Have you ever made a costly mistake because your customer feedback analysis wasn’t on point? Well, you thought you had actionable insights, but then the end result was a big floparoo? That gold mine list of feedback turned into a mine field?
Unfortunately, it’s happened to us; as one time is already too many for any growing SaaS company, we needed to come up with a way to improve our analysis process.
If the same has happened to you, then you’re probably asking yourself: how should I most effectively use the customer feedback that comes in to make better business decisions?
Feedback alone isn’t fully actionable and usable. In this article, we’ll break down the feedback analysis process. As a result, you can easily adjust your decisions-making process based on learning directly from customers. This way, you can build better products and measure the success of your efforts with your customers.
What is Customer Feedback Analysis?
🦄 Hold your horses, hombre! Before we get to far, just wanted to tell you about our ultimate guide to customer feedback (no worries, it opens up as a fresh tab). 🦄
Customer feedback is the lifeblood of your business. It’s the voice, emotions, and insights of how your customers experience your product. It’s your call to action to go from lousy product experience, customer frustration, and alarming churn rates to outstanding product experience, customer delight, and retention (retention, retention).
In this case, such feedback tells you everything you need to know about customer satisfaction levels and overall experience.
You can collect customer feedback in a variety of ways:
- Messenger tools
- Social media
The feedback analysis process filters all the information received. With that, you can use the data to make customer experience improvements.
The first stage includes making decisions about how to cluster the data, via tags or labels. From there, you can make decisions about what customers are telling you about your company and product experience.
Customer vs User Feedback Analysis
What’s the difference between customer feedback analysis and user feedback analysis? Simply put: users may or may not be your customers, but your customers will almost always be your users. This means that when you get user feedback, analyzing it should be done through a slightly different lens.
Additionally, user feedback analysis could be employed for different purposes. Perhaps you need the user feedback for your website and user journey, and not the in-product customer experience (where customer feedback analysis would be more apt).
Why is Analyzing Customer Feedback Difficult?
Let’s face it: it’s not easy to summarize what people say into specific categories of what they say they want, prefer, or dislike. Sometimes, it is a thankless task that has to be done in order to get to the fun stuff: making better product decisions.
You can easily write out a generic understanding of what you see in your customer feedback software. However, if your goal is understanding precise details about customer feedback, then it might take a few days or weeks to summarize it.
People use complex language
A group of people often provide dozens of variations when describing the same situation or answering the same question. For example:
- I can’t find the submit button
- The button arrangement isn’t intuitive
- It’s hard to navigate
- I’m finding it difficult to move through it
You can see why it’s hard to categorize customer feedback based on these free response answers. Ask yourself how you’ll make sense of it when you end up with dozens or hundreds of similar replies to your customer satisfaction surveys.
Feedback quality varies
You’ll receive qualitative feedback from customers that varies in quality. It could end up being unhelpful or generic or it may be specific and usable. That’s why we recommend proper tools that help you receive specific and actionable insights.
How is it Important?
Do you have an abundance of feedback data, and still you don’t know what to do with it? That’s why you must get good at customer data feedback analysis.
Benefits of Effective Feedback Analysis
Using customer feedback surveys to gather customer data results in four specific benefits to you as a business owner.
1. More business growth
Did you know that you can increase prices up to 25% and realize continuous revenue growth if you collect, analyze, and take proper actions on the feedback provided by customers? 86% of customers will pay higher prices if you improve their overall experience.
2. Better customer experience
Improved customer experience is a natural extension of the customer feedback analysis process and should be a big part of your customer retention strategy.
Paying attention in this area reveals where your customers’ dissatisfactions may hurt the business. You’ll learn from customers exactly what to do to improve customer experience and boost customer loyalty.
Net Promoter Score (NPS) is a feedback response from customers. Simply put, how likely it is that they’ll recommend your company or products to family members, friends, and colleagues.
Your NPS is by subtracting the percentage of Detractors from the percentage of Promoters. The NPS is typically represented as a full number, within a range of -100 and +100. For instance, if you have 35% Promoters 15% Detractors, and 50% Passives, your NPS will be +20.
Improving your Net Promoter Score will end up making it easier for customers to recommend you to others. You’ll want to keep your NPS at +30 and above for SaaS.
4. Better products and services
It’s difficult to make product improvements if you don’t have a direct line into what your current customers like or don’t like about it. If you start asking customers to tell you exactly what they think about your products or services, then you can analyze that data in such a way that it directs you into the correct fixes.
Splitting Customer Feedback Data
You can’t use all the data that comes in after asking for customer feedback. Some of the information is useful and actionable. Some of it won’t help you at all. You need to split your customer data into one of two categories:
- Insightful data
- Non-insightful data
Insightful data exposes the difference between what you thought was working and what customers tell you. It might even confirm suspicions that you have about what needs to get fixed in your business.
You’re looking for three types of actionable insights from this customer feedback process. You want insights that lead to:
- An ability to reformat your overall strategy
- Indications about what works and what doesn’t require changes
- Insights about where to make critical, specific changes
For example, you may learn that your app users can’t click on a button that you previously thought worked perfectly. You need to get that fixed immediately. If you do, then you’ll see an increase in customer satisfaction right away.
Non-insightful data doesn’t tell you anything new. It’s old news in your mind. It merely confirms something you already knew with absolute certainty.
For instance, if you get negative feedback about an app feature that your team already identified as a negative feature, that’s non-insightful data. You can ignore it because you’re aware of it and the team is fixing it.
Your task is to gather as much insightful data as possible. You’re probably asking how to get this data from customers so you can split it into one of these two groups. Let’s discuss that next.
How to Get Actionable Insights from Your Customer Feedback
If you can’t get real, useful feedback from customers, then you can’t accomplish the overall outcome of improving the customer experience. Actionable insights point you directly to what you can improve for your customers. Sometimes these improvements may only take days or minutes to make.
Collect Customer Feedback
Getting feedback from customers is a proactive activity. You can’t wait for someone to use your About page or reply to a newsletter once in a while. Let’s discuss the different sources for gathering feedback
Surveys, e.g. CSAT or NPS
Use NPS surveys to quickly gain insight into what your customers think about you and your company. An NPS survey looks like this:
“How likely are you to recommend [company or product name] to others?”
Give customers a 0-10 scale and rate them accordingly when compiling the data:
- 9-10 = Promoters
- 7-8 = Passives
- 0-6 – Detractors
Note that you’ll also hear NPS surveys being referred to as Customer Satisfaction (CSAT) surveys, sometimes. With that in mind, most experts would disagree. In the end, what’s most important is getting quality insights, whether it is positive feedback or negative feedback.
Use customer surveys when you want to expand the one-question NPS survey. These surveys might include open-ended, closed-ended, or multiple-choice questions. Send them via Twitter, Facebook, email, or on your web pages.
Optimize your surveys to increase the customer survey response rate. Typically, customers prefer shorter surveys with more multiple-choice responses. However, a few open-ended questions can help identify major pain points to be addressed.
Most people look at online reviews before deciding to become your customer. For example, using tools such as ParseHub or Dexi, you can scrape the web to gather your company’s online review data and analyze it.
Public reviews can reveal much more than your surveys since the customers write them voluntarily and on the spot.
Some customers go to social media to provide proactive feedback. Pay close attention if a customer criticizes a product feature or reveals their raving fan status on Twitter, Facebook, or any other social media channel.
Respond to these interactions immediately. Help anyone going through a challenge to find the solution that makes them feel great about you. Reach out to raving fans and ask if they’ll create testimonials or full case studies with you.
Customers often go on social media when they feel like other feedback channels haven’t been effective for them. If you notice a trend in this, take a look at your other customer support channels.
You can gather customer feedback via your website chat apps. Use a chat app to ask website visitors, for example, whether the page provides everything they’re looking for. Ask them where it’s confusing. Use this feedback to make necessary changes and improve website conversions.
Facebook Messenger allowed businesses to incorporate Messenger into their websites. You can embed your business’ Facebook chat in just a few minutes.
Call Center Notes
Compile the notes taken by your call center representatives. They have personal conversations with your customers daily, where customers provide excellent feedback about their satisfaction levels. Compile these answers, which helps analyze the data. Then, helpful customer service reps use the feedback to improve overall customer satisfaction rates.
Use the notes you make in your contact relationship management software.
Train your staff to use this area for important feedback notes. For example, the sales team can insert notes from sales calls. Investigate those CRM notes to find where insightful data exists and use it to your advantage.
Categorizing Customer Feedback
You might wonder then: how can I categorize customer feedback?
You should split the customer feedback across your product, customer service, and marketing and sales categories.
For example, you might compare the way your competitors talk to their customers on social media and the feedback you’re getting from your customers. What do you notice about your tone against the tone of competitors? How might you need to change your approach in that area?
Use the feedback data to make decisions about how to improve the way you market and sell the product, how you teach customer service reps, and how to positively change the product.
How do I categorize customer feedback?
Not all customer feedback is the same – they might be alike, yet they might not mean the same thing. It’s up to the business to ensure that they answer accordingly. Categorizing feedback can help provide the best replies. Remember, you have to collate the feedback first. Also, do not be surprised, you might need to sub-categorize after categorizing. Some common categories might need more categorizing, so be prepared.
To begin, see whether your data reveals any patterns. Then, to make categorizing and subcategorizing easy, choose the common theme that most staff, if not every staff, can understand. You can worry about sub-categorizing after you are successfully done categorizing.
Sorting customer feedback into categories will assist you in seeing the overall picture of how your product or service is doing. There might be incomplete feedback too, but it will also help you understand what customers are going through. Categorizing (and sub-categorizing) always makes for better understanding of customers.
Below are some categories that might help:
– Billing/Pricing issues
– Improper app usage issues
– Positive and negative reviews
– Bug issues
How to Discern Insightful and Useless Data
Not all customer feedback is useful to a business. This means that there are two types of data, useful and useless data, or, in data analysis terms, insightful and non-insightful. It is after this that you then categorize the insightful data – there is obviously no need to categorize non-insightful data.
What makes non-insightful data non-insightful is the fact that it tells you nothing new, and even adds no information to statistical inferences. Insightful data offers new information that either challenges the accepted status quo and/or strengthens your previous inferences.
For example, if a large percentage of customers complain about how a particular product tastes, the next thing to do is to go back to the drawing board and check the creation process, probably the ingredients. Insightful data is more commonly known as insights or actionable insights.
Customer feedback analysis reports may provide three sorts of actionable insights:
– Insights that help you reconsider your strategy
– Insight for critical thought and action
– Insights that help validate established opinions
Market Feedback Analysis
People see or hear the word analysis and think, “oh, there goes the difficult stuff.” Analysis is definitely not difficult, infact, you might be very interesting if you actually settle with it.
Basically, analysis means looking more intently at data to draw inferences or insight, which can be profitable to a business or academic. It is breaking down large volumes of structured (or unstructured) data. For business, the data gotten from market feedback analysis (or customer review analysis) is called actionable insight, and is very useful as it can guide improvements and attract potential customers.
A good feedback analysis example is, after getting a lot of feedback about how a food ordering app does not respond when a particular meal is chosen, analysis staff come together to find out why. Could it be location, a bug, a malfunction, or simply the meal does not exist? That’s what needs finding out.
Customer Satisfaction Analysis
It is a well-known and accepted fact that customers that get satisfied return for more. Also, another fact well known in business is that it is easier to maintain current customers than get new ones. This implies that no business wants to lose customers, and their best ones at that. Hence it is wisdom to consistently check up on how satisfied your current customers are to avoid losing them, and also ensure they recommend your service/product to their friends. The process of studying the satisfaction of your customers is called a customer satisfaction analysis.
Apart from the above-stated reasons, businesses do customer satisfaction analysis to ensure that issues that cause dissatisfaction are eliminated and prices can be increased for greater profits.
Most businesses, if not all, utilize qualitative and quantitative customer feedback analytics as their major sources of data. However, qualitative data is often ignored and wasted. This is because it is easier to utilize quantitative data due to its numerical nature (numbers come to mind easily than facts), unlike qualitative data, which focuses on the quality of an idea through the use of descriptions instead. Hence, quantitative data is easily measured and, consequently, more preferred to qualitative data.
However, because qualitative data focuses on personal sentiments and customer experience, it is a more trusted form of data for businesses as it identifies personal pain points of the customer experience.
How to Analyze Customer Feedback
Once you get feedback from customers, you can analyze customer feedback in four different ways:
- With a script
- Using software
- Trying AI
How to Analyze Feedback Manually
Using two spreadsheets, separate the feedback into sub-themes and themes. A variation method is to simply compare positive and negative feedback. Create a code value for each type of feedback, such as:
- Interesting courses
- Variety of course
- Course quality is poor
- Poor company atmosphere
Log how many times each positive or negative comment occurs via its code on your spreadsheets. This method helps you understand the process as you go through it methodically. Unfortunately, the manual method is a tedious activity, and sometimes needs some better visualizations to understand what is happening with your customers.
How to Automate Customer Feedback Analysis Using a Script
Avoid tedious manual methods by using a script. Some programs such as Rake allow you to use keyword extraction scripts. In the case, that type of script takes less time than doing it by hand.
The negative aspect to this is that if you aren’t familiar with coding, then you would need to hire an expert. However, automation is the best option to analyze a large number of reviews and scale your business.
How to Automate Customer Feedback Analysis Using Third-Party Software
Various third-party software exists to help you further automate the process. Data-driven companies can use Thematic’s software. Many companies offer customer feedback analysis assistance for large enterprises. For instance, Usersnap allows you to gather, prioritize, and analyze customer feedback.
This method is less time-consuming than the other methods. However, you must research the costs and companies before you select one of these services.
How to Analyze Customer Feedback with AI
Artificial intelligence offers interesting customer feedback analysis solutions. It’s more accurate than manual methods and provides faster results. Using machine learning, AI can sort through thousands of data points, provide clear analysis, and help you take meaningful action on the information.
Looking at raw data inside an excel spreadsheet isn’t typically helpful because it’s difficult to interpret the data.
You can use visualization tools to turn raw data into graphs, charts, and other forms of easy-to-interpret visual representations. The better you can understand customer feedback, the easier it is to turn your product into a positive customer experience platform.
Looker is a tool with a simple dashboard and an ability to zoom into detailed visual views.
Google also offers a visualization tool that lets you build reports and graphs around your customer feedback data.
If you’re looking for a simple drag-and-drop tool to create customer feedback charts and graphs, then take a look at Tableau. It offers real-time data integration.
Invest energy and money in visualization tools so you can shorten the time frame required to turn data into action steps.
Are you ready to start gathering customer feedback, become great at analyzing it, and then taking specific action steps to improve your company, product, and/or service?
If so, then you need to ask yourself which analysis method sounds best to you.
We encourage you to take a free demo of our solutions at Usersnap. You can effectively automate the process as you work to increase customer engagement, make positive changes to your product, and quickly respond to feedback.
It’s possible using our customer feedback platform with tools such as:
- Customer satisfaction widgets
- Feedback menu options
- Customer engagement widgets
We make it easy to use CSAT, NPS, CES, and binary rating systems to gauge customer happiness levels. Our tools help to streamline the feedback process, obtain customer health scores, and resolve challenges more quickly.
Check it out today!
Capture feedback easily. Get more insights and confidence.
Getting feedback has never been easier and we hope you’ve realized that after reading this article. Let us know what you think, your feedback is important.
And if you’re ready to try out a customer feedback software, Usersnap offers a free trial. Sign up today or book a demo with our feedback specialists.