When a customer calls a brand’s 1-800 number, their experience interacting with the call center agent can make or break their brand loyalty. Customer experience is a top concern for businesses that want to ensure customer retention and improve sales. Enterprise organizations have adopted the term “voice of the customer” (VOC) to describe customer feedback about products and services. A typical VOC program seeks to understand the customer journey, and their needs, wants, and expectations. Most companies measure these things with surveys or other standardized methods, but there is a powerful tool that many enterprise companies have yet to utilize: speech analytics.
Natural Language Processing for Customer Experience
Within the contact centers of enterprises, speech analytics is still unfamiliar territory to most. More businesses are choosing to adopt the technology as digital transformation and cloud-based infrastructure is gaining popularity. However, most contact centers for large brands still manually listen to and score only 5% of calls; this means a manager must personally listen to the recorded calls one at a time, note the findings, and act based on those findings only. By using speech analytics, 100% of all calls are analyzed automatically with machine learning algorithms, thus reducing cost and time significantly.
By leveraging this powerful technology, brands can access a wealth of value, optimize their customer experience, and in turn increase profits through more effective customer retention.
What is Natural Language Processing in Speech Analytics?
Natural Language Processing (NLP) in speech analytics provides the ability to parse and translate unstructured data like human conversations on a recorded call. NLP is what allows a system to determine whether you stated you are calling about a “fraudulent transaction” or a “new account.” Speech analytics goes beyond the words that were spoken. In human communication, how you say something is equally as– and sometimes more–important as the words themselves.
Sophisticated speech analytics platforms determine emotions, attitude, and can even alert a manager when callers are using explicit language. Machine Learning can even catch patterns that humans may not notice. For example, medical research institutions have studied using speech analytics to alert doctors if someone may be more at risk for manageable neurological conditions, such as anxiety or depression, based on their speech patterns and other nuances long before they present typical symptoms. These highly adept systems take massive amounts of unstructured data (the raw recorded calls) and turn it into a structured format that can be easily manipulated and visualized in your choice of analytics tool, such as Tableau, putting the Voice of the Customer at your fingertips.
Untapped Organic Customer Sentiment
Typically, a contact center relies on classic scoring metrics, such as a Customer Satisfaction (CSAT) score. This is captured by asking a customer to participate in a survey after the call or via email by rating their experience. CSAT is a good industry-standard tool to gauge overall customer satisfaction; however, post-interaction surveys only capture responses from customers who choose to stay on the line and provide feedback. In order to gain this information, companies implement these surveys at multiple points of the customer journey, resulting in an increase in customer feedback fatigue. To replace this declining source of evaluation, customer experience experts need a new way to capture these assessments without extra effort.
Using sophisticated language models, speech analytics can ingest and measure both sides of the conversation, without any additional involvement from either party. Measurements taken include customer tone, pitch, the amount of silence on the call, and additional emotion scoring, such as if the customer was truly satisfied by the end to indicate that the agent had completed their request. By combining recorded calls and text scripts from customer service chats and social media, brands would receive a comprehensive view of their customers, as well as their perception in the market.
Your Agent Performance
Agent performance is key to operational success in a contact center. They are your brand’s key touchpoint and interact with your customers daily. Using speech analytics, you can easily measure the top performing agents to discover what tactics work best as a model to train other employees. You can also track agent improvement over time in order to better align performance with goals and rewards. NLP models will quickly identify knowledge gaps where an agent may need supplementary training and alert their supervisor. For a more real-time adjustment, these models can provide live coaching to agents, where the system can be instructed to listen for key phrases and alert the agent with suggestions directly on screen.
Predict The Future
By training a custom model specific to your business needs, you can unlock insights that give your brand a strategic advantage. Use these algorithms to identify the caller’s needs and determine which agent is best equipped for that situation. Route that customer directly to the agent who is most likely to service them the best. Predict churn by analyzing calls in which a customer canceled service, and comparing them to calls in which a customer was retained. Speech analytics models can determine which calls signal for each situation moving forward and suggest an upgrade, special service, or other tactics to win that customer back.
Robust Analytics for The Entire Organization
Contact center metrics may seem like data only useful to a single department, but that is far from true. Every part of the enterprise can benefit from understanding the voice of their customer, and how it relates to overall performance. As our Director of Support likes to say – “What is in your calls today will show up in your financials at the end of the month.” Customer experience is directly linked to profits. If you’re not on top of your customers’ experience, how will you know what’s going on?
Speech analytics platforms allow everyone from the contact center agent to the CEO to discover insights hidden within customer calls. From big picture metrics like overall sales trends – to more granular data like what demographic is most likely to purchase a certain package. NLP technology allows you to discover pain points and gaps in the brand experience, as well as track overall brand perception. Close alignment with customer interaction data is currently a competitive advantage, but will eventually become a basic necessity.
Your customers are speaking. Are you listening?
