainfall Insurance in India
14. Are Consumers Too Trusting? The Effects of Relationships with Expert Advisers

Need help interpreting and applying these academic findings to the research questions your financial services team has?  Give us a call at 312-348-6089 and we would be happy to help you think about how to bring more insight to your research, and then how to find useful stories in your data that can be put into action.

–Joe Hopper, Ph.D.

Earlier this month Arthur C. Nielsen, Jr. died.  He left behind a giant and reputable market research company and a brand name recognized throughout the world.  The A.C. Nielsen company was started by his father and in its early years tracked the sales of goods through grocery and drug stores.  The company then moved into media tracking and became the authoritative source for measuring audience size and demographics.  Nearly every company with an advertising budget continues to rely on Nielsen data to determine where to advertise and how much to spend.

Nielsen’s legacy is that he demonstrated the value of collecting and tracking data, and lots of it.  Every item we purchase is now logged, counted, and tracked.  Every television and radio show is tracked for how many viewers it has and in what markets they live.  And of course everything we do on the Internet is recorded and tracked.  Even our bodily locations are tracked via GPS or cell phone signals.  Most market research firms today generate the bulk of their revenue simply by collecting, tracking, tabulating, and reporting data.

This important legacy has left us with tons of data, growing at an exponential rate,  and a monumental challenge of how to synthesize it and move beyond mere tabulation and reporting.  The question is, how do we meet that challenge and take Nielsen’s legacy to the next frontier?  In our view, it will involve two key efforts:

1.  Understanding data in much deeper ways and analyzing it with data mining tools, new algorithms, and new approaches that go beyond traditional statistics, including Bayesian analysis, neural networks, and machine-learning techniques.

2. Interpreting and communicating data in ways that are more practical, relevant, meaningful, and useful.  In other words, turning data into stories that real people, real managers, and real businesses understand and can use.

To be sure, much of the research industry is still (appropriately) focused on implementing technologies to better manage, tabulate, and report volumes of data.  But automated tables and charts with ever-expanding levels of detail are reaching their limits of utility.  Versta Research is proud to be on the next frontier, where better interpretation and understanding of data is key.

–Joe Hopper, Ph.D.

Two researchers at the U.S. Census Bureau recently outlined an emerging innovation in survey research that could reverse the trend towards passive, boring, self-administered surveys that characterizes much online research.  The idea is to use internet avatars in real-time interviewing with survey respondents.

Beyond just the heightened interest of having an animated survey, the avatars would be programmed to register and interpret respondents’ verbal answers, facial expressions, and body language through webcams.

Suppose, for example, that a respondent answers a question with detailed information that answers a follow-up question as well.  The avatar would use natural language processing to insert that data into the subsequent question, and then avoid asking the follow-up.  Or if the respondent looks away from the screen and pauses for time longer than is typical, the avatar can offer a rephrased question or a reassuring comment to re-engage the participant and to put him or her at ease.  This type of innovation  could bring many of the advantages of live interviewing back into the realm of internet surveys, which are far more efficient in terms of time and cost.

The use of effective avatar interviewers is at least several years away, however, because it involves not only evolving internet technologies, but also advanced linguistic processing, facial and voice recognition technologies, and so on.  In fact, the sheer technological difficulty of truly replacing human interviewers reminds us of how absurd it is for research companies to make claims about technology replacing higher-order activities in the research process, such as providing analysis and insight.

At least for now, software and services with “actionable insight” buttons generate yet more mountains of data in need of human synthesis and interpretation.  If anything, the role for smart and experienced researchers who can turn all that data into a story is growing.  It is growing for researchers who work on the client side and who have direct accountability to the executives who need data-driven insights.  And it is growing for firms like Versta Research where the highest levels of intellectual and human capital are central to our work.

–Joe Hopper, Ph.D.

one shortcut is to become reckless: to act impulsively instead of expending the energy to first think through the consequences. . . .  The other shortcut is the ultimate energy saver: do nothing. Instead of agonizing over decisions, avoid any choice.

But give the brain a hit of glucose (the basic fuel that runs cell functioning), and our willpower and rational decision-making are restored.

The findings are from multiple experiments over the past decade that relied on a variety of scenarios that both academic researchers and marketing people care a great deal about: selecting (and paying for) options on new car purchases, buying computers, shopping in malls or grocery stores, selecting fabrics for customized products, and making critical financial decisions that involve trade-offs between short-term rewards and long-term gains.

The findings also have implications for all kinds of marketing decisions and strategies.  How many choices should consumers be offered?  How difficult should those choices be?  Should you offer a default or recommended option?  Where in the decision process should the recommended option be offered?

One area in which Versta Research has done a great deal of work is in consumer attitudes and behaviors when it comes to saving, spending, and investing, particularly for retirement.  We all know that few consumers are saving enough.  Most consumers know this, too, but they struggle to make the most effective decisions.  Bombarding them with education and tools seems to go only so far.

Fortunately, many financial services companies are doing a better and better job helping people save and invest more wisely.  In part, they are doing it by taking advantage of our proclivities to “do nothing” when fatigued by choice, though nobody has understood until now why this works.  The recent research cited here offers new insights that may help configure better choices and contexts for financial decision making, in part because it suggests an intriguing link to brain physiology:

Apparently ego depletion causes activity to rise in some parts of the brain and to decline in others. Your brain does not stop working when glucose is low. It stops doing some things and starts doing others. It responds more strongly to immediate rewards and pays less attention to long-term prospects.

So before you are faced with the task of configuring your 401k or making other long-term financial and investing decisions, here are a few tips at least suggested by the research cited here: Be well rested.  Set aside time early in the day when your decision-making abilities are fresh.  Avoid times right after you have made other significant choices or decisions, either at work, when shopping, or in your personal life.  And the best suggestion of all?  Have a cookie with your 401(k).

—Joe Hopper, Ph.D.

]]> http://www.verstaresearch.com/blog/have-a-cookie-with-your-401k/feed/ 0 http://www.verstaresearch.com/blog/smartphones-matter-more-than-cell-phones/ http://www.verstaresearch.com/blog/smartphones-matter-more-than-cell-phones/#comments Fri, 19 Aug 2011 12:47:28 +0000 Joe Hopper http://www.verstaresearch.com/blog/?p=1543 The most recent government estimates of cell phone usage among U.S. households were released a few weeks back, and the pace at which landline usage is disappearing is astonishing.  Here are just some of the numbers:

• Thirty percent of U.S. households do not have a landline telephone
• An additional 16% have a landline telephone, but never or rarely use it to receive calls
• The percentage of households without landlines is increasing by about five to six percentage points each year
• Half of young adults under age 30 have no landline in their homes
• Half of adult renters have no landline in their homes
• Nearly four out of ten Hispanic adults have no landline in their homes

For anyone doing random sample surveys of consumers, the implications are huge.  Methodological purists insist that only phone-based surveys are rigorous, but clearly the biases of phone-based research can be severe, and no doubt they often are.

Putting aside the issue of research methods, however, we believe a more significant issue over the next few years will be the explosive growth in smartphone usage.  Although not captured in government surveys that track phone usage and availability, the Pew center estimates that one-third of all U.S. adults currently own a smartphone, and industry analysts predict that by the end of 2011 half of all cell phones in the U.S. will be smartphones.

Why is this is so critical for researchers?  Because more than any other technology since the widespread adoption of the Internet, smartphones are changing how consumers behave.  Consumers get up in the morning and check media apps before brushing their teeth.  Then while commuting to work or waiting for their computer to boot up, they purchase coupons for goods and services they might never have bought otherwise.  They map and track their locations, and expect product features and services that can anticipate what they need.

Smartphones are important for reasons far beyond narrow methodological concerns about how to execute surveys.  They are important because they are changing the very nature of what we research: how people behave and think, and what they buy, believe, want, and aspire to.  Indeed, just as we nearly always ask our research respondents to tell us their gender, age, and income, we now often ask whether they have smartphones.

Beyond anything else, market research is about understanding people (the verstehen in Versta), which means our focus at Versta is always on the “what, how, and why” of what matters in peoples’ lives in a rapidly changing world.  Smartphones matter in a more profound way than cell phones ever did.

—Joe Hopper, Ph.D.

]]> http://www.verstaresearch.com/blog/smartphones-matter-more-than-cell-phones/feed/ 0 http://www.verstaresearch.com/blog/cell-phones-may-double-your-survey-costs/ http://www.verstaresearch.com/blog/cell-phones-may-double-your-survey-costs/#comments Tue, 09 Aug 2011 14:13:02 +0000 Joe Hopper http://www.verstaresearch.com/blog/?p=1528

These days most researchers agree that if you want to do a random sample phone survey of the U.S. population, you ought to include cell phones.  More than one-quarter of the population do not have landline telephones at home.  Those who do have landline telephones are less likely than ever to answer them, and less likely than ever to participate in surveys.

But it is not easy to include cell phones.  The sampling protocols and the post-stratification weighting become more complicated.  You need to account for a higher probability of cell phone owners being in your sample, because most of them also have landlines.  You can’t use automated or predictive dialing to call cell phone numbers.  You can’t target geography as well, because area codes and exchanges have become mobile.  And people get mad at you if they have to pay for incoming calls, so you need to offer cash.

What’s the bottom line effect on costs for a survey that includes cell phones?  A recent study sponsored by the American Association for Public Opinion Research (AAPOR) documents the following:

The cost of fieldwork for cell phone interviews is double if you don’t screen out those who also have landlines, and more than double (2.6 times higher) if you do screen them out.

Of course if you are surveying the whole population, only a portion of your sampling and interviews will be cell-phone based.  Currently, we recommend that 20% to 40% of interviews be cell-based.  But there are additional professional costs to remember as well, such as purchasing, managing, merging, weighting, and analyzing different types and sources of sample, and training interviewers to work with different sources and types of respondents.

There are still plenty of phone surveys being done that do not include cell-phones, and for many types of studies landline-only surveys produce information that is good enough for what needs to be learned.  But it is getting increasingly difficult for these surveys to achieve true representation and surely their days numbered.

Feel free to give us a call if you need help figuring out the best approach for your research.  We can advise you on the most cost-effective, feasible, and rigorous approaches to getting the data, stories, and level of understanding you need.

—Joe Hopper, Ph.D.

The last couple of weeks we have been working with a group that specializes in coding and tabulating text responses to open-ended questions on surveys.  They have tools and technology that undoubtedly make the process easier and more efficient (we have used those tools, and they are impressive).  They are also have a singular focus and expertise that is supposed to help streamline the process, cut costs, and improve speed and efficiency.

The results have been mediocre at best, even with human coders working the technology and making the critical decisions. They efficiently and accurately coded each response into one or more  buckets.  But they created buckets that give hardly any insight into what the client wants to know.  “What do you love most about this product?”  The coders accurately identified all consumers who mentioned the physical size of the product.  But they lost critical distinctions not only about big versus small, but also about size being a constraint (not enough room for a larger product) versus a preference for how consumers wanted the product to look (an aesthetic choice).  They got the topic right, but did not answer the question in a meaningful way.  So what good was all that coding?

I asked a colleague (highly paid, less efficient) to fix and re-code the data, and I asked her to think not in terms of topics but in terms of answers to questions.  She did, and remarked, “You have an advantage, because you know more about this product and what is relevant to the research than the people (and machines) who did the coding.”

Yes, that’s the point, and that’s the struggle for technology and automation.  Smart researchers who know the right questions and continually think about how best to answer them with data will always have an advantage.  Even when pitted against the best and most efficient technologies, we will always win the insight contest.

There are lots of places where technology is helping us do our work faster, smarter, and at a lower cost.  But no matter what the innovators in tools and technology tell you, it makes a huge difference to have smart people with expertise slogging through the data, deciding how to analyze and present it, and transforming that into a story you can use.  We, at Versta Research, consistently and substantially outperform machines and outsourced labor, which means that you, the client, win as well.

—Joe Hopper, Ph.D.

This year Ogilvy & Mather is launching a unit within its agency that focuses on cross-cultural marketing as opposed to multicultural marketing.  This is an important shift in how to think about multiple markets and segmentation, and consistent with what we at Versta have been seeing in our research for quite some time.

For decades, marketing has focused on demographic segmentation.  Research in particular has focused on understanding the unique needs and specific messages that appeal to women, for example, or to Hispanics, African-Americans, Asian-Americans, or gay or lesbian consumers.  For many companies, this has fragmented their marketing and messaging even when trying to offer the same goods and services that offer the same consumer benefits.

From the perspective of marketing research, one problem has been that analysts tend to rely on “statistically significant” differences to guide them when presenting findings rather than thinking more broadly about substantively important differences.  In our view, statistically significant differences should only be highlighted if they matter within the larger context of the questions being asked and how the data might be used.

Suppose that your consumer study shows that women are significantly more likely than men to focus on customer service as a reason to purchase, whereas men are significantly more likely to focus on the warranty.  Does this gender difference matter?  It depends, and no test of statistical significance can answer that question.  If you find that 93% of women are focused on service versus just 87% of men, it may be statistically significant, but who cares?  You better focus on service no matter what gender your customers are.  Likewise, if you find that 8% of men care a lot about warranties versus 3% of women, does that mean you should begin targeting men with messages about warranties?  Probably not.

While it is critical to segment your customers and understand important differences among them, market research that focuses narrowly on reporting statistically significant differences is doing a disservice.  It may be leading you towards marketing fragmentation rather than truly effective segmentation.

Wondering whether differences among subgroups in your data really matter, or whether an approach focused on commonalities is more appropriate?  Versta Research can help.  We do not supply reports that look like banner tabs, but rather reports that focus broadly and deeply on what the data mean and how it answers your key business questions.

—Joe Hopper, Ph.D.

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