A plethora of data is available to the modern business owner, marketer, salesperson, and customer support leader. Data is a vital part of business, and understanding where and how to look during data analysis is essential. One of the goals of data analysis is capturing consumer insights. What does your customer think about your product or services?
You can capture consumer insights through proper feedback analysis. By utilizing AI tools that sift through unstructured feedback comments, you can find out what your consumers desire, and how you can meet their expectations.
Customer insights tell you what your customers think and feel, and more importantly, why they think and feel that way. Your business can then use these insights to improve customer satisfaction and retention through better products and services and increase the bottom line by generating more sales — in fact, research shows that customers are 90% more likely than ever to share positive and negative experiences.
You can collect customer feedback on social media, comments on app stores, or surveys. Whichever way you choose to gather the data, it’s hard to analyze in its raw form. The reviews not only vary in size and content; they may also have different contexts. To draw proper insight, you need to go beyond the customer rating and identify what the customers honestly think about you.
1. Tagging Data
In the first stage, you need to tag the data. Tagging consumer comments when sifting through thousands of comments, requires an automation tool. Auto-tagging can help you quickly categorize your comments into reliable fields for analysis.
With natural language processing, modern feedback analysis tools can sift through comments, tag each comment, and place them in the relevant category. If 80% of your clients are commenting on recent price changes, you can detect it in real-time.
The tag you apply to your products varies depending on your business. When customizing a tagging system for your feedback analysis, it’s crucial to understand the customer and business language. Properly sorting your comments can help you identify words that pop up repeatedly. Once you find repeated words and terms, you can create the best tags.
Are consumers discussing customer service, price, value, response time, or convenience? If you’re in a specific industry, such as app development, it may help to look out for jargon such as bugs, dashboard, settings, in-app, or UI. It may also help to include names as tags, mainly if your customers use your staff’s names.
2. Categorizing Customer Feedback
After tagging the data, you can dive into creating sub-categories and categories that can guide your analysis. Several issues can affect your choice of category. You can group the comments per topic, such as customer support, customer service, pricing, and ease of use.
You can also create categories based on the feedback type. Is it a complaint, negative or positive comment, improvement? Alternatively, you can use urgency (high, medium, low), customer levels (subscriber, non-subscribers, premium, and basic packages), channel (phone call, text, chat, and social media) and product (t-shirts, pants, leggings, earrings, watches, rings, sneakers).
3. Routing Customer Feedback
Routing serves two purposes: it saves time and ensures that different departments in the businesses draw insights quickly. For example, if a customer complains about rude customer support, it makes sense to route the comment to a customer service leader instead of the technical support team. The customer support leader can then deal with the rude agent immediately without top management in the decision-making process. Another critical aspect of this is that it improves “time to insights” — the right automated systems can help you find insights faster and route this information to relevant folks so that they can react quicker.
Drawing Actionable Insights
Drawing relevant customer insights from feedback analysis is essential for decision making. After tagging and categorizing comments, you can identify general areas of concern for consumers. You can achieve this by visualizing the data on a map or a graph. The visual representation can help you identify areas in need of urgent solutions. What’s more, you can subdivide your comments into specific problems.
For example, let’s say, after analyzing the data, you identify that 60% of the comments focused on customer service. After digging further, you realize that your consumers have raised concerns about inadequate responses (60%), inaccessibility (30%), ), and lack of personalized approaches (10%). Upon further examination, you may identify that the poor response vote is due to rude customer service agents, slow responses on social media, and lack of product awareness when advising customers.
With the right intelligence tool, you can analyze the data down to the rude customer agent’s name, or the app with the slowest responses. You can then take action, such as checking your customer support agents for skills such as listening, politeness, quick service, and a deep understanding of your products and services. AI doesn’t just provide information, it helps you better meet your customer’s desires and expectations.
Difference Between Actionable & Non-Actionable Data
While collecting customer feedback is essential for any business, finding insights in the data is the most crucial part. Non-insightful data provides information that you already know. However, insightful data provides new information, confirms a suspicion, and also states importance. You can draw different actionable insights from your customer feedback analysis.
First, you may receive validation for a new feature or product you’re testing out. Perhaps you’re launching a new fragrance, flavor, or function in your mobile app. If the data shows that customers are happy with the new change and product or service, you can take no action.
Second, consumers may help you rethink your strategy. For instance, if you launch a product and realize that many consumers want you to communicate more about your new products, you may have to reconsider your marketing strategy.
Lastly, the insight may require critical thinking and immediate action. For example, some consumers share product reviews with suggestions for product changes beneficial to the consumer. Complaints about rude customer support agents may require immediate action.
How Can Yogi Help?
Yogi breaks down customer feedback beyond the coveted 5-star rating status. With Yogi, you can isolate your comment to find the aspects of your products and services that consumers are focused on. Should you maintain the current changes, make new changes, or discard current changes?
Yogi helps you draw actionable insights to improve business operations by auto-tagging, categorization, and routing. What’s more, you can analyze customer feedback from different sources in real-time for the latest consumer insights.