None of that has to be the case, though. The power of feedback analytics lies in using it contextually, appropriately, and with external validation. <\/p>\n\n\n\n
Five ways to use feedback analytics to drive innovation and growth\u00a0<\/strong><\/p>\n\n\n\n Personalization and customization\u00a0<\/em><\/p>\n\n\n\n 91% of consumers are more likely to shop with brands that recognize, remember, and provide relevant offers and recommendations.\u00a0You see this in practice everywhere. When you open YouTube, Netflix, or Amazon, your homepage is filled with suggestions tailored to your preferences. You rarely have to invest effort in finding the next show to watch or item to buy, because each of these businesses already knows your likes and interests.\u00a0<\/p>\n\n\n\n Feedback analytics typically focuses on things like analyzing unstructured text.\u00a0While capturing data on a customer\u2019s past behavior or product usage don\u2019t quite fit that category, these things are like the two wheels on a bicycle: lose one and you\u2019re stuck.\u00a0Say your customer bought a sweater from your ecommerce store. Great! You now know they like sweaters, they wear a women’s medium, and they like the color green.\u00a0But then a month later they leave a review: \u201cThis sweater was the perfect Mother\u2019s Day gift! My mother thinks it\u2019s super cozy, and she loves the shade of green it comes in.\u201d\u00a0<\/em><\/p>\n\n\n\n Oops. <\/p>\n\n\n\n You\u2019ve just learned\u2014through feedback analytics\u2014that all of the \u201cpersonalized data\u201d you gathered on this customer was inaccurate. Each of those things apply to their mother, not to them.\u00a0\u201dAnalyzing what your customers have done and <\/em>what your customers have said together <\/em>is the only way to get the full picture of who your customers are.\u201d\u00a0<\/p>\n\n\n\n Predictive analytics<\/em>\u00a0<\/p>\n\n\n\n Feedback analytics can help you anticipate <\/em>customer needs and behavior. It\u2019s powerful, but predictive analytics isn\u2019t an exact science and usually requires leaving room for error.\u00a0Combining customer feedback with <\/em>purchase info, browsing history, or engagement metrics can fill in the blanks.\u00a0If you\u2019re a SaaS company and a customer shows behaviors that indicate decreased product engagement. Not good.\u00a0Then\u2014in a totally different tool\u2014you also see they’ve reached out to your support team multiple times about product issues.\u00a0<\/p>\n\n\n\n Really not good. <\/p>\n\n\n\n Combining and analyzing these two sources of data through feedback analytics can give you the information you need to make changes proactively and retain that customer.<\/p>\n\n\n\n Real-time feedback\u00a0<\/em><\/p>\n\n\n\n Agile environments thrive on fast and frequent iterations.\u00a0Sometimes that means it\u2019s valuable to stop the roll-out of a new feature because of a technical issue that wasn\u2019t caught during testing. Other times that means capitalizing on a great opportunity to produce more of a product or extend an event because your customers have received it so positively.\u00a0The only way to react quickly enough in these situations is to use feedback analytics. But analyzing feedback manually is incredibly time-consuming. By the time you know how to react, it\u2019s often too late.\u00a0Gathering real-time insights through a modern customer feedback analytics tool enables you to make those impactful decisions quickly and confidently.\u00a0<\/p>\n\n\n\n Data-driven decision-making\u00a0<\/em><\/p>\n\n\n\n There\u2019s a huge correlation between data maturity and business success. McKinsey suggests that data-driven organizations are:\u00a0<\/p>\n\n\n\n And it\u2019s easy to understand why\u2014data is the ultimate objective validation of anything you want to do.\u00a0Feedback analytics enables you to access a giant pool of data that is otherwise only shared as individual anecdotes or in a broad statistic that doesn\u2019t teach you anything.\u00a0Imagine the wealth of information in your customer surveys, support inbox, or online reviews.\u00a0<\/p>\n\n\n\n If you aren\u2019t combining and analyzing that data effectively, you\u2019re forced to make decisions without the complete picture.\u00a0It\u2019s easy to talk about wanting to be \u201cdata-driven\u201d as an organization. But the only way to tap into the power of feedback analytics is to invest the time, effort, and money to building out a great analytics program.<\/p>\n\n\n\n Idea generation and validation\u00a0<\/em><\/p>\n\n\n\n While it\u2019s true that customer feedback might not provide you with that innovative and unheard-of solution that will make or break your business, customers are <\/em>very good at telling you what isn\u2019t working.\u00a0our customers are experts in their own paint points.\u00a0And feedback analytics teaches you how to listen.\u00a0<\/p>\n\n\n\n Ten customers might send you ten different feature requests explaining how that feature would help them.\u00a0At first glance, these seem unrelated. If your support team manually categorizes feature requests, they might list them all as different features.\u00a0But what if there was an overlap between the pain points each customer experienced that made them send in the request?\u00a0<\/p>\n\n\n\n Feedback analytics can easily show you these connections because it helps you identify patterns in your huge amount of customer feedback. Your team can use it to generate new ideas and validate customer interest, enabling you to make smarter bets.\u00a0You might say it\u2019s the difference between playing roulette\u2014a game of total chance\u2014and playing poker, which involves both chance and skill.\u00a0<\/p>\n\n\n\n Feedback analytics unlock deeper customer insights\u00a0<\/em><\/p>\n\n\n\n Your organization is probably already comfortable working with data and tracking essential business KPIs.\u00a0Once you\u2019ve laid that foundation, you\u2019ll find that feedback analytics can provide a depth of understanding that\u2019s Feedback analytics makes you customer-centric by giving you access to your customers\u2019 thoughts in their own words. It removes bias and lets you combine quantitative data with qualitative insights. <\/p>\n\n\n\n Ultimately, feedback analytics gives you the \u201cwhy\u201d behind the \u201cwhat.\u201d<\/p>\n\n\n\n About the Author<\/strong><\/p>\n\n\n Ryan Stuart is the co-founder and CEO of Kapiche<\/a>, a new wave insights and analytics platform for customer insights and research teams. With more than 15 years experience in Natural Language Processing and its application in Customer Experience, Ryan is deeply passionate about using data and technology to make better business decisions.<\/p>\n\n\n\n Kapiche is revolutionizing customer intelligence to create a world where organisations make human-centric decisions & every voice is heard. Kapiche has grown into one of the most in-demand technologies in the Australian customer insights space, and has recently launched into the North American market with customers that include Zappos, Nextdoor, Cox Communications, Toyota, Target, Wolverine Worldwide, Colorado Tech University and Basalm Brands.\u00a0<\/p>\n\n\n\n Sign up for the free insideBIGDATA newsletter<\/a>.<\/em><\/p>\n\n\n\n Join us on Twitter: https:\/\/twitter.com\/InsideBigData1<\/a><\/em><\/p>\n\n\n\n Join us on LinkedIn: https:\/\/www.linkedin.com\/company\/insidebigdata\/<\/a><\/em><\/p>\n\n\n\n\n
hard<\/s> impossible to achieve without it.\u00a0It helps you dive into the wealth of unstructured data available to you, enabling you to understand nuances, identify emerging patterns, and uncover root causes.\u00a0<\/p>\n\n\n\n![\"\"](\"https:\/\/insidebigdata.com\/wp-content\/uploads\/2023\/11\/Ryan_Stuart.png\")
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