Personas Are Fake Customers. Here’s Where They Come From and Why They Are So Useful.
Personas are fictional representations of customer types, but they reflect the demographics, behaviors, goals, and motivations of people derived from real data.
Why You Need Designer Data
One luxury of doing primary research is that you can get data perfectly tailored to the problem you need to solve. Primary research allows you to design how data will be elicited, and how, exactly, attitudes and behaviors are measured. Hence, you get the insight you need. If you don’t have perfectly tailored data, you…
A Conference with Real Classes You Can Take
Every year I review and suggest summer classes that researchers might consider to learn all the newest techniques for research design and analysis. But for researchers who work in corporate settings, many of those classes are not practical. Who has the luxury of hanging out in Ann Arbor for six weeks to brush up on…
What Makes a Survey Scientific?
Surveys run the gamut from silly to serious, and from sloppy to scientific. Occasionally we do something silly if a client insists (though we generally advise against it). But we never do sloppy surveys, and we hope you never do them either. Lean as far as possible towards rigor and science within reasonable constraints of…
How Random Correlations Ruined a Gender Story
The problem with most business approaches to “analytics” is that they rely on automated, unthinking algorithms. The algorithms scan boatloads of data and generate correlations that are surprising and, therefore, presumably deeply insightful. But in most cases the correlations are not insightful. They are random coincidences, which unfortunately does not stop humans from sharing with…
The Dubious ROI of Customer Satisfaction Surveys
A good friend and client likes to joke during every project: “Remember Joe, correlation does not imply causation.” Well, I thought she was joking. Surely everybody with a job in marketing research knows this? Apparently not. Even professors at fancy business schools seem to forget it, as evidenced by this snippet of an article a…
A Research Technique to Optimize Your Product Mix
We just completed a very cool research project (a concept test) that perfectly demonstrates the power of MaxDiff and TURF analysis. These two techniques can help you make smarter product decisions than other types of concept tests. Here is an overview of what we did and why it was so powerful. We asked consumers to…
Don’t Be Fooled by Big Numbers
Suppose you could have a neural network machine-learned algorithm that is 91% accurate in predicting who will buy your product and who will not, just with a computer facial scan. Wow—91% sounds amazing! Don’t buy it, and don’t be a sucker for big numbers until you look more closely at the math behind those big…
Your Best Segmentation Tool Is a Salesperson
A cool deliverable of many segmentation studies is a “typing tool” that allows you to input data on just a few dimensions (usually six to twelve survey questions) in order to predict which segment any customer belongs to. It works because even though segmentation algorithms sort through tons of data to find the best clusters,…
Why Segmentation Is Sometimes Useless
Dividing a market into unique segments makes sense. But the statistical methods we rely on for segmentation often result in segments that are strongly differentiated in useless and misleading ways. A recent analysis of Facebook data by The New York Times illustrates this perfectly.