Archive for the ‘Data Analysis & Analytics’ Category
Thursday, November 3rd, 2011
MaxDiff is a powerful method and it is increasingly popular among market researchers. But it is not always the best choice for measuring the importance of attributes, and here’s why.
Suppose you want to measure the importance of 12 attributes for a new product or service. If you know ahead of time that consumers are going to say that all 12 are extremely important to them, then MaxDiff is an excellent method for differentiating among the attributes so you can focus on the top two or three that matter most.
But what if you don’t know that all 12 attributes are extremely important? Maybe none of them are. Maybe they run the gamut from unimportant to extremely important. The problem with MaxDiff is that it only tells you the importance of attributes relative to each other, but it won’t tell you whether the attributes are important. The MaxDiff model will assign ratio-level numbers so that you can rank and quantify the importance of each attribute vis-à-vis the others. But it will not anchor the attributes in a meaningful way. (more…)
Tags: conjoint, Market Research, MaxDiff, Survey Design
Posted in Data Analysis & Analytics, Market Research, Methods & Tools, Survey Design | No Comments »
Thursday, October 20th, 2011
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:
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Tags: analytics, communication, data, insight, Market Research, stories, tracking studies
Posted in Data Analysis & Analytics, Data Collection, Future Trends, Market Research, Turning Data into Stories | No Comments »
Thursday, October 13th, 2011
Many of us have uneasy feelings when reading statistics that presumably apply to ourselves and our own lives. Often the statistics do not seem to “fit” and seem to misrepresent the lives of real people from which the statistics are derived. It is with good reason that we chuckle when someone tells us that the average U.S. household has 0.64 children in it.
We were reminded of this upon hearing prominent news reports a few days ago that the average household income in the U.S. has fallen by about 10% in the past decade, most of it happening since the start of the recession four years ago. But does that mean most Americans’ incomes are falling? No. Though it is hard not to think so given how the data are being presented and reported.
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Tags: communication, data, Public Polls, statistics
Posted in Data Analysis & Analytics, Presenting Research, Public Polls, Turning Data into Stories | No Comments »
Thursday, September 15th, 2011
MaxDiff is a survey method used to measure the importance of product features. Subsets of features are presented, and respondents are asked to select which feature is most important and which feature is least important. Its advantage over other techniques is that by forcing a choice from among multiple features, it more strongly differentiates the features if customers are prone to say that all features are important or attractive.
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Tags: conjoint, Market Research, segmentation
Posted in Charts and Data Visualization, Data Analysis & Analytics, Market Research, Methods & Tools, New Products and Innovation, Presenting Research | No Comments »
Wednesday, August 31st, 2011
Monty Hall in Let's Make A Deal
The hardest part of quantitative market research is not that it involves numbers, math, or even statistics, but that it involves complex problems in probability.
Over the past several years, psychologists have been documenting how difficult it is for us humans to solve even “simple” probability problems. One fascinating example is a puzzle known as the Monty Hall dilemma based on the 1960’s game show Let’s Make A Deal. Monty would offer his contestants three doors to choose from, one of which had a valuable prize behind it. After the contestant chose, Monty would open one of the other two doors, deliberately choosing one that had no prize behind it. Then he offered the contestant an option of staying with the original choice, or switching to the other unopened door. Which should the contestant do? (more…)
Tags: conjoint, data, Market Research, mathematics, Sampling, statistics, stories
Posted in Data Analysis & Analytics, Market Research, Presenting Research, Sampling, Turning Data into Stories | No Comments »
Thursday, July 28th, 2011
An issue we continually struggle with at Versta Research is how to automate the research process and leverage new technologies without losing the essence of what good research does. Good research does not report data, build charts, or generate dashboards. It learns, answers new questions, interprets data, and helps users focus on information and findings that are relevant to their needs.
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. (more…)
Tags: data, insight, Market Research, open-ends, qualitative research, survey technology
Posted in Data Analysis & Analytics, Future Trends, Market Research, Methods & Tools | 2 Comments »
Thursday, July 14th, 2011
How statistics are calculated and presented has a huge effect on how audiences interpret information and make decisions. A recent study about medical decisions based on drug efficacy data highlights the critical importance of how you turn your data into stories, no matter what industry. The research shows that different stories, all of them true and all of them based on the same data will lead to sharply different assessments and decisions. An article in the New York Times summarized one scenario tested by the researchers:
If your doctor tells you that highly reliable studies have shown that taking a certain pill will cut your risk of getting a serious disease in half, would you take it?
Suppose he adds that the risk is 2 percent for people who do not take the pill, but your risk will be reduced to 1 percent if you do. Would you still take it? And what would you do if he told you that only one of every 100 patients who take the drug will actually benefit from it?
The doctor could have said any of these things, all truthfully, because they are just different ways of describing the same data. (more…)
Tags: communication, data, Market Research, research, stories, visualizing data
Posted in Data Analysis & Analytics, Market Research, Presenting Research, Turning Data into Stories | No Comments »
Thursday, July 7th, 2011
Versta Research just hit a magic number: 100. That’s the number of articles we have written to help our clients and their colleagues keep abreast of important trends in market research. If your market research supplier is not providing ongoing thought leadership in design, methods, and analytics, then what are the chances they are bringing ongoing and deep insight to your specific research needs?
To celebrate, we’re serving up a sampler of our five best articles. How did we decide they are the best? Our clients told us. These are the articles that they write to us about, forward to their colleagues, and for which they return to our website time and again. These are also the articles for which we get requests for print-ready PDF versions. (Just let us know if you want one!) (more…)
Tags: communication, conjoint, Market Research, product innovation, research, statistics, stories
Posted in Data Analysis & Analytics, Future Trends, Market Research, Methods & Tools, New Products and Innovation, Turning Data into Stories | No Comments »
Saturday, May 21st, 2011
We like this cartoon because it highlights the unrealized potential of really smart research, but also the potential perils of research gone bad.
The cartoon brings to mind three lessons worth pondering:
- Customer satisfaction research is often “not fun”—but it can be
- Internal data can be a goldmine of insight and there is often a lot of it lying around
- Ethical considerations dictate that just because research can be done does not mean it should be done (more…)
Tags: data mining, ethics, insight, satisfaction research, tracking studies
Posted in Data Analysis & Analytics, Funnies, Market Research | No Comments »
Thursday, May 12th, 2011
We are often surprised by the number of senior researchers in the market research industry who never touch raw data. Often they don’t even have the tools, since “data processing” is outsourced to lower levels or other countries. It is surprising because we almost always engage in work where getting into the data and puzzling over anomalies or hypotheses yields much deeper insight.
Here is an example of how critical it can be to look closely at your data, and in this case, very early in the data collection process. We launched an online survey last week and got reports back from our sample supplier that incidence was just one-third of what we expected, which would have serious feasibility and cost implications.
But once we looked at their report portal, we saw that for every qualified respondent completing the survey, two qualified respondents quit before finishing. That’s an unusually high ratio of “suspends” as we call them. So what was the problem? Were we just getting lousy respondents who did not want to seriously participate in a survey? Was the survey was too difficult, tedious, boring, or confusing? One source of answers (rarely examined) is to look at the data question by question to identify where in the survey people are quitting.
The story in this data: Something is wrong with your survey
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Tags: data, Data Collection, data quality, insight, research, stories, survey, survey respondents
Posted in Charts and Data Visualization, Data Analysis & Analytics, Data Collection, Methods & Tools, Survey Design | No Comments »
