How to Build An Effective Customer Feedback System

Loyal customers are, of course, the cornerstone of any successful business. Keeping your customers happy is of utmost importance and there are nearly endless ways to get customer feedback from them to help your business grow, find out what you're doing wrong, and help you acquire new customers.

Customer feedback data is everywhere – you’re certainly gathering it from CRM systems, surveys, emails, chats, and the like. But there’s also plenty you may not yet be using to its potential – all over the internet. The hardest part can be wrangling all this data and analyzing it to get an idea of the whole picture.

Setting up a customer feedback system is your next step to understanding the entire customer journey. When you put the proper customer feedback system framework in place, you’ll be amazed at the results.

What Is Customer Feedback?

Customer feedback is any comment, opinion, or input provided by customers or the public about a particular company, product, or service. It’s the information (positive or negative) companies use to improve products and services and the overall customer experience (CX).

Customer feedback can come from a number of sources – both internally and externally. The below examples are great for collecting customer feedback directly and finding unsolicited feedback.

Types & Methods of Customer Feedback

Customer satisfaction (CSAT) ratings

CSAT ratings or CSAT scores are among the most simple measurements of immediate customer satisfaction. They’re usually just one question, like “How happy were you with your experience today?” and the option to click a multiple choice response.

Responses are often on a scale from 1 to 10, a star rating, or as simple as a smiley face or a frowny face.

CSAT questions are often used in apps or on live chats to get a very basic idea of how happy customers are. You can even include open-ended questions, like “Tell us why you felt this way.”

CSAT surveys are great because they’re easy to calculate and quantify, and it’s just a single question, so the response rate is high. They don’t, however, tend to give enough information to truly understand a customer’s feelings.

Net Promoter Score (NPS) surveys

Net Promoter Score is another of the most popular ways to measure customer satisfaction with quick feedback. It asks a simple question: How likely are you to recommend {our product or service} to a friend or colleague?

Customers are asked to answer this question from 0 to 10, which classifies them as Promoters (9-10), Passives (7-8), and Detractors (6 or less). A company’s final “Net Promoter Score” is found by subtracting the percentage of detractors from the percentage of promoters.

It’s a simple metric with a quick result that many companies feel is an important indicator of customer loyalty and potential for growth. However, responses between 6 & 8 may be wholly ambiguous, and single-click responses, while they get a high percentage of responders, may not elicit much honesty because the user may just want to clear through the screen.

Again, you can include follow-up questions that elicit a more detailed response, which you can analyze based on the different groups.

Marketing & sales feedback

When you send out marketing and sales emails it can be helpful to include a survey or simply ask the recipient to respond to the email to find out how marketing and sales teams are doing. Were customers promised something that the product didn’t deliver? Are you simply sending too much marketing material? What can you do to improve?

Onboarding feedback

Onboarding is a logical time to request customer feedback because it’s a major customer journey touchpoint (right after they’ve made the purchase) and, especially with tech-heavy products, customers may be particularly unhappy with onboarding if they’ve had trouble using the product.

With services like Netflix, onboarding may completely dictate the CX, as their algorithm based on onboarding feedback results in 75% of everything viewers watch from that point forward.

Customer reviews

Customer reviews can come from all over the web: Capterra, G2 Crowd, app stores, Amazon, Yelp, and many more – even social media, blogs, forums, etc. Online reviews often reflect the most honest opinions because they’re unsolicited and offer details that you’re unlikely to get from surveys or requested feedback.

The problem is they’re open-ended comments containing unstructured data that needs to first be formatted before it can be analyzed by machines. Fortunately, advancements in machine learning make it possible to automatically analyze online reviews with almost no human interaction for deep insights. And it’s qualitative data that goes beyond mere numbers and statistics.

Performing sentiment analysis on reviews of your brand, for example, can automatically read comments for “opinion polarity” to find out if the review is positive, negative, or neutral. Imagine using this on reviews and comments about your products from all over the web. Take this tweet for example:

Tweet: "@AppleTV is a great example of terrible User Experience. And I'm not talking about the lack of content."

This pre-trained sentiment analyzer easily reads it as negative:

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Product surveys

You can run occasional surveys about your products to tweak and improve them or perform market research. Platforms like Google Forms, SurveyMonkey, and Typeform make gathering data easy, and you can have surveys occasionally pop-up in-app, send them via email or social media, or use post-purchase follow-ups after online chats or sales interactions.

The great thing about directed product surveys is you know you’re communicating with your target audience and you can customize the questions to find out exactly the information you need.

Feedback from support conversations

It’s important to follow customer service feedback because it can truly make or break an organization, and it’s usually the last interaction customers will have with your company. Simple survey pop-ups after live chats or follow-up emails are a great way to accomplish this, and satisfaction is the main goal, so simple targeted questionnaires can often get the information you need. But you can dig deeper into open-ended questions or even analyze historical emails and support conversations with text analysis and customer feedback software.

In-person interviews or focus groups

Focus groups and interviews can sometimes be the most successful way to elicit feedback because their conversational approach allows the subject to dive deep into their feelings – often in a roundabout manner. Furthermore, properly trained interviewers are able to anticipate topics and feelings and steer subjects in new directions to get the information they need.

What Is a Customer Feedback System?

A customer feedback system is a holistic strategy for collecting and analyzing what customers are saying about a business or product. It’s a framework of tools and techniques for obtaining insights from feedback from multiple sources and platforms to improve the customer experience (CX).

An efficient and properly managed customer feedback system can gather and analyze customer feedback wherever it may be for real-time, data-driven insights to inform business decisions and understand the voice of the customer (VoC). Putting a customer feedback system in place allows you to integrate data analysis tools for a seamless process and impressive results.

Benefits of a Customer Feedback System

When you have a good customer feedback strategy in place you’ll see immediate results and be able to follow the customer journey from beginning to end. Benefits include:

Social media listening

Customer comments and complaints can appear all over social media, 24/7, and it can be overwhelming to try to handle them manually. Furthermore, in this fast-paced social media world, 83% of customers who comment or complain about a business on social media expect a response the same day, and 18% expect it immediately.

AI-guided social listening tools allow you to follow real-time brand and product mentions on Twitter, Facebook, Instagram, and more; automatically analyze them for intent and opinion, and route them to the proper employee or department, so your customers aren’t left out in the cold.

Customer experience analytics & voice of the customer (VoC)

Integrate your data and processes to follow the whole customer journey. Customer feedback software allows you to find patterns and trends and understand your company’s relationship with your customers – even perform competitive analysis to find out what competitors may be doing better than you. Put yourself in the customer’s shoes to understand exactly the experience you’re delivering.

Survey and feedback collection & integration

Integrate your CRM system with survey tools, like SurveyMonkey, to streamline processes. Connect regular CSAT, NPS, or survey data of all sorts (as well as other feedback collection) to your data analysis tools to see ALL of your customer data together.

Stimulate customer reviews With online reviews and star ratings heavily driving customer acquisition, it’s important that you remind or gently poke your current customer base about the importance of these reviews. Customer feedback systems can help you automatically target your biggest promoters to practically guarantee 5-star reviews.

Multi-source feedback

Ensure all of your feedback platforms and sources are integrated, working together for a truly holistic analysis of your data: emails, surveys, live chats, social media data. You may discover insights that you’d never even considered. And business intelligence (BI) visualization tools help make your results easy to digest and understand.

But just how do you handle your feedback?

A Sustainable Customer Feedback System

MonkeyLearn is an intelligent customer feedback solution: a suite of text analysis tools to get you from customer feedback collection to analysis and qualitative results.

MonkeyLearn Studio offers an all-in-one, seamless process to analyze and visualize your customer feedback, so you won’t miss a single step of the customer journey. MonkeyLearn is easy to set up, completely scalable, much more accurate than human analysis, and offers real-time, data-driven results.

Here’s how to create your customer feedback system with Monkeylearn in just four steps:

1. Collect Feedback

Use CSAT and NPS surveys, emails, social media data, chat conversations, customer support tickets, whatever data source you need. MonkeyLearn integrations allow you to connect directly to Zendesk, SurveyMonkey, Typeform, Google Forms, and more, or upload CSV or Excel files.

Connecting MonkeyLearn with Zendesk, for example, allows you to extract all your help desk data and can even help automate your customer support process. By creating a Zap that syncs with MonkeyLearn’s machine learning capabilities, you can automatically prioritize, route, and respond to customer support tickets in real time.

2. Set Your Goals

What are you trying to achieve with your new customer feedback system? Do you just need to automate processes? Do you want to improve individual products or customer service?

Think about how you can use all of your feedback data together to get the information you need. This will also inform new survey questions or areas of data collection.

3. Set Up Your Automatic Feedback System All In One Place

Connect MonkeyLearn to the tools you already use with the aforementioned integrations so you can analyze feedback with almost no human interaction.

Or with just a little bit of code you can use MonkeyLearn’s API in all major programming languages for an even more streamlined data analysis process.

A flowchart showing how MonkeyLearn Studio works automatically: "choose a template," "import your data," "run analysis," visualize data."

With MonkeyLearn Studio you can connect multiple analysis techniques, like keyword extraction, sentiment analysis, aspect classification, and more, and analyze your customer feedback automatically.

You simply choose a template or create your own (with the tools you need), import your data with integrations, and your analysis and data visualization will happen automatically.

Tools, like the automatic NPS survey classifier (that automatically categorizes survey responses as Customer Support, Ease of Use, Features, or Pricing) are particularly great for customer feedback analysis:

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Or the pre-built email classifier to sort marketing email responses as: Autoresponder, Email Bounce, Interested, Not Interested, Unsubscribe, or Wrong Person:

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Best of all, 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 unsurpassed accuracy.

Get Real-Time Insights

Once your analyses are set up, you’ll get 24/7, real-time results, automatically.

Take a look at the MonkeyLearn Studio dashboard below showing aspect-based sentiment analysis of customer feedback of Zoom.

Each review has been classified by “aspect” or category: Usability, Support, Functionality, etc., and then each category analyzed for sentiments: Positive, Negative, or Neutral.

MonkeyLearn Studio dashboard showing results for intent classification and sentiment analysis in charts and graphs.

Imagine this run on all your customer feedback data. You can search data by date and time to find out when products may have been trending positive or dig in to see why your customer service team seems to perform poorly on a certain day of the week.

Take a look at the MonkeyLearn Studio public dashboard and change criteria by date, intent, category, etc. and see just how easy it is to get real insights from your data.

The Takeaway

Customer feedback is possibly the most important source of insights to retain customers and help your business grow. But setting up a customer feedback system can seem like a daunting task – there’s so much data from so many sources, and then you have to connect and analyze it all.

Fortunately, MonkeyLearn Studio lets you connect all of your internal and external data streams and create a seamless customer feedback system framework to analyze and visualize your customer feedback for fine-grained, real-time insights.

Sign up for a free demo to find out just how easy setting up a customer feedback process can be.

Rachel Wolff

October 27th, 2020