More Is Not Always Better in Surveys

Having trouble getting responses to your survey?

In a MarketingProfs.com article, Dean Wiltse tells us seven rules for achieving higher online survey response rates. One of the rules is:

Rule #4: More is not always better

Many organizations believe the more questions they ask, the more measurable the results will be. However, the reality is the exact opposite. The more questions asked, the less focused and thoughtful survey responses are and the more survey takers rush to exit.

Instead of asking every possible question under the sun, survey designers should keep the survey focused and to the point.

Survey administrators should bear in mind that to get a solid response rate the number of questions should not exceed 30.

I'm even more radical. I recommend limiting the number of questions to 12 in most cases.

Comments

Joy said…

Good points Roger. I even suggest getting it down to 5 questions if you can.

Sadly, we've done some surveys that give us completely useless results. We could have cut 1/2 the questions and gotten just as much out of them. There is more on this here - (http://www.seilevel.com/messageboard/showthread.php?t=617)

Tue Dec 11, 11:47:00 AM 2007

Why Spreadsheets Suck for Prioritizing

The Goal As a company executive, you want confidence that your product team (which includes all the people, from all departments, responsible for product success) has a sound basis for deciding which items are on the product roadmap. You also want confidence the team is prioritizing the items in a smart way. What Should We Prioritize? The items the team prioritizes could be features, user stories, epics, market problems, themes, or experiments. Melissa Perri makes an excellent case for a " problem roadmap ", and, in general, I recommend focusing on the latter types of items. However, the topic of what types of items you should prioritize - and in what situations - is interesting and important but beyond the scope of this blog entry. A Sad but Familiar Story If there is significant controversy about priorities, then almost inevitably, a product manager or other member of the team decides to put together The Spreadsheet. I've done it. Some of the mos

5 Ways Companies Make Product Decisions

In the last blog entry, we reviewed the four problems that companies face, or are trying to overcome, as they make product decisions . Now we'll look at the ways that most companies make their product decisions. Companies that develop, market, and sell products and solutions make strategic and ongoing tactical decisions. They decide what features to include in their products, what messages they will use to communicate the value of their products, what marketing tactics they will use, what prospective customers they will target, and many day-to-day choices. Whether or not these decisions are deliberate or ad hoc, most companies use some combination of the following ways of making product decisions. (A downloadable "map" that summarizes the product decision landscape is included at the end of this article.) Customer Wants Product decisions based on feature requests, focus groups, and what prospects and customers say they want. Companies are selling products to

Is Customer Development Pseudoscience?

The “Science” of Lean Startup Lean startup practitioners embrace the scientific method, seeking the "truth" about what business model and strategy will lead to product success. We do so by: Formulating hypotheses Crafting and running experiments to test them Learning from the experiments Iteratively feeding our learnings back into revised hypotheses Sounds pretty scientific, at least in spirit, doesn't it? Yet this process actually neglects a key ingredient in the scientists' mode of operation. To identify what’s missing, let’s examine “customer development”. Customer Development Steve Blank is one of the pioneers of the lean startup movement. He introduced into the lean startup lexicon the term “customer development”. Customer development consists of sessions and interactions with customers to test hypotheses. For example, a product manager might interview a prospect, asking if she agrees with the product manager’s hypotheses about the problem

Cauvin

Search This Blog