Closing the Information Loop with Actionable Data

Analyzing survey data and turning it into actionable data is the key to maintaining your current customers and adding to that customer base. But what is actionable data? Basically, actionable data is your survey results input into an improvement program to modify your business and make it better.

In order to effectively transform your piles of information into actionable data and make analyzing survey data work, you need to look at the actual questions you ask on your survey. If you don’t ask the right type of questions your data could be misleading and as a result, you will misuse it with no benefit to your company.

Close Ended Questions

These are simple clear questions that ask a survey taker to rate specific aspects of the products, services and experiences they engaged with. They respond on a numbered scale or check boxes of different graduated measurement to reply to the questions. This type of questioning has two useful advantages.

  • Easy Analyzing: Analyzing the survey results is very simple, since all the data is coming to you as a check mark, number or yes/ no answers. The guess work is taken out of the analysis and ambiguity is kept to a minimum. The simple responses make calculating the results and transposing them into percentile information or mathematical equations very easy.
  • Easy to Take: The actual survey itself is easier for your subject to navigate through. Clicking on responses they identify with is much easier than writing down specific detailed narratives. If it’s easy more people will take it and that will give you more data to use in your growth process.

Open Ended Questions

Open ended questions ask your survey takers to describe something in detail. While analyzing survey data, the more detail oriented the survey answers are, the more focused and exact our improvement efforts can be. The problem is that open ended questions rarely get answered and if they do it’s with one or two words. Not really the detail you were looking for and very misleading if you use it. Open ended questions should be used sparingly and only as an addendum or supplement to the closed question parts.

Filtering and Branching

Two survey construction techniques that, when used correctly, will make analyzing survey data easier by pre-sorting and categorizing certain elements of the survey as determined by you.

  • Filtering: In the survey, it serves the useful purpose of weeding out the subjects that you don’t need results from and lets you focus on subjects whose opinions you want. When it comes to analyzing, you can implement filters like location, age, or whatever to help with the process. This allows you not waste peoples time (including yours) and will increase the amount of useful data.
  • Branching: Similar to filtering, branching just divides up your subjects and sends them down different survey roads, if you will. This allows you to view specific results easily and categorize your raw data. Branching serves as a pre-sorter that will streamline you process for analyzing survey data.

Conduct Interviews: Yes, more surveys. I know it sounds weird but if you think about it, it makes sense. Interviews effectively expand the scope of your resulting data. The pre- and post-survey interview helps to make sure the subjects understand the topic or field the survey is concerned with and they add dimension to the scope of the main survey.

Analyzing survey data and turning it into usable, actionable data will positively effect your business. Invest the resources into well thought out data gathering and analysis programs and reap the rewards.

Steve Jobs’ effect on the market research community

Can Mr. Jobs be credited with inventing the idea of market research?

Well, no!
But he can surely gain credit for shaping the future of how it is conducted! For so long, if you wanted to find out what people thought of your product, the only way was to get out on the street and ask them. Of course, we then moved on to mailing out questionnaires and interviewing by phone, but each of these requires a significant time investment on the part of the interviewee.

With the digital age upon us, things have moved on rapidly and peoples thirst for information seems never ending. High speed connections are everywhere and you are never far from a screen of some kind.

With this technology explosion, researchers have worked hard to keep up, fielding surveys by cell phone based text messages, emails, web pages and any other means they can conjure up. Consumers are encouraged to participate in research efforts through links on retail receipts, direct TV/radio advertising and most recently through the use of ‘QR Codes’ that are placed in magazines, newspapers, on product packaging, stickers and even clothing, encouraging the inquisitive among us to pick up their smart phone, scan the code and follow the link to find out more!

So what, you say, does all this have to do with Steve Jobs? Well, it was only last week that it was noted that “around 92% of Fortune 500 companies are currently testing or using iPads as a corporate solution”. And to make that statistic even more impressive, the iPad has only been on the market for just over 18 months!

Whether it be in the local mall, small town tourist office or at a specialist research event, tablets are the go-to device of the moment for data collection.  Apps are springing up to make this easier than ever and with their portability and ease of use, this trend will only increase.

The unquenchable thirst for knowledge that I mentioned earlier, now seems to be driving more and more people to not only want to collect data via tablets, but also to want the ability to delve in to the data further, to find the nuggets of information hidden within it.  Developers are reacting quickly to this need and in the very near future, it is safe to assume that the number of tablet based survey analysis tools will grow drastically.

And all any of us can really say is: Thanks Steve!

To learn more about how to prepare your survey data for analysis, feel free to download our whitepaper Ten Essential Prerequisites for Survey Data Analysis.

Qualitative Research – Tips on how to use Unstructured Research Data

In my previous blog article ‘mTAB Understands Qualitative Research Needs!’  I discussed the need, or advantages, to utilizing qualitative, or unstructured, data when reviewing research results; now I want to help you learn how to implement this suggestion.

I have always visualized structured response data in my imagination as a city with sky-rise buildings and lots of traffic; there are mathematical equations creating a functioning city and it works as well as we need it to. In my imaginary city I visualize unstructured data as a reservoir of gold in the underground tunnels that the city is built on. Burgeoning cities have a tendency to expand, and expansion will generally follow the basis of the original model, but improvements are made by utilizing the underground reservoir.

Yes, fanciful, I know. Keep following me, structured response data gives you an answer to exactly what you’ve asked, but how did you decide what to ask? Have you based your survey response questions on your desires, or your consumer’s desires? Unstructured data allows for responses that are unsuspected and can lead to great improvements.

Let’s use an example: Car manufacturing. The survey asks for demographics, model preferences, etc. Generally an unstructured data response will be positioned as a means of gathering more information about a previous structured data question; e.g. ‘why did you answer yes to this question?’ This is brilliant because the survey is looking to dig deeper into reasoning, however, the full potential of unstructured data is not being utilized.

To harness the power of unstructured data one must think outside of their normal understandings. If you work in the automobile industry you immediately take for granted the need for automobiles. This assumption is the basis for the rest of your survey. Now, if you realize your previously held assumptions about your field and bring them into question, you may find that reservoir! Survey respondents don’t want to write a book while filling out your survey, so you’ve got to choose your open-ended non structured questions wisely. Some examples may be: why do you drive a car instead of taking mass transit? If money was not an issue what car would you buy, and why? What is the most important aspect of a car in your opinion? If you’ve ever considered fuel-alternative transportation, what factors concerned you? Are there any questions that you would want to ask us?

Asking your customers questions that you haven’t assumed answers to will result in responses that you couldn’t have anticipated, and insight you may have overlooked. By incorporating unstructured data responses in your survey you may just find the seedling of an idea that will greatly improve your product, and also give your customers the satisfaction of knowing that you’re interested in their thoughts.

Please be sure to follow my blog posts regarding qualitative survey analysis.  Keep an eye out as well for text analytic posts that we’re planning to run in the near future.