Analyzing customer feedback is a complex and insightful process. You get a wealth of data from your customers, but it’s not typically in a form that you can use with traditional analytics tools. Your company needs a specialized approach to get the most out of your customer feedback, allowing you to offer the best customer experience.
Techniques for Customer Feedback Analysis
The quality customer experience is the key to creating a loyal and dedicated customer base. Each good interaction helps to drive repeat buyers and encourage them to become outspoken proponents of your brand. However, understanding the factors that make up a good experience and what your customers are looking for requires the careful evaluation of customer feedback.
Many customers are happy to provide feedback, but you need a way to collect and analyze this information properly. Techniques for customer feedback analysis must offer a scalable way to understand unstructured data, the context of the feedback, and how it’s relevant to your customer experience.
What is Customer Feedback?
Customer feedback is input from your customers about the experiences that they have with your products, services, or brand. Your customers may have positive, negative, or neutral feelings about their interactions, which you can use to shape the direction of your business.
Your customers may provide this information to you in written, verbal, or video form, depending on the channels that they’re providing it on. Your customer feedback is not isolated to a particular business unit, as customers have many interaction points, from your social media channels to in-person events.
Why is Customer Feedback So Important?
The effective collection and analysis of customer feedback offers many benefits to your business.
Looking for Ways to Offer Better Products and Services
You can continually evaluate how your customers feel about your products and services based on their interactions. When you receive repeated feature requests, encounter common complaints, and receive other information on how your product line is received, you can tailor it around your buyers’ expectations.
Customer feedback is excellent for testing new product and service ideas as well, as you can discover whether they will be well received with your typical buyers. As you apply this data to your research and development process, you can continue to keep your customers happy.
Discovering New Markets to Expand Into
You may find out about potential markets for your products and services through customer feedback data. The potential for horizontal and vertical growth can help you drive new business, bring in new audiences, and cement your position in the marketplace.
Understand How Your Customers Actually Use Your Products and Services
The problems that you think your customers need solved are not necessarily the ones they’re actually solving with your products and services. In some cases, customers may need more information and guidance on how to properly use your offerings, while in other situations, you may need to make adjustments for the real-world use cases happening.
Learn About Your Customer Satisfaction Ratings
How happy are your customers? Do you know how your customer satisfaction ratings compare to your competitors? A good customer satisfaction score for one industry may be subpar in another. While this type of rating doesn’t tell the whole picture of your customer experience, it does offer a helpful baseline that’s valuable for a big picture view of your buyers.
As your customers become happier with your brand, products, and services, they’re more likely to make other purchases, recommend your company to their social circles, and post positive reviews and messages online.
Fix Issues with the Customer Experience Proactively
Another way you can use customer feedback is to identify problematic trends with your products and services. If you see recurring issues popping up in the customer feedback, then you may have a problem that needs solving. A few mentions may be an outlier situation, but when you examine the data for overarching patterns, it can indicate whether you need to address that part of the customer experience.
Helping Customers Feel Engaged With Your Company
People like to feel listened to, and customer feedback is one way that you can ask for buyer opinions. The higher the engagement levels with your brand, the more likely that you can help form an emotional connection that drives customer loyalty and satisfaction.
Acquiring Social Proof
Testimonials, reviews, and other forms of social proof come directly from customers. When a potential buyer is shopping around and doing research, they will look at information from their peers as a more trustworthy option compared to something directly from your company.
Making Better Business Decisions
You can use real customer data to guide your company’s decision-making processes, rather than taking a more subjective approach to your strategies. By doing so, you can keep an eye on the feedback to your moves, how they impact your company’s growth, and what you need to do to remain competitive in the marketplace.
How to Collect Customer Feedback
You have many avenues available to collect customer feedback, providing your organization with a wide range of input to work with. Some common forms of customer feedback include:
- Customer live chat support and chatbots: Both your live chat and chatbot channels can offer valuable customer feedback during their conversations. Since this interaction typically takes place through text-only, it’s also easy to pull these conversation logs for further analysis.
- Customer focus groups: You can get detailed information about particular topics during focus groups, which tend to involve a smaller subset of your customers or potential customers. This type of customer feedback collection method is good for learning more about particular parts of the customer experience, testing the waters for new products and services, and looking for ways to improve the customer experience.
- Customer posts and replies on social media sites and other communities: Your best customer feedback may not be directed at your company. Instead, customers can discuss your brand, products, and services on social media sites and in other communities. This information can be an excellent way to learn what your customers and target audience are thinking and how they respond to different moves that your company makes.
- Customer surveys: Customer surveys are a common method for collecting customer feedback, and they come in many forms. One of the most common is the Net Promoter Score survey, which encourages customers to rate whether or not they would recommend your business to others. This is not the only survey used, and more free-form options are available for open-ended questions.
- Order comments: Your customers may share valuable information on the comment form on their orders, or during follow-up surveys after the sale.
- Customer service calls: You can learn more about the challenges your customers encounter when they use your products and services, as well as the common fixes required to help them get the most out of their purchases.
Collecting Customer Feedback Data
The good news is that your business has plenty of sources for customer feedback data. The challenge is that you need a way to collect and process these large data volumes. Manual processes are not realistic for the size of the data sets you’re working with. You also need timely and accurate data, which is difficult to get when you need a lot of end-user input to get this information into your systems.
If you don’t have good data quality, you could end up drawing the wrong conclusions from your available customer feedback data. This data could lead to poor decision-making that makes your customer experience worse, impacting your reputation, revenue, and other parts of your business.
The Challenges of Analyzing Customer Feedback
One of the biggest roadblocks to analyzing your customer feedback comes from unstructured data. Unstructured data does not have a particular data model, so your systems need a way of understanding this information before you can use it. Most of your customer feedback data comes in written form without using particular keywords or other identifying markers that your systems can use.
Your customers use natural language, which is how they would typically communicate with others, when they’re talking to you. Natural Language Processing, or NLP, and other forms of Artificial Intelligence can take this information and translate it in a form that your systems can process. If you operate in multiple countries, you also have to account for any translation and localization that would be necessary to make that data relevant to your analysis.
The use of this type of technology also solves the scaling issue, as most of the process is automated so it’s capable of keeping up with the sheer size of the data sets involved. Your staff can focus on the insights offered by this data, rather than the tedious work of getting the information prepared for use. When you automate this business process, you also end up reducing the time it takes to process the data. It may only take minutes for a modern system to work through your data sets and get it ready for the next step.
By solving these challenges with the right customer feedback analysis tools, you’re able to harness one of your best sources of information for the customer experience. The more that you improve your customer experience and prove that you value feedback, the more that you can encourage buyers to continue coming back to your brand.
Coding Feedback from Customers
One of the first steps of this process is coding the feedback that you receive from customers. The coding process organizes your customer feedback into different categories, and structures it for other analysis processes as well. It can look at the text, break down the context, and sort it into different criteria. While positive, negative, and neutral are commonly used categories, you can also use coding to identify other types of patterns.
For example, you may want to see how often a particular feature is mentioned by customers, or see how often an issue comes up in support calls. Due to the complex and changing nature of human speech, as well as the evolving requirements of your company, you may need to do some manual coding alongside more automated processes. However, the bulk of your work can be handled by specialized applications and platforms for this purpose.
How Do You Analyze Customer Feedback?
Several types of tools are available to further analyze your customer feedback so you get the most out of this data. Verbatim analytics platforms and text analysis software are two categories that hold the answer to unlocking this valuable source of information. The features of these solutions vary between developers, but you may want all or part of the following functions available when you’re working with customer feedback data.
Verbatim analytics means that you can perform analysis on input that is given verbatim, as the customer said or wrote it. Rather than locking customers into set responses during surveys and other data collection efforts, you can offer open ended questions that get you far more valuable input.
Sentiment analysis is another important functionality, which focuses on the emotions behind the text. Your products and services may elicit different reactions from your customers, based on their customer segment and other factors. Learning more about these reactions can help you define your sales and marketing strategy, make improvements to your products, and better serve your customers.
Data visualizations are a helpful way of taking the analysis done by these systems and displaying it in an easy-to-understand form. Dashboards, charts, graphs, and other tools can help you interact with the data sets and get to the bottom of what it’s trying to tell you.
Topic grouping allows you to group up topics that are similar, so you can get a comprehensive view of how many customers care about that particular aspect of the experience. Without grouping, you may not think that it’s important at all, as that information is hidden in a group of related terms.
Data filtering helps you remove the junk data from your sets before they make it to visualizations and other forms of analysis. You can toss customer feedback that is profanity laden, incomplete, or otherwise low quality so it doesn’t get in the way of your valuable insights.
Over time, you can create custom rulesets that surface the insights that are the most important for your company. These priorities may change over time, so your rulesets should as well.