Research Landscape

January 11, 2016 § Leave a comment

We recently had a good question from a CEO who just heard about Adaptive Survey(r) Technology, “Why should I use Adaptive instead of SurveyMonkey or any other tool my people already know?”

One of our advisors, Professor Raghu Santanam from Arizona State University, jumped right in with a short definition of the various uses of research, “There are three basic uses for research…”

  1. Descriptive surveys are backward looking and captures what happened to what demographic in the past. CX or Customer Experience surveys are in this category.
  2. Confirmatory surveys confirm information you already know by taking a current reading. Some of these are tracking over time to see if anything changes – NPS or other tracking surveys for example.
  3. Discovery surveys are future looking where you want actionable insights that lead you to doing something.

Research Landscape V1Adaptive Survey(r) technology falls primarily in the Discovery category. It is used to generate new ideas, innovations or simply unexpected opportunities to delight customers. If you are looking for new and actionable insights in priority order, Adaptive is the right type of tool for you. Adaptive generates new ideas not conceived in a traditional design.

The first and only tool for doing Adaptive Surveys(r) is at GroupInsight.com.

Once you see some results form your discovery survey, you’ll find that Adaptive is also a useful replacement for open-ended questions and collapsing ratings into one Adaptive Question(r) in descriptive and confirmatory surveys too. Many survey can be reduced by 80% using this method; you can turn 30 questions into 5 or 6 using this method. Adaptive surveys require dramatically fewer questions, yet provide more business insights.

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Fear of WOM

March 23, 2013 § Leave a comment

We got this client feedback through our partner about Adaptive Questions where respondents can see responses from others.

“I spoke to the client today and they are excited about the prospect of this project. They have only one concern which I could not address… they are worried about the likelihood of negative comments surfacing and being shared within the survey group, and possibly shared outside the group. “

One of our best long-term customers from TurboTax put this in a most elegant way, “You have to expect negative feedback to make any progress. If you filter it out, you are doing a disservice to your company.” 

I usually like to put both positive and negative people in the same Adaptive Question because we can see how they agree and disagree. Think about how valuable it is to see agreement and disagreement between Promoters and Detractors, happy and unhappy customers. Personally, I prefer to allow respondents to say anything they want because…

  • Bad ideas, negative ideas, complaints don’t usually get seen by very many people because they don’t usually get a lot of agreement because we word questions to get constructive feedback, not complaints
  • Only a small portion of respondents see the negative ideas
  • Only a small portion of customers participate
  • Your mother told you, “If you don’t have anything nice to say, don’t say anything at all.”

Given the sensitivity of some clients such as this one, there are a couple of fairly easy solutions.

  1. Moderate the comments – only allow constructive comments  to be seen. CloudMR has an option to require moderation. Respondents only see the comments you approve. That way we can limit the pool of ideas to positive and constructive improvements. The client will need to give us some guidance which is a part of our process. Downside: If you are not aggressive about approving legitimate ideas during the early part of the fielding process, you could go through all of your sample with just the initial 10 seed ideas.
  2. Separate positive and negative respondents into two Adaptive Questions(TM) – It is pretty natural to get a rating such as satisfaction or likely to recommend before the Adaptive Question. Simply use the built-in logic to get improvement suggestions from unhappy respondents and positive sound bites from happy customers. This isolates the negatives to an extent.
  3. Combine 1 and 2. Adapative Questions are ideal for getting WOM. The analysis will include both general buckets of ideas and individual comments. If you want to WOM for your promotions or advertising, we will ask respondents to identify themselves for the quotes.

Sentiment Analysis

March 15, 2013 § Leave a comment

When we started thinking about text analysis, one of the issues we discussed was sentiment analysis. Lots of people have tried to figure this out and some companies claim a pretty high success rate using algorithms or other techniques.

Our feeling is that language is so complex and that the subtleties of things such as sarcasm make it really difficult to be very accurate. So we took a different approach to the problem. What if we leave the determination of sentiment up to real humans? If we do that, it simplifies the task to finding which comments to read.

CloudMR’s patent-pending algorithm sorts a list of comments in priority order. The comments most likely to resonate with other respondents are sorted at the top. If you want to know sentiment, just read the top comment for yourself. If you are feeling really energetic, read the first ten. Sentiment problem solved…

Adaptive Survey(r)

March 1, 2013 § Leave a comment

An Adaptive Survey® is a market research method that combines qualitative and quantitative research features. This unique combination allows researchers to speed up the research process by gathering ideas and prioritizing them in the same research project.

Adaptive Surveys are offered by CloudMR, Inc. and this blog is related to that company. The benefits of this technique…

  • Systematically gather and prioritize open-ended text in a single project
  • Replace dozens of traditional market research rating scales with a single Adaptive Question™
  • Answer questions you didn’t even know to ask
  • Get higher response rates since Adaptive Surveys® are short and conversational
  • Add structure to unstructured data
  • Prioritize ideas using any representative sample you choose

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