Artificial intelligence is an ideal match for customer support workflows, but not every support workflow is ready for AI. To determine where your customer support AI opportunities lie, you first have to answer three basic questions:
Talla is an artificial intelligence solution that integrates with your knowledge base to answer questions and offer support in real time.
Artificial intelligence requires training data -- specifically, well-annotated training data -- in order to learn to do its job correctly. In fact, the data you've got lying around probably isn't good enough for AI. You'll need to refine your data before AI can use it.
"Inbox Zero" is all the rage for personal productivity, but the equivalent for your support team would be "Backlog Zero" -- and it's achievable with artificial intelligence.
We all know that Slack is awesome for knowledge creation. The ability for a team member to send out a question and quickly get a response is incredibly powerful -- we refer to this as transactional communication. For example, it’s great if you’re a support rep and your company has launched a new product. If you’ve been at the company for some time, you need to quickly figure out what’s changed and what’s still valid. If you’re a new rep, you need to quickly get up to speed on all the offerings. Yes, there might be training available, but people can only keep so much information in their head and searching online can be far too time-consuming. With Slack, you can simply post a question in your team's customer service channel, and get almost immediate results. Often, these types of channels have subject matter experts (SME) monitoring them and part of their job responsibilities is to answer these types of questions.
There are a lot of companies that want to use AI, but just don’t know where to start. 85% of executives believe that AI will give their business an inherent advantage (MIT Sloan Management Review and the Boston Consulting Group), however, of the half of CIOs planning to use AI, only 4% have actually implemented the technology (Gartner).
For those trying to introduce AI projects internally, generating buy-in requires more than facts and figures or trusting that the AI mystique will sell itself. As with any software sale, there will be an objection handling effort. It’s likely no one in your company has had to navigate this with an AI implementation yet, so you’ll find little internal advice. To help, here’s a brief look at three objections you’ll face. Included are insights on how to overcome each.
Customer support leaders are generally receptive to new technology that is faster, cheaper and more reliable. What they aren’t onboard with is overhyped tech that promises everything. It’s why AI gets met with eye rolls inside some offices. No one believes there’s a panacea for every support ail. Yet everyday unscrupulous marketers boast of AI as a cure-all. Often, they don’t even have true AI, just basic scripts or data science techniques. They promise big and invoke “AI” in their marketing to stay relevant. These products disappoint and it’s no wonder why the real opportunity of AI get lost as leaders grow wary of dubious claims.
For as long as there are businesses with customers, there will be a need for customer service teams -- but what your customer support organization will look like in the future will be heavily influenced by artificial intelligence and software automation.
Case deflection will be far more proactive in the future, as automation software will monitor customer usage of your products and services and detect problems as the happen -- perhaps even before the customer notices a downgrade in service or performance. This automation system will reach out to the customer itself -- via chat, email, autmated voice calling, or contacting their smart-speaker -- to advise on how to solve the problem without needing to search for advice in your FAQs or contact your support team.