Archive for the ‘Charts and Data Visualization’ Category
Wednesday, January 4th, 2012
Given how common mapping capabilities have become via the Internet and smartphones, it is surprising that we don’t see more geographic mapping in market research. Researchers nearly always look at customer demographics, and a key component of a person’s demographic profile is where he or she lives. This data is far more compelling if you can present it visually with maps.
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: (more…)
Tags: Market Research, visualizing data
Posted in Charts and Data Visualization, Data Analysis & Analytics, Future Trends, Market Research, Methods & Tools, Presenting Research | No Comments »
Thursday, December 1st, 2011
Over the last few years we have wondered whether spreadsheet software like Excel will soon make statistics software like SPSS or SAS obsolete.
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: (more…)
Tags: analytics, software packages, statistics
Posted in Charts and Data Visualization, Data Analysis & Analytics, Future Trends, Market Research, Methods & Tools | 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, September 7th, 2011
It's pretty, but it's chartjunk
Turning data into stories involves not just words, but pictures as well. In the world of quantitative market research, that usually means charts, graphs, and tables. Moreover, just like poorly written sentences that often complicate rather than clarify data, charts and graphs in market research too often suffer from “chartjunk,” as Edward Tufte calls it. Any superfluous details, design elements, or decorations that do not tell the viewer something new about the data are chartjunk.
At Versta Research we write a lot of reports. We also revise others’ reports to help our clients find and more clearly present research stories to their management teams. Here are three of the more common chart design mistakes we see and help our clients avoid: (more…)
Tags: charts, Market Research, satisfaction research, stories, visualizing data
Posted in Charts and Data Visualization, Market Research, Methods & Tools, Presenting Research, Turning Data into Stories | No Comments »
Thursday, June 9th, 2011
A good chart is the best way to understand the law of diminishing returns when it comes to sample size. So for our June 2011 newsletter we built an interactive graph for choosing sample size. It’s cool, educational, and useful. Moreover, it will show you just how mind boggling the numbers behind sampling can be. It may even give you more sympathy for the majority of people who just don’t “get it” or believe it when it comes to statistical sampling.
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Tags: charts, Market Research, population, public opinion, Public Polls, Public Relations, Sampling, survey respondents, visualizing data
Posted in Charts and Data Visualization, Data Collection, Market Research, Methods & Tools, Omnibus Surveys, Public Polls, Public Relations, Sampling | 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 »
Thursday, April 28th, 2011
As much as we love numbers, we find ourselves often advising clients against using numeric scales in their surveys. A numeric scale is any response format that asks people to give a number within a certain range to indicate the strength of their feeling or opinion. The insanely popular survey question used to calculate Net Promoter Scores is a good example:
“How likely is it that you would recommend Acme Solutions to a friend or colleague? Please answer on a scale from zero to ten, where zero means not at all likely, five is a neutral score, and ten means extremely likely.”
There are many good reasons to use numeric scales and many types of research for which numeric scales are optimal. The NPS scale is good because it has eleven points with meaningful endpoints and a meaningful midpoint. Research shows that scales like this can be highly reliable and valid, with sufficient variability to allow for sophisticated statistical modeling.
But if your objective is to use survey data for marketing materials, public relations, news releases, or white papers, numeric scales make things difficult. They are not easy to summarize in words, and if you want to use charts that tell quick, compelling stories, you will end up having to do something like this:
A Poor Fit: Pie Charts and Numeric Scales
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Tags: charts, communication, Data Collection, journalism, media, news, omnibus, Public Relations, stories, Survey Design, visualizing data
Posted in Charts and Data Visualization, Data Collection, Omnibus Surveys, Presenting Research, Public Relations, Survey Design, Survey Tips, Turning Data into Stories | No Comments »
Wednesday, August 18th, 2010
At its core, data visualization is about using visual techniques as shortcuts to understanding patterns in data. Some of the newer tools available in common programs like Excel provide an excellent means for visualizing data. This can save you time and it can point you in the right direction for rigorous analysis.
Here is an example from our recent work. We had a working data set with 107 variables. We wanted to know whether we could reduce these down into a smaller set of variables using techniques like factor analysis and scaling. We were planning to use linear regression techniques as well, so we wanted to be aware of any collinearity issues.
Our first step in getting familiar with the data was to run a bivariate correlation matrix. This resulted in a matrix of 11,449 coefficients. High correlations would suggest potential collinearity and opportunities for data reduction. Not so long ago, it was not feasible to review so many coefficients in a single matrix. But now we can use color rules in Excel to create a “heat map” that makes this possible:
107x107 Correlation Matrix with Excel Color Rules Used to Flag Higher Correlations
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Tags: visualizing data
Posted in Charts and Data Visualization, Data Analysis & Analytics, Methods & Tools | 1 Comment »
Friday, August 13th, 2010
Does data displayed in charts and graphs, rather than tables, lead to better decisions? Not according to the latest research reported in this month’s Journal of Marketing Research.
The authors looked at various types of biases that creep into business managers’ decisions when based on data presented to them. They did this by conducting experiments with business school students and managers who are members of the American Marketing Association. Some were presented with numeric data in tables, while others were presented with data in charts or graphs. All tables, charts, and graphs were clear and well-designed. (more…)
Tags: bias, charts, communication, data, Market Research, statistics, stories, visualizing data
Posted in Charts and Data Visualization, Market Research, Presenting Research, Turning Data into Stories | No Comments »
Friday, July 9th, 2010
Telling a story with data is one part finding the right words, and one part finding a compelling visual way to present numbers. Good visualization of data conveys the “big picture” at a glance. At the same time, it includes details so that the audience understands and sees both the whole and the parts. Effective charts also invite visual comparisons so that the viewer sees (without having to think about) the trends and patterns we are highlighting in a story.
We highly recommend learning about theories of presentation, perception, and data visualization, and we are big fans of Edward Tufte’s approach to visual explanations. At the same time, we recommend learning the basics of using simple tools, like pie charts, bar charts, line graphs, and so on. One good source for developing a mastery of the basics is a book called Graphing Statistics & Data: Creating Better Charts, from which we have learned a few tips about using bar charts: (more…)
Tags: charts, communication, data, statistics, stories, visualizing data
Posted in Charts and Data Visualization, Methods & Tools, Presenting Research, Turning Data into Stories | No Comments »
