When customers’ expectations are higher than ever, companies need to keep a constant watch on the entire customer journey, and understand how customers can inform improvements in their products and/or services and overall customer satisfaction (CSAT).
This is where VoC, “voice of the customer” or “voice of the consumer” comes in. In order to improve your products or services, your business, and ultimately, your profits, you need to listen to your customers’ opinions about your business.
Voice of the customer (VoC) is used to describe how customers talk about your brand, products, and services. VoC gauges customer expectations across the entire customer journey, allowing businesses to become more customer-centric, improve products and/or services, and increase customer retention.
VoC analysis aims to combine customer feedback from customer service interactions, CSAT and NPS surveys, chatbots, emails, social media, and all over the internet, to understand the vast array of customer experiences and customer relationships, and enhance customers’ overall happiness with a brand or organization.
Voice of the customer helps businesses improve their products or services and inform product development, so they can refine their offerings into something customers truly feel good about spending money on.
What can VoC do for your business?
Instituting a holistic approach to VoC with a customer feedback loop, for example, will ensure you’re tuned in to CX at every step of the customer journey – marketing, sales, onboarding, customer support interactions, etc. – to uncover pain points and highlight the positive attributes of your business.
Once you’ve pinpointed which areas of CX you need to improve, you can take action and close the loop, to let customers know that you’ve made changes or are at least listening to them – which can go a long way in making customers feel appreciated by a brand.
According to Zendesk, half of customers worldwide say that customer experience is more important to them now than it was just a year ago and would switch to a competitor after just one bad experience.
Performing VoC analysis will teach you how to connect customer feedback across all data channels, both internal and external, to inform decisions with as much data as you can get your hands on. You’ll improve processes, like onboarding and delivery, and offer seamless omnichannel customer support. And you’ll be able to follow real-time brand sentiment and perform competitive research across social media, online reviews, forums, and more.
Honing in on particular pain points will help understand why customers may be leaving. You can execute customer surveys via email, in-app, chatbot, on your website, or wherever your customers may be, to regularly analyze their issues.
Targeted CSAT surveys, at time of subscription cancelation, for example, can be helpful to pinpoint the reasons customers may be churning. And unsolicited feedback from churned customers on Twitter, Facebook, Instagram, etc., can sometimes provide even more helpful information because spontaneous feedback is often the most honest.
According to a 2020 survey of leading product managers, 52% of teams say that their products and features are primarily inspired by customer feedback, yet only 10% of teams feel that they successfully capture feedback from all available sources.
Customers could be regularly discovering new use cases for your products or suggesting minor tweaks that could have a huge impact on the usability of your products or services. Your customers are the ones that actually pay for your products or services, so they understand their value better than anyone else – and this could mean adding new features or introducing new versions to keep them happy.
It’s simple, contented customers lead to less churn, more acquisition, and lower marketing budgets, while VoC analysis can lead to more data-driven decisions from less overall spending and, ultimately, higher revenue.
How to create and launch a VoC – voice of customer – program in just three steps:
1. Collect your customer data: create surveys and collect internal and online data.
2. Analyze your data: put machine learning to work on your VoC data.
3. Take action: visualize your data for powerful insights.
You’re likely already collecting a lot of VoC data from CRM systems, customer service feedback tools, emails, and more. Expanding on this to build a customer support ticket management system can help funnel all of your customer support to one place, to streamline processes, facilitate data collection, and keep you in touch more closely with your customers.
Not only is a ticket management system great for VoC analysis but overall support improvement – especially given a recent Zendesk CX trends report that shows that 64% of customers used a completely new support channel in 2020 and 73% of them plan to continue to use it. 2020 also saw a 36% growth in customer/business communication on in-app messaging, 75% in SMS/Text, and a full 110% in social messaging.
You can also collect regular customer satisfaction (CSAT) and Net Promoter Score (NPS) surveys via chatbots, in-app, or emails, after distinct customer journey touchpoints, like after purchase, after onboarding, or upon cancelation, so you can have an idea of individual pain points. Survey applications like Typeform and SurveyMonkey can walk you through creating and implementing custom surveys and collecting survey data.
Finally, web scraping tools allow you to extract customer comments from social media, online reviews, and more, and many sites, like Twitter and Facebook, even offer APIs to connect directly to their data.
As customer support channels expand, ticket volume grows, and data increases, manual analysis is no longer viable – it simply takes too long and isn’t even completely accurate.
On top of all this, customer expectations have only grown during the pandemic. According to the American Customer Satisfaction Index (ACSI), the average CSAT for American companies had the largest quarterly drop from Q2 to Q3 last year (by 1.2%) in almost 20 years.
That’s why more and more companies are adopting AI solutions, like text analysis. Text analysis tools are ideal for automatically analyzing your VoC data and facilitating customer communication. They can gather and analyze your customer feedback in real time, with immediately actionable insights.
Techniques like sentiment analysis can be put to work on voice of customer data to automatically understand the opinion polarity (Positive, Neutral, Negative) of any text. Take this tweet for example:
First, we’ll run it through a pre-trained opinion unit extractor to separate each opinion within the text and analyze it separately:
Then we run each opinion unit through a pre-trained sentiment analyzer:
It easily classifies this opinion unit as Negative. Imagine this analysis run on thousands of tweets, emails, and customer service interactions in real time.
Other tools, like this pre-trained keyword extractor, can find the most used and most important words and phrases from a text, to summarize whole texts and uncover emerging topics and trends, like from this online review of the Spotify app.
The great thing about text analysis tools like MonkeyLearn is that you can train them to the specific needs, language, and criteria of your business for even more accurate results.
Finally, with tools like MonkeyLearn Studio, bring your voice of customer data to life in striking visualizations, so you can see the whole picture or pinpoint individual aspects of your data. Take a look at this analysis of VoC from online reviews of Zoom:
The above shows each customer opinion separated by topic: Usability, Support, Reliability, etc., then by sentiment, so we understand which aspect of the business is particularly Positive and which is Negative.
MonkeyLearn Studio is the only all-in-one text analysis and visualization tool that allows you to set up your VoC analysis, have it run 24/7 and in real time, and automatically show you the results in an easy-to-use, interactive dashboard.
When your results are this simple to understand, it’s easy to follow VoC through the whole customer journey and to know, immediately, where you may need to make changes.
Follow customer sentiment as it changes day-to-day or hour-to-hour. Perhaps you’ve just released a new marketing campaign and you see sentiment falling. Maybe you need to pull it. Or if you’ve just released a new product or feature and customers are reacting positively all over the internet – you can use this to your advantage.
Take a look at the MonkeyLearn Studio public dashboard to see how easy it is to use. You can search by date, category, keyword, and more, to get a super fine-grained view of VoC.
There is perhaps no better way to follow the customer journey and get into the heads of your customers than setting up your own voice of the customer program. You’ll be able to understand your customers’ needs – to streamline processes, improve products, reduce churn, and increase revenue. And there’s no doubt that businesses need to turn to AI tools to help them listen to and better communicate with their customers.
MonkeyLearn’s powerful text analysis platform allows you to train machine learning tools to the needs and criteria of your business, and set them up to follow VoC constantly for real-time, data-driven decisions.
Take a look at all of MonkeyLearn’s tools to see what they can do to help you understand your business’s voice of the customer.
Or sign up for a free MonkeyLearn demo for a personal walk through the VoC process.
February 22nd, 2021