{"id":10979,"date":"2021-10-13T14:14:22","date_gmt":"2021-10-13T14:14:22","guid":{"rendered":"https:\/\/www.revuze.it\/?p=10979"},"modified":"2021-10-13T14:14:22","modified_gmt":"2021-10-13T14:14:22","slug":"7-ways-to-improve-customer-feedback-analysis","status":"publish","type":"post","link":"https:\/\/www.revuze.it\/blog\/7-ways-to-improve-customer-feedback-analysis\/","title":{"rendered":"7 Ways To Improve Customer Feedback Analysis"},"content":{"rendered":"
Information is power, so you\u2019ll have a huge competitive advantage if you know how to interpret feedback from customers and use the analyzed tips that can be generated from it. Customer feedback analysis is a powerful tool that helps you take <\/span>feedback<\/span><\/a> from your audience and turn it into something useful, a clear target for improvements that you can make and complaints that have been made.<\/span><\/p>\n Remember, while not all feedback is going to be negative, consumers are far more likely to leave feedback over a negative experience than a positive one. Therefore, don\u2019t be discouraged if the majority of your feedback data is negative: it\u2019s a chance to learn how to be better!<\/span><\/p>\n Below you\u2019ll find seven of our best tips for improving analysis of complaints and compliments and how to interpret feedback in the workplace to form a better idea of what the consumer desires.<\/span><\/p>\n When you\u2019re analyzing feedback forms, it\u2019s often just as important to check <\/span>who<\/span><\/i> is leaving feedback as <\/span>what<\/span><\/i> is being said. After all, the most important pieces of insight will come from <\/span>long-term<\/span><\/a> customers who have much more experience with your brand than the average consumer.<\/span><\/p>\n However, you shouldn\u2019t be fooled into thinking that newer customers have no insight into things. Pay attention to how much the customer has used your products rather than the length of time they have done so for. Remember that your feedback analysis relates to the study of determination of sales performances and potential, you want to ultimately be looking at what will bring in more revenue.<\/span><\/p>\n When checking your feedback, it\u2019s also important to keep in mind that the two ends of the scale (e.g. 1 and 5 in a 1-5 rating) are going to be more populated than the middle, as it\u2019s just human nature to act on strong positive or negative feelings. Because of this fact, you can separate your feedback into the positive and negative kinds which will tell you different things about your customers\u2019 experiences. Want to focus on improvements? Complaint trend analysis is your friend. Want to think more about refining the positives? Glowing reviews that give positive feedback for customer service can help there.<\/span><\/p>\n If you\u2019re wondering how to improve analysis, one of the best first steps is to take your data and categorize it (and subcategorize). How this might be done is up to you, but one of the best ways of doing this is to look at each step in the customer journey and place the feedback into categories that represent said steps. That way, you\u2019ll have an easier time getting your data analysis and interpretation of customer satisfaction right \u2014 there\u2019s no use trying to make improvements if you don\u2019t know what your customers want, after all! You can find market feedback analysis templates and similar online if you\u2019re not sure where to begin.<\/span><\/p>\n You can also categorize your data by type if you\u2019re using multiple methods of collection (are you calling customers for feedback, or simply leaving forms with their purchases), by date if you want to analyze the effect of a new change in procedure etc., or by how useful you think it is and how detailed a piece of information it contains. When you\u2019re categorizing feedback a lot of it will go into the non-useful categories, junk or generic reviews that give no actual information being two of them. While it\u2019s always heartwarming to see someone leave a comment saying \u201cI love your brand,\u201d it isn\u2019t very useful in this context so you should filter it and comments like it out so you can focus on customer feedback results that you can extract useful data from.<\/span><\/p>\n If you\u2019re a small business that turns over relatively few products, you might be able to go through all of your reviews by hand and sort them into neat little piles. In the digital age where reviews can be left en masse this approach isn\u2019t very feasible, with reviews for even small brands numbering in the hundreds or thousands. This can be aided with software or AI filters that screen feedback and separate it into categories automatically, doing in seconds what it would take a human all day.<\/span><\/p>\n1. Check and separate the type of feedback you\u2019re getting<\/b><\/h2>\n
2. Categorize your feedback<\/b><\/h2>\n
3. Automated tools and software<\/b><\/h2>\n