When it comes to understanding customer feedback, businesses can learn so much by making an effort to understand the language of their customers. This doesn't just mean interpreting the words they're using; it also involves analyzing behaviors and actions that factor into that line of communication.
I'm always impressed by those who have learned English as a second language, because it can be so difficult to speak, write, and understand.
- Exhibit 1: There, their, they're
- Exhibit 2: "It's time to eat grandma," vs "It's time to eat, grandma"
- Exhibit 3: According to thesaurus.com, there are twenty-six synonyms for the word "problem," including quandary, dilemma, and pickle
Now, put the general complexity of language and communication into the context of contact center interactions. Would your chatbot understand a customer that said they were "in a pickle?" Or for that matter, would any agent under 30 know what that means?
Behavior can be just as difficult to understand. If someone doesn’t respond to your text message, are they ghosting you, or did they just lose their phone? The implications can be stress-inducing.
Your customers send you plenty of behavioral cues about their preferences, needs, sentiments, and expectations. All of these things, in turn, may be the difference between positive or negative customer experiences (CX). But the messages are lost if you don't have the right approach and tools to listen and react.
This article explores some new ways to listen in on customers’ digital languages and deliver improved CX. Use these suggestions to re-examine your voice of the customer (VoC) program, self-service solutions, or customer relationship management processes and take them to new levels of responsiveness and CX excellence.
Idea 1: Integrate customer feedback surveys with interaction data for improved understanding
Surveys are an effective way to collect customer feedback and calculate key metrics such as satisfaction, Net Promoter Score, and customer effort scores. Customer satisfaction surveys are valuable because they let contact centers know how people feel about their overall service experience. They also gauge satisfaction levels with specific aspects such as agent competence, speed of resolution, and the usability of self-service solutions.
Survey results are a vital input to every customer experience management program, but as valuable as they are, they don't provide a holistic understanding of the Voice of the Customer (VoC).
However, some shortfalls include single digit completion rates and an over-representation of highly satisfied and dissatisfied customers. People tend to complete customer satisfaction surveys when they're either really happy or really angry. Additionally, customer feedback garnered from surveys doesn't always provide useful information about the extent of certain problems; for example, a single customer might complain about an issue that impacts thousands of people.
Combining survey results with contact center interaction data is a powerful way to develop a more complete understanding of customers and what they're contacting your business about. Circling back to the example above, using this combination of data can help businesses understand if an issue that appeared on a single customer satisfaction survey is an anomaly or more widespread.
Contact centers have always been treasure troves of mostly inaccessible customer and business insights, but artificial intelligence (AI) has changed the game. Now, organizations can use AI-powered interaction analytics software to mine all interaction channels (speech and text), feedback channels, and other relevant data points in true “omnichannel” fashion. The resulting insights make it possible for businesses to take informed action to transform and improve customer experiences (CX).
Interaction analytics software analyzes every interaction from every channel in real time. Its capabilities include:
- Measuring customer sentiment. Sentiment is a machine-learning AI trained with more than 500,000 customer interactions to measure whether an interaction is positive, negative, or neutral on a relational scale. The model identifies positive and negative words and phrases, whether spoken or text, considers semantics and context, and then fine-tunes with laughter, crosstalk, or changes in pitch, tone, or speaking rate.
- Identifying contact drivers. Interaction analytics automatically identifies contact topics with useful metrics such as topic volume, trending over time, related topics, sentiment, and more. These metrics can be reported across the organization on role-based dashboards so that all roles can identify problem areas and then work to mitigate them quickly and efficiently. In this way, the organization becomes proactively involved in improving customer experiences.
- Identifying customer needs. Interaction analytics doesn't just produce helpful problem-related insights; it also helps identify unmet needs that, when addressed properly, can lead to enhanced CX and greater revenue. For example, interaction analytics can identify competitor mentions for root cause analysis into why customers might be considering cancelling. This makes it possible to empower agents with counter offers, upselling, or loyalty programs to help prevent costly customer churn.
When it comes to developing a robust feedback management program, more data is better. Combining survey results with customer interactions data leads to a deeper customer understanding. Organizations can then take action to improve customer satisfaction, loyalty, and overall experiences.
Idea 2: Personalize customer experiences
Personalized customer experiences show customers you speak their language, and you understand their needs and expectations. Tailoring experiences to specific people requires businesses to recognize customers in every channel they use and to leverage individual data—such as purchase and interaction history—to make customized recommendations. An example of personalization most are familiar with is the film and show recommendations we see when we log into Netflix.
In the contact center, personalization could mean using a customer's history, preferences, and sentiment to route them to an agent they're more likely to "click" with.
Customers want to speak to agents equipped with the disposition that’s most compatible with their personality and the knowledge needed to resolve their issue.
Customers not only value customized experiences—they expect them. A Salesforce study found that 59% of customers expect tailored engagement based on past interactions.[i]
Read on for additional ways contact centers can customize interactions to meet customer expectations.
Leverage CRM data
Customer relationship management (CRM) applications are warehouses full of valuable customer data and are useful in personalizing customer service experiences. When a CRM solution is integrated with contact center systems, it captures cross-channel activity and then makes it available in every channel to better tailor interactions to customers.
Additionally, these integrations provide agents interaction analytics data and customer information such as search history, sentiment, the channel customers came from, and what knowledge articles they already viewed. When presented in a streamlined, unified desktop, this information enables agents to customize live customer experiences in real time. According to Microsoft, 75% of respondents expect the agent to know who they are and their purchase history.[ii]
Putting their CRM applications and contact center data to work, together with AI-powered analytics, allows businesses to meet these expectations.
Implement a customer and agent feedback loop
As anyone who has learned a foreign language knows, the best way to become fluent is to seek out conversations with native speakers.
Similarly, contact centers can proactively reach out to customers to become proficient in their language. Regularly soliciting customer feedback through surveys helps businesses identify components of CX that are working well and areas that need improvement.
However, gathering and analyzing feedback is not enough. Have you ever described an issue on a survey and felt like the information fell into a black hole? Maybe the issue was corrected behind the scenes, but because the organization never communicated with you about the resolution you assumed your input was disregarded.
Don't do this to your customers by treating surveys as a form of one-way communication. It's a customer experience management best practice to close the loop with unhappy survey customers by contacting them and trying to develop empathetic, personalized resolutions to their issues. Additionally, if customer feedback results in significant product, process, or policy enhancements, communicate that information clearly to let customers know you heard them and value their input.
Use this same feedback loop process with your customer service agents. Voice of Employee (VOE) survey data boosts employee satisfaction and loyalty because they have a forum where they can offer suggestions and feel that they are heard. Giving agents a voice makes them actively involved in improving the business. They can offer suggestions to improve customer experiences or pain points preventing them from delivering excellent service. If the business takes action to implement or solve these issues, employees feel engage and job satisfaction rises.
Related resource: For more personalization ideas, download “14 innovative personalization ideas for your contact center.”
Idea 3: Upgrade contact center customer experiences with advanced conversational AI
Many customer inquiries can be handled through self-service by a bot. Resolving their own issues would be just fine for the 68% of customers who’d rather use self-service channels for simple questions or issues.[iii] The problem is that 90% of businesses believe chatbots and virtual agents need to get smarter before consumers are willing to use them regularly.[iv]
To be effective and increase customer adoption, it’s imperative for virtual agents to understand sentiment, context, and intent, and be able to handle conversations when customers switch topics. When they provide accurate, relevant answers and know when an interaction would be best handled by a live agent, virtual agents successfully understand and speak the language of customers.
To achieve this, ensure virtual agents are powered by natural language processing (NLP) and AI; specifically, continually improving machine learning (ML). These advanced technologies allow virtual agents to communicate with customers in natural language without forcing them through a structured menu that may or may not lead to the information they seek. Additionally, machine learning enables virtual agents to get smarter with time and use. Eventually, they’ll know what "in a pickle" means.
And for the record, according to What’s the Sitch, “to be in a pickle is to be in a situation in which you are pulled in multiple, opposing directions, akin to one’s tastebuds when subject to the sweet and saltiness of a pickle.”[v] The phrase also has origins in baseball, when runners would get caught between two defending fielders while trying to make it safely to a base.
Smart virtual agents that use conversational AI can be deployed in chat and voice channels and integrate with automation tools and back-office systems. They can also easily perform the following tasks:
- Digitally guide conversations with minimal escalations
- Use customer data to personalize interactions
- Answer frequently asked questions
- Schedule and make changes to appointments
- Collect customer information and share it with agents in real time
- Proactively reach out to customers with personalized messages
Conversational AI is essential for virtual agent effectiveness. Because people use various ways to describe what they need help with, non-AI bots can get quickly tripped up when they haven't been programmed to process certain words or phrases. A bot that repetitively responds with, "Please rephrase your question" signals to customers that the business doesn't speak their language fluently.
For the best self-service CX, implement a virtual agent that uses conversational AI and machine learning.
Idea 4: Use real-time contact center analytics to empower agents to engage customers in more effective live conversation
All feedback, whether it's given to a pet, a child, or employees, is more effective when it's given during or immediately after the event. Unfortunately, in the case of quality and performance feedback, agents typically receive coaching several days or even weeks after the event or interaction took place. They may not even remember the interaction they're being coached on, which diminishes their ability to improve on their past performance.
Real-time interaction guidance helps solve this problem by coaching agents in the moment. The guidance uses AI trained on the largest interactions database in the world to detect and objectively measure sentiment and soft-skill behaviors proven to improve customer satisfaction. When the system detects low sentiment or behavioral metrics, real-time interaction guidance prompts the agent in the moment to remind them of their training. For example: to listen more actively, to show empathy to the customer’s situation, or to exhibit other soft skills that can improve the customer experience.
But don’t stop there. Real-time guidance is a reinforcement, but not a method to guide an agent’s overall performance. The same real-time methods should be measured post-interaction and delivered in easy-to-read dashboards for agents to review their own high- and low-scoring behaviors. This provides continuous, focused, and measured improvement. Supervisors should have their own dashboards with metrics across teams and so they can also find coaching opportunities at a glance.
All these behavioral metrics can roll up to an overall team, departmental, or site customer satisfaction score so that the entire organization is focused and engaged on improving the same KPIs.
Idea 5: Provide customers the option to navigate the channel of their choice
Offering multiple communication options to customers empowers them to use those they find convenient and most appropriate for their issues.
Offering channel options can influence customer behavior and loyalty. NICE research revealed that 90% of consumers are more willing to do business with companies that offer multiple ways to communicate.[vi]
Those channel options should include self-service. Most customers prefer to solve their on digital channels themselves, and only contact customer service as a last resort. In fact, many of them have an aversion to contacting customer service. Relationship management with customers who don't want to interact with agents requires an offer for effective self-service options.
Most resolution needs events begin with a search on the internet or your company's website. To meet customer expectations, first-rate knowledge management systems help deliver accurate answers quickly. The right knowledge management system can even extend answers to search engine search results, which means customers don't have to go to your competitors.
Adding self-service and additional digital channels adds friction to the customer journey when done incorrectly. 96% of customers think businesses should make it easy to switch channels,[vii] which makes omnichannel capabilities a significant asset.
Omnichannel customer experiences enable customers to move seamlessly across channels without being required to repeat information. The result? A much slimmer chance of negative feedback.
Do you need an interpreter? NICE helps you better understand the language of your customers
Interpreting and responding to what your customers tell you requires good technology and a disciplined approach to customer experience management. To jumpstart your efforts to meet customer expectations, download our complimentary mini guide, "Cheat Sheet for Customer Loyalty."
[i] Salesforce: Trends in Integrated Customer Experiences (2018)
[ii] Microsoft: Global State of Customer Service: The transformation of customer service from 2015 to present day (2020)
[iii] Salesforce: State of the Connected Customer, Third Edition (2019)
[iv] NICE CXone: 2020 Customer Experience (CX) Transformation Benchmark (2020)
[v] What’s the Sitch?: In a Pickle (2020)
[vi] NICE CXone: 2019 Customer Experience (CX) Transformation Benchmark, Global Consumers (2019)
[vii] NICE CXone: 2020 Customer Experience (CX) Transformation Benchmark (2020)