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Voice of the Customer Trends to Watch Out For

Blog Post
To help you make the most of your voice of customer data and maximize your ROI in 2020, we’re highlighting 3 major trends that you need to keep an eye on.

With demand for better customer experiences on the rise, retail and eCommerce businesses are looking for ways to improve every stage of the buyers’ journey. Naturally, this has made voice of customer (VOC) data invaluable — as it offers deep insights into what customers actually want, as well as what they like and dislike about your current offerings.  
To help you make the most of your voice of customer data and maximize your ROI in 2020, we’re highlighting 3 major trends that you need to keep an eye on.  
Omnichannel Data Collection Methods 
In the past, most VOC data was collected by phone or web surveys. Customers would respond to questions if they had time, and businesses would analyze that data to find critical insights. But today, with customers taking to social media, review sites, and live chat to discuss their opinions, there are new opportunities available.  
On the one hand, your customer support team can tap into multiple channels to talk to customers directly. They can reply to social media comments tagging your business and respond to Google and Amazon reviews to ask for more detailed information from positive and negative reviewers. Using live chat, they can also ask unprompted questions like “What are you looking for, today?” to get detailed information on your customers’ needs and wants during a browsing session.  
At the same time, your teams can gather passive data to get deeper insight into your customers’ goals and pain points. For example, if you have customers asking when an item will be back in stock or posting about how they can’t get a trending product for another few weeks, those insights provide valuable information on product demand and current inventory levels. And knowing those things enables you to make adjustments to keep your customers happy.  
Business Intelligence and Analytics 
You don’t have time to comb through every customer review to figure out what your customers want and identify processes and products that need improvement. Since each customer has their own vocabulary, style, and cadence, it can take hours upon hours to find common themes.  
So it should come as no surprise that natural language processing is becoming a popular solution for managing and filtering out VOC data. With it, you can virtually put your data analytics on autopilot, as the solution can pick out common themes and identify the sentiment behind your customers’ feedback automatically — be it positive, negative, or hovering near neutral.   
As a result, you can focus your attention on sharing insights across your organization and coming up with solutions to your customers’ problems, rather than endlessly reading reviews.   
Often, when businesses think about feedback, the first thing that comes to mind is a survey. And surveys are great in a lot of ways. They deliver insight into specific processes, teams, or products, and generally, they’re very thorough.  
But many customers don’t have the time or patience to answer a 2-minute survey over the phone or respond to the 10 question survey attached to your post-purchase “thank you” emails. That means if you want to get statistically significant feedback from your customers, you have to adjust your approach.  
One way many businesses have started doing this is by incorporating micro-feedback surveys at natural points in the customer’s journey. For example, rather than creating large pop-ups that interrupt their customers’ browsing experience, Amazon has started using a simple 1-question survey to gauge their customers’ satisfaction. Once a package is delivered, customers are notified via the Amazon shopping app that it’s on their doorstep. From there, they can go into the order, view the image of the package on their doormat, and answer the basic: “How was your delivery?” question by clicking the thumbs-up or thumbs-down emoji. And if they feel like it, they can offer additional information on the delivery as well.  
While this may not be the most detailed survey in terms of getting detailed answers on lots of topics — it does the job Amazon intended. It gathers feedback on their delivery service.  
The same tactic can be applied to any retail or eCommerce business’ VOC research. All you have to do is decide what specific insights you’re looking for and find a way to work a simple survey into your website UX or eCommerce store. It gives your customers a simple, low-pressure way to provide feedback and gives you targeted information on an important topic. 
As customers push for better experiences, eCommerce and retail businesses have to adjust their VOC research and analytics tactics to get the insights they need to make improvements. Fortunately, it’s really easy to do so. By tapping into multiple channels, enhancing your business intelligence and analytics, and relying on micro-feedback opportunities, you can create the experience your customers envision.