In light of technological advancements, both consumer markets and marketing tools are changing. In this blog post, I will discuss how to use the strengths of open-ended survey questions to stay ahead of your competitors. Finally, while the technology is rapidly evolving, the old way of thinking about unstructured data methodology hasn’t changed.
The benefits of open-ended survey questions
All methodology guides agree on the strengths of open-ended survey questions:
- Allow customers to highlight what they feel is important
- Add details and context
- Insight into customer thinking
- Insights into customer emotions
- Avoids bias that can occur when suggesting answers
- Allow the unexpected to show up
- Address individual circumstances
- Allow the respondent to explain complex issues
- Provide context, especially when correlated with meta data like time stamps and location
- Provide background to structured data like NPS
What does this all mean? Let’s explore a scenario. You are the Customer Experience Manager for a chain of sandwich shops. You want to assess if your customers are happy with the service you provide and you also want to catch any issues quickly. You can ask your customers “How friendly was your waiter on a scale of 1 to 5?”. However, it’s best if you avoid “Did you have a stomach ache after you ate our sandwich?”. How can you know about an issue without asking about it? You need to let your customers mention what is important to them. In a survey, only open-ended questions can achieve these goals.
How to use open-ended questions to stay competitive
Here is a list of challenges that businesses today face when optimizing their customer experience and how open-ended question can help.
Your customers expect your company to adapt quickly to new trends. How can you know about all the trends if you don’t listen to them? Let them tell you directly.
Low entry barriers
A lot of markets are changing because they are becoming more accessible. This means that very small companies and even individuals might be competing with you. As a medium/large organization, you are expected to provide a spotless experience. But that also means having a consistent experience across vast geographies and long time periods.
Most markets are now mature, with little differences between competing forces. The superior experience might be the only real differentiator.
Communication and distribution channels are getting increasingly diverse and therefore complex to manage. It’s easier to pinpoint how the customer was interacting with your brand by letting them give you the relevant details.
Expectations being treated as an individual
You may have invested a lot of time and effort assuring your customer that they are an individual to you. Surely you can’t just send them a set of standard questions you ask everyone?
Help explain the why
You’ve measured everything diligently. Well done! Companies often have difficulties getting here. But do you know why you’re doing well/badly? Does the data show how to improve? Where to invest your resources? Data from open-ended questions can show you exactly where the weak and strong points lay. This is especially useful when measuring your company’s NPS.
Technology has made open-ended survey questions accessible
In light of technological advancements in text analytics such as artificial intelligence (AI), natural language processing (NLP) and deep learning (DL), it’s important to reassess the scope of using open-ended questions. Most marketing analytics guides will contain the following information on unstructured survey responses:
- Data usable only as quotes
- It takes a lot of effort to analyze responses
- Time consuming
- You can get overwhelmed
- Difficult and complex
- Manageable only for small studies
- Cannot be used for statistically significant insights
- No comparison
- No correlation
- No progression
- Difficult to code
- Difficult to interpret
This list is no longer true!
The only remaining downside of open-ended surveys is that they can affect response rates. This can be mitigated by optimizing the survey experience. For insights into survey user behavior check out my previous blog post.
Modern AI powered text analytics solutions like our product can analyze large amounts of data very quickly and help users identify the insight in the data very quickly.
The power of statistically meaningful qualitative data
It’s a mouth-full, I know. Let’s see what this means for your hypothetical restaurant chain.
You uploaded your data into Keatext and you noticed your sandwiches get negative mentions. You look at the records of the negative mentions of sandwiches: one customer reported there was a bug in the sandwich, another that there was a piece of plastic and so on, soggy lettuce… on average your sandwiches get 30% positive mentions, and 10% negative mentions. But when you filter the data by store location, you notice that the store in NY gets 25% negative mentions regarding the sandwiches. You prioritize to look into this store’s hygiene before it turns into a huge scandal that will shut down your whole chain. Now that would be useful, wouldn’t it?
Are you a survey provider that would like to add text analytics to your survey solution? Check to see if you’re eligible to partner with us.
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