Customer Feedback Analysis: Definition + Step By Step Instructions

SaaS Product Management
Sep 10, 2023
Customer Feedback Analysis: Definition + Step By Step Instructions

Bill Gates famously said: “Your most unhappy customers are your greatest source of learning.” The difference between good and great businesses is how they treat customer feedback. But if you have hundreds or thousands of customers, how do you even start making sense of it?

Analyzing customer feedback is just as important as collecting it. However, the typical business has many different feedback sources and formats and analyzing it can be challenging.

No more! We’re going to explain what customer feedback analysis is, why it is challenging, as well as walk you through the steps on how to analyze your customers’ feedback.

What is customer feedback analysis?

Customer feedback analysis is the process of taking the feedback that is collected from your customers and turning it into information that can be used by your product, marketing, sales and customer support teams.

Customer feedback can come in various shapes and forms, e.g. customer satisfaction surveys, NPS (Net Promoter Score) surveys, ratings and reviews. In order to act on the feedback your customers provide, you first need to analyze it and separate the wheat from the chaff.

In other words, customer feedback analysis is necessary if you want to find out which pieces of feedback are important for the refinement of your product and revenue growth.


Why analyzing feedback is difficult

Whether you want to or not, feedback is probably coming your way from a variety of different directions. Review websites, customer support calls and emails, NPS surveys, live chat - you name it. So why is analyzing it so difficult then? There are multiple reasons.

First off, there is qualitative and quantitative feedback and they differ from each other greatly. Qualitative feedback offers richer insights but is harder to quantify - it’s hard to make actionable decisions from it. Quantitative feedback is easier to quantify but lacks the depth of insights that qualitative feedback offers.

Combining these two types of feedback can be challenging.

Second, customers can find a variety of ways to say the same thing. For example:

  • I can’t find the upgrade page in the app
  • I want to change my plan and I don’t know how
  • The billing page is not intuitive
  • You won’t let me upgrade my plan

All of these statements talk about the same thing in different ways. Analyzing them all and recognizing that they are in fact, the same thing, requires manual input and is not easy to automate.

Then there is the fact that customer feedback comes from a large number of different sources:

  • Customer support calls
  • Sales emails
  • Live chat
  • Social media inboxes
  • Mentions in communities such as Reddit
  • And many others

To succeed at customer feedback analysis, you need to categorize all of these feedback entries and put them in a single place.

Last and most importantly, not all feedback is equally important.

Is all customer feedback relevant?

The short answer is no. While you should make an effort to collect customer feedback, it’s important to recognize that not every piece of feedback will lead to actionable insights.

Here are two examples of customer insights:




Both are examples of customer feedback coming from online reviews, but the second one is far more useful. 

The point is - not all customer feedback will be relevant and not all customer feedback should be analyzed.

Here is what makes for good feedback:

  • It is specific and detailed
  • It is time-bound (the customer shares their pain points immediately after an interaction with your product)
  • It is not necessarily positive - a negative customer experience is a great learning opportunity

And last but not least, the relevance of a feedback entry will depend on who it is coming from. For example, if you serve different types of markets, you’re going to prioritize the market that brings in the largest revenue share. In other words, customer feedback data coming from an enterprise account with 50 seats will probably have more importance than a solo user on the lowest pricing plan.

Moreover, feedback from existing customers takes priority over feedback from potential buyers - if you want to focus on customer retention, of course.

How to analyze your customer feedback in 4 easy steps

Before going any further - the feedback analysis process is going to be different for every business. Depending on the metrics you track, the channels you choose and the goals you set, you should adjust the methods for analyzing customer feedback.

Having said that, here are some practical steps that every business can use in their customer feedback analysis.

Step 1: Choose your feedback channels

There is no shortage of feedback avenues for data analysis. From feature requests to review sites, feedback comes from all places. You may be tempted to analyze user feedback from every place you find it, but this can lead to piles of work that is not always necessary.

Instead, choose a handful of channels that matter. Here are our suggestions.

NPS, CSAT, CES and other types of surveys

Feedback analytics from surveys is extremely easy because you don’t need sophisticated analysis tools. Most survey types provide quantitative feedback, which makes it easy to collect and analyze.

Common survey types you should cover are:

  • NPS (Net Promoter Score) surveys: they show you how likely someone is to recommend your product to others, with an NPS score range
  • CSAT (customer satisfaction score) surveys: they show you how satisfied a customer is overall with your product
  • CES (customer effort score) surveys: they show you how difficult it is to perform an activity in your product, i.e. how much effort someone has to put in

Besides surveys, there are more qualitative feedback channels.

Customer reviews

Customers will leave reviews for your product on websites such as G2, Capterra, Software Advice, GetApp and many others. 49% of customers trust online reviews as much as they trust recommendations from a friend, so this is a bit of data to keep an eye on. Also, 3.3 stars is the minimum most customers will accept when considering their next purchase.

Make sure to regularly collect and respond to customer reviews from these websites as they provide valuable insights for business growth and product improvement.

Note that while they do have numerical star ratings, most reviews fall into the category of qualitative feedback. This means extra time spent on analysis and categorization.

Sentiment analysis from mentions

No one has the time to collect and analyze feedback all day. But here’s the catch - truly data-driven companies don’t do that. They sit back and get real-time notifications every time someone talks about them online.

Tools such as Determ, Brand24, and others allow you to track every instance of your brand mention online. Review websites, social media, forums, blogs, you name it. Each time someone uses your brand term (or product category, or any other term), you get notified.

And the best part is that most of these tools come with sentiment analysis. Using algorithms, they can determine if they’re negative reviews or a positive comment on your product. This will allow you to quickly filter through the noise and find the most relevant qualitative data from online mentions.

Customer support and sales calls

Speaking of qualitative data, there is nothing better than the data you can get while on the call with people who want to buy your SaaS product. Conversations about customer needs, complaints and comparisons against the competition are an invaluable source of feedback.

To quickly capture this feedback, you can use AI transcription tools such as That way, you get a clean transcript that you can work with further.

Whichever feedback form comes in, make sure to create workflows on how it is handled so that you can effectively close the feedback loop. When a customer leaves feedback, thank them for it and do a follow-up round in case you actually work on resolving an issue they’re writing about.

Step 2: Put your feedback in one place

Whether positive or negative feedback, all of it has to be pooled in one place for easier analysis. Unfortunately, it’s not as easy as using a CRM because there are many different data types. The challenge is putting quantitative data and qualitative insights in one place.

The easiest approach is to create an Excel sheet with different columns for who posted it, where they posted it and what the general feedback is.

Even if you use advanced product management and customer service tools (e.g. Productboard, Canny, Uservoice, Bold Desk), you will still have to do this part manually.

Your sheet should have the source of the feedback, the sentiment, the numerical value (if applicable), an importance score and a field for qualitative feedback, e.g. from open-ended questions.

Step 3: Categorizing your feedback

After you have all the feedback entries in one place, you can start categorizing it according to different criteria:

  • Sentiment (e.g. negative or positive feedback)
  • Types of customer (e.g. new customers or those who churned)
  • Type of feedback (customer feedback surveys, reviews, call information)
  • Urgency (how soon you need to take action)
  • Department (who should be in charge of responding to feedback or solving the problem. E.g. sales, customer support, product, marketing)

This lets you filter non-insightful data and focus only on those issues that matter, such as user experience, usability, new features and other important problems that can hurt the customer journey.

Step 4: Finding the root cause of an issue

With all the feedback laid out in front of you and properly categorized, you can get key insights. For example, you can learn…

  • What negative feedback is the leading cause of churn
  • What positive feedback can give you more information on how to improve customer loyalty
  • Which customer support channels need more attention
  • Which product functionality, integrations or features need more work

Based on the importance score you assigned to a feedback item, you’ll know exactly which items need to be resolved sooner rather than later.

And that’s a wrap

No matter how much feedback you get and whether it’s good or bad, you can easily analyze it with the right systems in place. Establishing this system might take a bit of extra work in the beginning, but it gets much easier once your entire product, sales and marketing teams know how and where to analyze that feedback.

And if you’re looking for a surefire way to make your product better, why not Luzmo? With our interactive dashboards, you can give your users a new kind of access to their data. And it only takes a few hours to fully implement in your product.

Ready to learn more? Build your first dashboard in Luzmo today!

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