Let’s start with a moment we’ve all experienced. You’re having an issue with a company’s product. Whether it’s your cell phone, your bank account, or Starbucks mobile account. It’s safe to say you’re not happy, and you’re definitely not over-the-moon-excited to call or chat customer support. You probably don’t have much time, and you’re picturing yourself being shuffled from automated recording to automated recording, eventually screaming into your phone, “Speak to a rep-re-sen-ta-tive!”. Long story short, you want your problem solved as quickly and painlessly as possible.
It's the difference between a map and directions, between a recipe and a meal, between sheet music and a song. That's the difference between search results and a real answer to a question, and that difference matters a great deal to customer support teams.
We've written previously about why allowing AI to capture the "tribal knowledge" of your customer service teams is critical to deriving value from your artificial intelligence solutions, but the value of this practice goes beyond just optimizing customer service. Allowing AI to capture and quantify your "unwritten rules" has wide-ranging benefits for your entire business.
According to Forbes’ Predictions For Customer Service In 2019, the two most important things for customers today are convenience and speed. With that being said, the prediction that 2019 will be a record year in AI investment for customer support comes as no shock.
Many artificial intelligence solutions promise to make your customer support teams more efficient and effective, but how do you separate the vaporware from truly valuable AI-for-CS products and services? You use The PAC Framework for Customer Support Teams eBook
The PAC Framework is an AI evaluation tool developed by Talla to help you determine what tasks artificial intelligence software can actually perform, as opposed to what marketing spin and pundit hype suggest is possible. The PAC Framework is based around three types of AI skills: prediction, automation, and classification. These three things are what modern AI software is actually good at.
If the marketing hype is to be believed, artificial intelligence will soon be able to completely replace your entire customer support team, yet somehow no AI solution is out there causing massive support headcount reductions at any major business or agency. As it turns out, current-generation AI is really good at exactly three things, and none of them is replacing an actual human support representative.
Where do you work in a day? It’s probably not a short or simple answer. Support teams are constantly jumping between email, chat, ticketing systems, an internal knowledge base, and many other places. What they don’t need is another tab open. That’s why having Talla everywhere is so important to us. What does that really mean? Simply put, users have access to all of the information in Talla wherever they work. We want to improve your productivity and lower your time to resolution with AI-powered automation. The best way to do that is to ensure that Talla works within your existing workflows.
Artificial intelligence is powered by well annotated training data, but the data you need to train a customer support assistant includes more information than you might expect. The "tribal knowledge" of your customer support teams is critical to developing a customer service AI agent that can most effectively help your business.
We've all had interactions with clunky or incoherent chatbots that made their owners look dumb, but few companies know what steps to take to ensure their own bots don't make the same mistakes. Before you entrust a chatbot to help with customer service and support, make sure you've given it the tools it needs to avoid embarrassing itself.
We’ve written about how AI use is expanding across the enterprise and early-adopters are leaving the competition behind.
We’ve shared how AI is a superpower for customer support execs facing the daunting task of delivering scaled, personal and cost-effective support.