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.