So let's dive into four areas that the customer experience can be improved with a variety of different AI / machine learning technologies.
Free the customer service team from the
mundane
AI can automate some
time consuming tasks such as data entry and directing a caller to the right
person to allow customer service representatives to focus on the customer’s
problem rather than gathering mundane information such as their name, address
and date of birth or answering simple FAQ questions. This is where chatbots and
virtual assistants can be deployed for basic automatic data entry.
Chatbots are designed to simulate human interactions
and provide immediate, personalized responses 24/7. This is particularly useful
managing customer questions or complaints. Virtual assistants on the other hand
can engage customers in simple conversations to check on orders or find
recommendations based on querying large databases of information, past
responses or predictive next best actions.
By automating the mundane parts of customer service,
the opportunity is to give the customer service team more complex tasks to deal
with.
Predict next-best actions
Brands have made a seismic shift in the last decade
away from telling customers what they want (okay, they’re still guilty of that
somewhat) to creating a brand experience that feels like it was tailored for
them. AI tools are enabling brands to accomplish this by sifting through
customer data and personalizing the information to offer relevant products.
These technologies help identify the consumer's needs
before they even know it (which in the past, visionaries like Steve Jobs have
done this with products such as the iPod and iPhone). In the world of
marketing, an insurance company could use a recent doctor visit to offer a
coupon for a medical device, or retailers could use smart shopping carts to
understand where the buyer is in his or her purchase decisions to recommend a product,
such as if they are buying ingredients to make a cake, it would recommend eggs, flour
and milk.
Discover hidden high-impact decisions
Delving deeper into the customer journey, data mining
looks at the bigger opportunities in terms of what future brand engagements or
actions could be, such as the banking example above with a customer inquiring
about a wealth management product and subsequently ending up with a college
fund. Whatever the challenge is, the key is that AI is being used to handle
that particular co-relation over more traditional, manual methods used in the
past.
Content that creates itself
Another way AI can be used to better the customer
experience is training it on business-specific metadata to dynamically generate
webpages, mobile alerts or other content-centric communications. For example, a
professional sports association wanting to drive more attention to its games
and get fans more engaged,they can use AI to deliver live statistics on each
game and provide fans a unique display of their favorite player stats on their
mobile device.
Investing in customer experience and AI should be a high priority no matter what industry. And it’s
not just about adhering to compliance and governance that should be the reason
for doing so – the customer expectation is changing and if businesses aren’t appealing
to them and making changes – the customer is going to find a different company to align their brand loyalty.
