When you contact a customer service department, you want fast and accurate answers. But in times of uncertainty, that preference can become a serious need. When demand spikes, call centers become bottlenecked with so many calls, chats and messages and too few human agents trying and failing to field too many queries. This leaves agents feeling burned out and inadequate. But it’s not their fault. They don’t have the right tools.
The COVID-19 pandemic has forced organizations to reimagine what “business as usual” means for their call centers. Traditional call center methodologies can frustrate consumers and employees in a few key ways.
They can’t scale
In times of emergency or uncertainty, call centers can’t keep up with outsize demand. And when demand falls, they end up laying off employees, crushing morale.
They aren’t data-centric
Data is not being sufficiently analyzed to generate insights that would improve customer service, and employees aren’t receiving training on the latest data because it’s too expensive.
They aren’t secure With agents working from home, managers have less oversight than usual. Knowledge bases are exposed outside the office, and many agents are taking calls in an environment that’s less likely to be monitored for quality assurance purposes.
These practices are unsustainable. Fifty-nine percent of customers say they have higher expectations for customer support than they did a year ago. Customers are demanding better service, and only organizations that take advantage of the latest technology will survive. Fortunately, chatbots have skyrocketed in popularity over the last decade, and customers are more comfortable using them than ever.
But customer service departments need more than just simple chatbots. They need to provide customers with fast ways to find information and resolve issues. They need a solution that provides more than just simple answers to simple questions.
In short, they need conversational AI. The technology uses sophisticated machine learning (ML) and natural language processing (NLP) to elevate customer experiences. These virtual agents can do so much more than just chat and relay basic information repurposed from a website. They can update your address, refill your prescription and upgrade your data plan. They can remember who you are and generate deeper insights about what you need. But conversational AI on its own is still not enough. To survive the next phase, customer service platforms will have to supercharge their chatbots with AI-powered search.
Just as you use a search box, a virtual agent must search through its corpus to find an answer for you. Search boxes used to be primitive, and you might not realize how far they’ve come.
- Keyword search: searches a database for documents that contain one of your search terms
- Personalized search: delivers personalized results based on your previous searches
- Recommendation engines: recommends content based on your previous interactions with a platform, without you even having to perform a search
- AI-powered search: uses advanced ML algorithms and natural language understanding (NLU) to predict answers to your questions
Conversational AI + AI-powered search is the next-generation paradigm for customer service, and organizations that don’t embrace both technologies will be left behind. Seventy-eight percent of customers (PDF, 524 KB) will back out of a purchase because of a poor customer experience.
Let’s explore the three ways this pair of technologies works together in customer service.