It’s always important to know how your customers feel about your brand and your products. Properly gathering customer feedback to understand the customer experience and improve customer satisfaction can be a game changer for any business.
That’s why a strong customer feedback loop is essential: a proven and reliable process for staying in touch continuously with your customers to follow the entire customer journey, from start to finish.
A customer feedback loop is a three step process used to (1) gather, (2) analyze, and (3) act on customer feedback. It’s a constant cycle of communication between your business and your customers to gain insights and improve your business, products, and/or services.
Having an effective customer feedback loop in place will ultimately lead to more money, because you’ll be using customer feedback to develop your product roadmap and align services to your customers' needs. So you can expect to reduce customer churn, and even improve customer acquisition.
Let’s go over some of the benefits of a customer feedback loop in more detail, then we’ll show you how easy it is to implement a customer feedback loop with AI technology, like MonkeyLearn.
Creating a strong feedback loop between customers and teams across your organization ( support, product, engineering, marketing) can help your business:
According to Microsoft, 56% of customers have ended ties with a brand because of poor customer service. Regularly asking your customers for feedback is a great way to find out how your company is doing. Direct customer satisfaction (CSAT) and Net Promoter Score (NPS) surveys can target your customers directly in apps, stores, emails, online, or wherever they may be. They’re simple to do and calculate for solid quantitative results.
And with the help of machine learning, you can dive even deeper into open-ended questions and qualitative feedback. Techniques like sentiment analysis can automatically analyze open text for opinion polarity (positive, negative, neutral) to get to the feelings and emotions of survey responses – even unsolicited feedback from social media, forums, blogs, and more.
One of the biggest challenges product managers face is setting roadmap priorities without real market feedback. How can they truly know that they’re building the right products for their customers?
No one knows about the value and success of your products and services more than the people that pay for them, and by sending out simple surveys or monitoring customer feedback over time (whether your own or your competitors’), you can understand your customers’ needs and design a product around them.
Using machine learning tools, you can gain detailed insights into specific features they like best and which may not be up to their standards. Do they feel like they’re getting a good value for the money? Are there certain functionalities that they feel are missing? The goal is to solve your customers needs before releasing a final product.
In a business landscape where it costs five times more to acquire new customers than it does to retain the ones you already have, making your customers happy is priority number one. Customer feedback is necessary to find out which customers are happy and which may be flagging. Furthermore, machine learning tools, like intent classification and urgency detection can help automatically route customer support tickets and improve response rates, so you never leave a customer hanging.
A customer feedback loop will help you get real-time, actionable insights from your survey and customer feedback data or by data mining brand mentions from all over the web. Furthermore, with business intelligence (BI) tools, like MonkeyLearn Studio you can gather all your customer feedback together in a single, easy-to-understand data visualization. Your data will help innovate products and validate strategies (or not).
Customer feedback can help discover industry trends just as they emerge or find new potential areas for growth. And monitoring and analyzing online reviews, forums, and social media feedback can go beyond just what your customers are saying about your brand and help you perform competitive research to get a leg up on the competition.
You’ll need to tailor your customer feedback loop to your goals, team and stage of the customer feedback journey.
Here are some examples of a customer feedback loop in practice.
Get regular insights about your products:
Get insights before launching a new product:
Find out how customers react to a campaign::
No matter the area within your business or your business’s particular area of expertise, a customer feedback loop will help you find customer pain points and sectors you can strengthen or improve.
Close the feedback loop in just three steps. Follow along and you’ll be on your way to improving your business with customer feedback from all kinds of sources.
Give regular CSAT or NPS surveys directly to your customers on your platform, in emails, or in-store. Survey applications like SurveyMonkey make it easy to gather feedback and transfer it to analysis platforms.
You can also use customer service feedback from CRM systems, surveys, emails, live chats, and more. It’s always a good idea to send follow-up emails or chat questionnaires after customers interact with your customer support department or at customer journey touchpoints (after purchase, onboarding, cancelation of service, etc.) to make sure customers are happy or uncover pain points.
You can even find customer feedback from all over the internet. Social media listening allows you to monitor Twitter, Facebook, YouTube, and more, for brand and product mentions, constantly, 24/7 and in real time. Or find comments and reviews from blogs, forums, app stores, Capterra, Amazon, and more.
Text analysis with machine learning is perfect for analyzing your customer service feedback. SaaS platforms like MonkeyLearn can gather and automatically analyze your customer feedback for immediately actionable insights. MonkeyLearn is a no code solution you can implement right away for powerful results.
Use sentiment analysis, for example, to read surveys, reviews, or social media comments for opinion polarity to automatically understand how customers feel about your brand and products.
Take this tweet for example:
This pre-trained sentiment analyzer automatically reads it as negative:
Tools, like the automatic NPS survey classifier (that categorizes survey responses as Customer Support, Ease of Use, Features, or Pricing) are particularly great for customer feedback loop analysis of your products:
Or you can get even more fine-grained with techniques like aspect-based sentiment analysis that allows you to classify customer feedback first by topic or aspect, then sentiment analyze it.
MonkeyLearn is an easy-to-use SaaS platform that allows you to train your tools, usually in just a few steps, to the language and criteria of your business for the ultimate in fine-grained results.
You’ve gathered the customer feedback and performed your analysis, now it’s time to close the loop. Data visualization tools, like MonkeyLearn Studio allow you to see all of your results at a glance for a wide-ranging overview or hyper concentrated results. You’ll be able to easily spot patterns and know where to implement changes.
Take a look at this aspect-based sentiment analysis of customer feedback of Zoom.
Each review has been classified by categories: Usability, Support, Functionality, etc., and then analyzed by sentiment: Positive, Negative, or Neutral.
Imagine running this on your customer feedback data from internal sources and all over the web. You can search data by date and time to find out what products or campaigns are trending positive, find out why customer service may be lagging on certain dates, and discover the most used words to describe your brand or products.
Play around with the MonkeyLearn Studio public dashboard to see how it works. It’s an all-in-one text analysis and visualization tool to follow your customer feedback 24/7 and in real time, automatically.
Once you’ve acted on your results, it’s important that you let your customers know about the changes you’ve enacted, so you’re constantly in touch. Letting your customers know you’re listening can be another powerful tool to keep them brand loyal, even offset any potential damages of buggy products or major down times, like Twitter did when they were experiencing outages.
A customer feedback loop is one of the best protocols to put in place to keep you in touch with your customers, their opinions, and their entire journey. There are massive amounts of customer feedback data you can put to use to strengthen your company.
And with tools like MonkeyLearn Studio you can connect all of your internal and external data into one seamless system to keep your finger on the pulse of your customer base and consistently close the loop
Sign up for a free demo to find out just how easy it can be to set up your own customer feedback loop.
November 3rd, 2020