Of course gathering information and insights from customers, potential employees, and targeted demographic groups is important to understand their points of view about your company and products.
And what’s one of the most effective ways to do this? Ask questions of course – whether in person, on phone calls, or online surveys.
Open-ended questions are usually the most valuable way to get the data you need because they provide more detailed information. In this post, you’ll learn everything there is to know about open-ended questions, from how to write them to analyzing them for fine-grained insights.
Open-ended questions are questions that can’t simply be answered “Yes/No” or with a fixed or multiple-choice response. Open-ended questions are worded to require an explanatory response in order to find out new, often subjective, information from the responder in their own words.
You ask open-ended questions when you require more than a one-word response. Open-ended questions often include “Why?”, “How?,” and “What do you think?” – to elicit descriptive responses that explain the respondent’s point-of-view – and to avoid shutting down discourse.
Close-ended questions are questions that can only be answered with one of a preset number of responses: “Yes/No,” predefined multiple-choice options, or scaled, e.g., “On a scale of 1 to 10 how happy are you with this product?” Close-ended questions gather quantitative data.
Open-ended questions, on the other hand, gather quantitative data. They lead to more detailed and valuable information because responders are using their own language to explain their ideas and feelings. Open-ended questions can lead to free form answers and actionable insights that the questioner may have never even considered.
One common example of a survey with both close-ended and open-ended questions is a Net Promoter Score (NPS). It’s used to calculate customer loyalty from a simple close-ended question: “How likely from 0 to 10 are you to recommend [this product or service] to a friend or colleague?”. Then, there’s the option to follow up with an open-ended question, to dig into the details: “Why did you choose the number you did?”
Open-ended questions are ideal for customer surveys to better understand the voice of the customer (VoC) and follow the entire customer journey. They can help businesses find out:
What does your business already do successfully that makes customers happy? Finding your consistent strong points can maximize marketing and increase sales.
It may be harder to face than the positive, but no one knows the pain points of your business better than your customers. You just have to ask. In fact, leading product managers say that over 50% of their new products and features are motivated by customer feedback.
Why are customers leaving your company or where specifically have you failed? Maybe you simply promised too much. Improve customer retention by finding out what you can do to meet their expectations – which is especially poignant when it costs 5 times more to acquire new customers than to retain existing ones.
In a nutshell, open-ended questions are better than close-ended because you:
Now for some tips on how to ask open-ended customer survey questions:
While negative feedback may be harder to swallow, it’s usually much more useful to guide you to necessary changes. And when you receive negative responses, it’s important to close the customer feedback loop by letting customers know you’ve implemented changes or are simply acknowledging their concerns. Just letting your customers know you’re listening is a huge step toward keeping them happy
Don’t ask questions that lead the respondent in a particular direction. Don’t assume you already understand your customers’ points of view. That’s the whole purpose of open-ended questions. You want candid, unvarnished opinions.
Nail down your questions to only the information you need to find out, or it could lead to survey fatigue and respondents will just want to get it over with – leading to bad data.
Think about how you can word your questions to maximize the information you’re likely to receive from the responses.
Below are some examples of open-ended vs close-ended questions:
It’s clear that open-ended questions offer more information and more in-depth results. But they’re harder to analyze, so a lot of companies stick to close-ended questions that can be calculated easily in spreadsheets. However, text analysis with machine learning has changed the game.
SaaS tools, like MonkeyLearn, can analyze thousands of surveys – and all manner of customer feedback – with machine learning, so you don’t have to spend dozens (or hundreds) of hours on manual survey analysis. Just four steps to getting real, actionable insights from your open-ended questions:
Online survey tools, like SurveyMonkey, Typeform, and Google Forms simplify the process of creating and sending open-ended surveys. They offer easy-to-use templates, so you can customize your surveys with just a few clicks.
With online survey tools, you can output your customer feedback data to a CSV or Excel file to set it up for automated analysis. From there, you just need to do a little data cleaning, so that machines can process it.
Here’s where we really get to see machine learning at work. MonkeyLearn can easily be connected to survey tools via the MonkeyLearn API, to help automate the data analysis process. Or, via Monkeylearn’s integrations with Zapier, Zendesk, and Google Sheets. Once you’ve connected MonkeyLearn to your data, you’ll need to choose the type of analysis you want to perform:
Sign up to MonkeyLearn to discover other types of text analysis you can perform.
Data visualization tools, like MonkeyLearn Studio, show your results in a striking, easy-to-understand visual dashboard, so you can see your fresh insights in broad strokes or minute detail.
Check out the MonkeyLearn Studio public dashboard and click around to see how it works. It’s a powerful, all-in-one tool to take you from data collection to analysis to visualization, all in a single dashboard.
It’s clear that open-ended questions and surveys can help dig into customer feelings and opinions much deeper than simple “Yes/No” or multiple choice questions. The analysis is also much more complex, but machine learning text analysis tools, like MonkeyLearn, can walk you through the process to save time and money.
And once you have your tools set up in MonkeyLearn Studio you can analyze your open-ended responses constantly and in real time for immediately actionable insights.
Take a look at MonkeyLearn’s suite of text analysis tools to see what you can do beyond aspect-based sentiment analysis. Or request a demo and we’ll be happy to walk you through how to analyze your open-ended questions.
January 11th, 2021