Analyze qualitative survey responses intelligently using AI

Analyze qualitative survey responses intelligently using AI

Introduction

Customer insights are essential for any business. Without them, how would you know what your customers want? And how could you improve your offer? Written feedback is usually the most important source of information to know customers’ exact thoughts and feelings about a service or product.

However, due to the difficulty of extracting meaningful information from text at a large scale, many companies ignore it. The good news is that you can remove this roadblock by using AI. You can better analyze unstructured data such as qualitative, written feedback and use it to improve your business.

This guide will discuss what quantitative and qualitative customer feedback is, why it is important, how to process and analyze survey responses, and how to act on the feedback.

Before we dive in, let’s make sure we’re clear on the definitions.

What is quantitative customer feedback?

Quantitative customer feedback is the type of feedback you can analyze numerically. In other words, you can easily boil down the collected responses to numbers. It is either purely numerical or can be turned into a numerical format. Quantitative customer feedback comes in various forms, some of which you might have already heard of. They include surveys such as:

  • Net Promoter Score, which is used to assess client loyalty on a 0-10 scale.
  • Customer Satisfaction Score, which is usually measured on a 1-3, 1-5, or 1-10 scale. Sometimes it also comes in the star or smiley scale format.
  • Customer Effort Score, or CES, which is a score that rates a user process or user journey on a scale from “very difficult” to “very easy” to complete.
  • And many other types of closed-ended surveys where the respondent needs to select an answer from the list rather than give their own text response.

Some benefits of quantitative feedback:

  • Quantitative feedback is objective. With numerical feedback, nothing is left to your interpretation. For example, if the customer answered the survey with an “A”, then the answer is “A” and there is no need to question it or ask what exactly was meant. With quantitative customer feedback, the only thing the client needs to do is click once on a score that best fits their thoughts and move to the next question. It's easy to collect, collate and scale across different customer types.
  • Quantitative feedback is easier to visualize. Once you collect your feedback, you can easily insert the numerical data into a tool to depict the customer responses. For this purpose, you can even use a free visualization software like Google Data Studio.

However, there is a piece that's missing here, which is the customer's account of their experience and opinions in their own words. This is where qualitative feedback comes into play. Let's discuss what this is and what it brings to the table.

What is qualitative customer feedback?

Qualitative feedback takes the form of non-numerical information that measures customer opinion using surveys. Some popular methods of gathering qualitative customer feedback include:

  • Open-ended surveys, which is when questions don’t contain a list of suggested answers, but only a text box to write out the response.
  • Conversations, such as talking to testers during usability testing of your software, or speaking to a client over the phone.
  • Follow-up, open-ended questions which supplement closed-ended, quantitative surveys. For example, the above-mentioned NPS and CSAT are super important, as they display your clients’ satisfaction and customer loyalty levels on a scale. However, to make the most of your customer surveys, it’s worth asking an open-ended follow-up question to understand why clients scored you the way they did.

Unlike numerical data, qualitative feedback serves as a deep dive into a customer's experiences, sentiments, and feelings. Customers can tell you word-for-word how they feel about their experiences with your business. This brings us to the next question:

Why is qualitative customer feedback important?

The main reason that qualitative customer feedback is valuable is that customer feedback drives business growth. It tells you how you can be better for your clients based on their own thoughts and feelings. Here’s how:

It gives context to quantitative feedback

If a customer gives you a low score like 5 out of 10 in your NPS survey, you can display an open-ended, follow-up question asking them to explain the reason for their score. In the case of happy clients, asking qualitative follow-ups can tell you what they love about you the most. You can  underline your advantages over competitors and apply it to other parts of your customer service experience.

Customers are given the liberty to say what they feel, in their own words

Qualitative feedback surveys feel more personal and human. With these surveys, customers can tell you what they like and what their pain points are. Without the insight that’s provided by qualitative feedback, it would be impossible to know where to focus your attention when it comes to making improvements.

A constant source of product improvement and new feature ideas

With written feedback, customers will often request new features and offer feedback that you had not considered before. Then, you can create products and services to solve this need. This is especially important when you bear in mind that 56% of customers say they have stopped doing business with a company because of poor customer service.

You can become better than your competitors

Many companies do not collect qualitative customer feedback altogether. If they do, they don’t analyze it effectively, at scale, due to a lack of the right tools, time, or resources. Written feedback is hard and time-consuming to analyze when it comes in by the 100s or 1000s. So, it’s not surprising or uncommon that some businesses do not analyze survey responses or gather this data at all.

Potentially, they might be missing out on an important piece of feedback, recurring ideas, patterns, or even market demand.

Gather customer feedback

There are several tools on the market to help you collect feedback from clients. Here are a few ideas:

Typeform

Typeform is an easy-to-use, highly customizable online form builder. It enables companies to create engaging surveys that can be used in many different contexts – from marketing surveys to customer feedback forms. We use Typeform quite a bit in-house and it's what we recommend.

Using Typeform is as simple as dragging and dropping fields from the sidebar onto the page and then adding your questions, images, videos, or other content. Forms created with Typeform look great, are fun to fill out, and save you time.

typeform screenshot for analyzing survey responses

Other form providers:

Google Forms

  • Quick and easy
  • Free
  • Use it for internal purposes or even collecting customer feedback

SurveyMonkey

  • Create and distribute surveys, track responses, view results, and share the survey with others.

JotForms

  • Create a professional-looking form and embed it on your website.
  • Convery PDFs into editable files with company branding

CognitoForms

  • Create the interactive surveys
  • Build, publish, and manage surveys with the intuitive platform.
  • Integrate it with other apps and create reports easily

Formstack

  • Create and send email-based surveys, quizzes, voting forms, and polls to collect customer feedback
  • Track responses in real-time and gather results with the analytics tools.

How to process and analyze customer survey responses

Most companies have a clear idea of what tool to collect surveys with but few have sophisticated ways to analyze the responses...

Levity offers a way to wade through this unstructured data. It saves your company weeks or even months of manual work, giving you the opportunity to take advantage of valuable customer insights. Using Levity, you can perform several analyses without writing a single line of code. Some options include:

  • Automatically detecting positive, negative, and neutral answers and sending them to the team that will find this information most useful.
  • Understanding the intent and topic of the feedback.
  • Filtering for urgency, allowing you to immediately react to written feedback when needed.

The tool classifies a respondent's free-text feedback using Natural Language Processing (NLP) which enables you to route feedback to different destinations depending on the nature or sentiment.

For example, negative feedback about the product could go to the product development team, and positive feedback about service received could go to the customer success team.

analyzing customer survey responses with Levity

With Levity, you can feed in your raw, qualitative customer feedback data, and have our AI-powered classifier (or 'block') understand this feedback. You could set up a workflow ('flow') which then categorizes the feedback based on sentiment, and even route it to the relevant department.

You can try it out for yourself in this demo below.

Now let's find out how to make this yourself! First, feed in your Excel spreadsheet or Google Sheet.

Import labeled data into Levity from Google Sheets or Excel

Then, you'll find an empty AI block, which you'll begin training after you've added all your data. The higher the quality of your data, the better your model will be trained (and the more able to cope with the task at hand with a high degree of accuracy).

You'll see the 'add data' button - be sure to click this and let the uploading commence.

how to process customer feedback responses using AI

After that, choose your sources and 'add organized data'.

add data and start training your ai block

On the data upload screen, ensure that the correct columns have been mapped to the correct input, such as 'data' (the contents of your sheet) and 'label' (what you are trying to classify).

bulk add rows to train your AI on processing survey responses

Then the fun part - view the data once uploaded.

view your data uploaded to the Levity platform

Then, begin training by selecting 'Start training' from the relevant tab.

start training Levity's AI on your data

Once the AI has processed your data, you'll be able to get a sense of the AI block's performance score. As close as possible to 100 is good!

training your ai block and judge its performance

As an optional step, you could set up human review. You can define a margin for error, which you can refine yourself according to the parameters that are acceptable for your project.

how to integrate human review into your AI

Next up, for your integrations, you can choose to connect via our API to Zapier, Integromat or Bubble to connect into your own custom workflow.

how to integrate levity into your workflows with zapier and integromat

Alternatively, you could integrate the AI Block into a Levity Flow, which is a visual representation of a workflow that could be several steps of AI Blocks, if required.

how to add your AI into a flow and integrate it into your customer feedback analysis workflow

As you can see, the options for processing qualitative data are huge - and can let you gain valuable customer insights at scale through use of sophisticated NLP algorithms, packaged in an intuitive, easy-to-use wrapper that anyone in the organization can start using today.

Act on customer feedback

Once you’ve read into your customer feedback, it’s now time to take advantage of it. The next step is to prioritize actions for each department based on your findings.

It may surprise you how qualitative data can fit in and improve the processes of several different departments! Here are some examples of the ways it could help your organization:

  • The product team can take the customer feedback and use it to prioritize the product roadmap, or to understand which bugs are causing the biggest customer frustration and need to be fixed ASAP.
  • Customer Support and Customer Success Teams can use gathered data to create a better FAQ for common questions or topics that cause confusion. By doing so, customers can better help themselves, which results in fewer questions sent to your customer service department. As a result, your client-facing teams will be able to spend their time on other pressing matters.
  • Marketing can use survey responses to communicate the product’s value better. For example, if you ran a qualitative survey of your landing page or blog, the feedback will help them improve the copy.
  • The Operations team will become better at predicting revenue fluctuations in various metrics. By knowing the sentiment and opinions of users, operations can set better OKRs, KPIs, and more.

Summary

Customers are the backbone of any business. When they are happy, businesses grow. And the key to high customer satisfaction is continuous feedback. It helps companies better understand who their clients are and how they feel about their product or service.

Gathering, processing, and analyzing qualitative data can be difficult and time-consuming, so many businesses opt out of collecting it or don’t use it to its full potential. With Levity, you can analyze survey responses automatically and focus on making the most of your customer feedback. This way, you’ll be able to make the most of what clients are telling you, and will know how to always put them first.

Now that you're here

Levity is a tool that allows you to train AI models on images, documents, and text data. You can rebuild manual workflows and connect everything to your existing systems without writing a single line of code.

If you liked this blog post, you'll probably love Levity.

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