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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, and why it is challenging, as well as walk you through the steps on how to analyze your customers’ feedback.
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. 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.
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:
All of these statements talk about the same thing in different ways. Analyzing them all and recognizing that they are 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:
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.
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:
And
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:
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.
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.
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.
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:
Besides surveys, there are more qualitative feedback channels.
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.
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, Mention.com 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.
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 Rev.com. 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.
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.
After you have all the feedback entries in one place, you can start categorizing it according to different criteria:
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.
With all the feedback laid out in front of you and properly categorized, you can get key insights. For example, you can learn…
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.
It's likely you'll get a lot of food for thought - but you can't consume it all at once. Prioritization is your companion here.
So, after categorizing feedback based on thematic elements such as customer satisfaction levels, product feedback, or social media comments, the next step is to prioritize action items.
A good idea might be to create a priority matrix (e.g., Eisenhower Matrix) to determine which feedback items need immediate attention.
You can also use feedback tools to help visualize this data and understand where to allocate resources effectively.
For instance, issues reported by detractors or passives in customer surveys should be addressed promptly as they directly impact your business growth.
How to prioritize effectively? Despite lack of a golden rule in every case, these three actions are worth considering:
Once you have prioritized the feedback, create a complex action plan that outlines specific tasks, responsibilities, and timelines for each priority item. This plan should also specify who will be involved in each step.
An effective action plan transforms feedback into tangible results and data-driven decisions instead of guesswork – all for continuous improvement and better customer sentiment.
Define clear objectives for addressing feedback, such as improving satisfaction levels or enhancing features based on feedback from surveys and support calls.
Clearly defined objectives help prioritize tasks and ensure that every action is aligned with customer expectations.
Establish measurable goals to track your progress and validate that changes positively impact the customer experience.
Identify the necessary feedback tools and resources, such as AI-powered analytics or machine learning models, to streamline the process.
Make sure your team is trained to use these tools for maximum efficiency – this often becomes an obstacle. Choosing the right resources will help you gather actionable insights and automate repetitive tasks, allowing you to focus on strategic improvements.
Set specific milestones to track progress and timely implementation. Break down large tasks into smaller, manageable steps with clear deadlines for each. At each stage of your initiative, this approach allows you to evaluate the impact and maintain momentum.
Identify potential risks associated with implementing changes based on customer feedback. In this step, you need to assess the possible impact on existing workflows, customer perception, and resource allocation. Develop contingency plans to mitigate these risks.
Create a clear communication strategy to keep both internal teams and customers informed about the changes being implemented. Outline how you will share updates, such as product improvements or new features, ensuring transparency and building trust with your audience.
Define specific metrics to measure the success of your action plan. These could include an increase in customer satisfaction scores, a decrease in churn rate, or improved product adoption rates. Regularly review these metrics to evaluate the effectiveness of your initiatives and adjust the plan as needed.
Implementing an action plan is just the beginning. For true success, businesses need to monitor the outcomes and make adjustments based on new feedback.
Regular monitoring of data points, using tools like artificial intelligence and machine learning, but also data visualization software, helps track changes in all areas affected by customer feedback.
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!
Experience the power of Luzmo. Talk to our product experts for a guided demo or get your hands dirty with a free 10-day trial.
