It’s no secret that a good customer experience leads to greater customer loyalty, which is why companies have invested in CX organizations and Voice of the Customer (VoC) programs. The online customer feedback survey industry is expected to grow from $4.8 billion in 2019 to over $10 billion in 2025, driven by strong adoption among retail and eCommerce companies.
The desire to know what your customers think of your company and products hasn’t changed, but how we capture and analyze the information to understand customers has. And that’s due in large part to the speed, scale, and anonymity of digital interactions with customers. Companies need new ways to capture the emotions and thoughts of their customers without getting swept away by the tidal wave of data available to them about customers.
Which brings us to the question of surveys: can surveys—which make up an outsized part of many CX team’s budget and effort—provide the depth of understanding and insight that companies need into their customers’ experiences?
You don’t need to know the growth rate of the survey industry to understand that surveys are becoming more common throughout the customer journey. Solicitations for feedback are popping up everywhere, from webpages and emails to phone calls and text messages. As consumers, we’re inundated with requests to score our experiences and provide feedback about everything we do.
These surveys attempt to pare down the customer experience into an easily digestible number to help leaders understand individual experiences and holistic trends across the customer base. There are disagreements on the best way to frame the question, though. The most common types of feedbacks surveys include:
- Customer Satisfaction (CSAT): Asks customers to rank their experience with a company’s product or service based on a numerical scale at key points in the customer journey such as checkout or after a service call.
- Customer Effort Score (CES): Asks customers how simple it was to accomplish a task, typically to procure support from call centers or other service channels.
- Net Promoter Score (NPS): Asks customers how likely they are to recommend a product or a service to a friend based on their experience.
Satisfaction, effort, and word-of-mouthiness are all important things to know about your customers’ experiences and loyalty to your brand. But they don’t tell the whole story.
According to research from McKinsey & Co. on the future of customer experience, “executives increasingly recognize that survey-based measurement systems fail to meet their companies’ CX needs—although surveys themselves are an important tool for conducting research.” In their research, they found four major shortcomings to surveys that can mislead companies in their efforts to understand customers, close the loop on unsatisfactory experiences, and charting the future of the brand experience.
In particular, there are four ways in which surveys as the sole or main means of measuring CX fall short, according to the CX leaders inMcKinsey’s research.
1. Surveys represent only a small percent of your customer’s voice, typically 7% percent.
2. Since surveys take time to collect and analyze, they’re out-of-step with the real-time needs of organizations.
3. The information surveys collect don’t get to the root problems.
4. The ambiguity also leads to suspect ROI calculations that make it difficult to tie survey scores to real world CX initiatives.
In light of the mountains of data already available to companies about the customer experience, this leads the authors of the study to ask: “Why use a survey to ask customers about their experiences when data about customer interactions can be used to predict both satisfaction and the likelihood that a customer will remain loyal, bolt, or even increase business?”
For companies that rely on surveys for their Voice of the Customer program, the question shouldn’t necessarily lead them to jettison their surveys. But it does offer an opportunity to think about what we consider VoC feedback and how the interaction data CX teams use to inform and augment their survey-driven perspective.
What Makes VoC Feedback, VoC Feedback?
The reality is that companies are awash in customer feedback. Every call transcript, chat log and email into the Contact Center is filled with information about the customer experience, including the way those experiences make the customer feel. Similarly, customers are putting their feelings about their experiences on social media and in product reviews.
Historically, however, these sources of customer feedback haven’t been seen as reliable sources to mine for insights. That’s because it takes a lot of time and energy to manually read them and come up with trends and patterns. What makes CSAT and similar feedback scoring systems attractive is it makes it easy to quantify a particular metric, such as the likelihood of a customer to stay loyal. For most companies, the juice has never been worth the squeeze; diving into these unstructured sources of data like text and voice records was slower and more costly than surveys.
As the McKinsey study finds, solely relying on surveys is not enough anymore, and advances in Artificial Intelligence (AI) and Machine Learning (ML) are opening new and cheaper ways to analyze the customer experience. The authors of that study recommend mostly eschewing surveys to instead rely on the operational and behavioral data you already have documenting the customer experience to develop predictive customer scores which they argue can help you “understand and track what is influencing customer satisfaction and business performance, and to detect specific events in customer journeys.”
Data-driven approaches like this can provide faster—even predictive—insights into the customer journey. But it misses the mark when it comes to listening to the voice of the customer. One of the key elements one loses with a voiceless approach to the customer experience is the sentiment tied to each moment. Is someone opening up a chat box because they’re frustrated with the user experience on the website? Or because they’re excited about the product they just saw and want to learn more?
With enough data points, we could find out. But that information is already there in the unstructured text of the conversation. And compared to behavioral data alone, it carries with it the emotions and sentiments of the customer—and employee—interactions.
Uncovering New Insights with AI-Powered Text Analytics
The customer experience is evolving. In the last eighteen months, companies have had to reimagine much of the way customers interact with their brand. Better, faster measurements and insights into the customer experience will be critical moving forward as companies look to make these changes permanent or to change course for the new normal.
Companies looking to create a customer-centric approach will need more than surveys to clearly understand the customer experience. For most, it shouldn’t come at the cost of losing the voice of the customer, however.
Advances in AI-powered text analytics like Natural Language Understanding and emotion analysis not only make it possible to quickly uncover deep insights into survey verbatims, it allows CX organizations to scale beyond verbatims to mine other forms of unstructured customer feedback. In fact, with more unstructured data to work with (compared to the small sample size of survey verbatims) companies can do more with AI-powered modeling.
In the era of big data, unlocking insights into all of this unstructured customer feedback in the moment allows you to analyze customer feedback alongside the operational and behavioral data that McKinsey’s study recommends relying on. By pairing the structured and unstructured forms of customer experience data together in your analysis, you’ve got all the ingredients you need to understand what’s driving your customers’ interactions with your brand.
Learn more about unstructured customer feedback and how it can be one of your greatest organizational assets when you download our latest eBook!