Call Centers, Customer Journey & AI

VoiceSignals #12 — Musings on Voice tech news

Is it Call Center or Contact Center? We see it written both ways, but key differentiator in our minds is old vs. new, where Contact Centers are taking a more omnichannel approach, incorporating voice assistants, chatbots, emails, social media monitoring, on top of the traditional agent-customer phone call. Call centers are modernizing, and in an effort to improve overall customer experience(CX), but also efficiency and performance, they’re turning to technologies, like AI, to shape their …contact centers.

A new revolutionary way of establishing meaningful communication with the customer is happening; NLP, training data, machine learning, are becoming part of their vocabulary. They understand that in order to compete with hundreds of other call-center services, limited customer satisfaction surveys or monitoring less than 0.2% of their agents’ calls, won’t cut it anymore.

Artificial intelligence in call centers is built on speech analytics, and now it can go beyond the basic speech-to-text analysis. The emotional and behavioral quality of the representative and customer can be assessed and analyzed on 100% of calls. This assessment lets the managers analyze the common problems faced by agents and assist them by coaching them to become more efficient, using successful examples, or by understanding better customers’ needs and addressing them efficiently. With growing advancements in Natural Language Processing and more sophisticated algorithms coming into play, AI is now able to achieve a more actionable set of solutions, like:

1. Rep <-> Customer Matching: Based on the affinity or rapport developed between people, AI can pair the contact center representative, with the right set of skills, to a specific customer in order to achieve more efficiently the desired outcome. This not only leads to a happy, loyal customer, but also to a satisfied representative for a job well done, reducing disengagement and attrition. Employee churn in contact centers is a real problem at a very high cost. Investing in knowledge, training, agent satisfaction, and smart tools can help lower churn and ultimately raise customer experience.

2. Analyzing Customer Journey: Customer Experience, as Morefield Communications says, is crucial today as brands are fighting for loyalty. With several channels of communication available to customers, ignoring how they feel after a support call went awry, means you’ll probably discover their rant on some social media platform. So managers at contact centers need to know what has happened over 100% of the calls. That’s where AI comes in. Not only can it catch disgruntled customers, but it can understand where the communication went wrong and even predict an escalation in real-time.

3. Predicting Intent: In 2020, analytics will make customer journeys smoother by alleviating contact center pain points and anticipating a customer’s future needs. For example, by analyzing communication interactions and using complex behavioral pattern algorithms, companies can predict outcomes like propensity to buy in order to effectively steer the conversation towards a sale.

Call Centers working on customer service, sales, or debt collection need to perform better in real-time and be able to analyze their own data from thousands of phone calls, in order to evaluate and understand their customer and eventually serve their own contracts better. AI is a one-way street if they want to stay in business.

What we read online…

Why Conversational Analytics is a Must for Any Company with Customer Calls

If, as a company, you’re using the telephone to communicate with your customers, you understand the value of keeping a record of the call and what was said in your CRM or wherever else you keep this data. But what about all the other insights you might be missing out on?
Conversational analytics is making it possible to not only categorize key elements of customer calls, but to rapidly analyze and utilize that data to predict customer intentions, quantify customer service performance in meaningful new ways, assess the overall quality of both service and products, and influence the outcome of these calls. Let’s take a closer look at what this entails and how conversational intelligence is helping to improve key service operations for so many organizations. Read more >

Predictive AI and Suicide Prevention [Podcast]

Sam Brake Guia, host of the Brain Bytes Back podcast, was joined by Assistant Professor of Biomedical Informatics, Medicine, and Psychiatry at Vanderbilt University Medical Center, Dr. Colin Walsh and the CEO of Behavioral Signals, Rana Gujral, to discuss how predictive AI is being used to identify suicide risks before they happen. Listen here >

Federated Learning and Data Privacy

We’ve all read about the privacy concerns the end-user has regarding who listens to their communications and how this data is being used by companies (usually for annotation purposes). It seems there’s a solution now that has us… convinced. Federated Learning is a machine learning setting where the goal is to train a high-quality centralized model with decentralized data. Well, that’s how Google puts it, but we like that they went one step further and decided to use comics to really explain it to us. And why is Federated Learning important in ML? Because of the training data, you absolutely need, and privacy concerns. The training happens on the device avoiding bringing the data to the company server. Furthermore, the whole process can be encrypted with a key which means secure aggregation that enables the server to combine the encrypted results and only decrypt the aggregate. But don’t take our word for it… Read more here >

Voice Technology Market in India

India is one of the fastest-growing economies in the world and an epicenter of call center services. It also has a lot of interesting companies and startups developing sophisticated AI software for contact centers. We wanted to see what the Voice Technology Market looks like in India and what the adoption rates of voice assistants are. According to a survey by WATConsult, the interest is still in its infancy but starting to catch up in large metropolis. Of those that use voice technology the majority use it on their mobile, but still, combine text with voice as they find it easier. They perceive Google Assistant as smart and intelligent, while Alexa is more reliable in managing smart home devices(IoT). The market is expected to grow by 40.47% by the end of 2020. Read more >

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