How Generative AI is Reshaping the Customer Experience
Contributed article by Marc Ferrentino, President & COO at
ChatGPT has captured our collective attention
over the past few weeks. From writing rap songs to planning beach vacations, OpenAI’s large language model (LLM) is resetting the
public’s understanding of AI’s capabilities.
Of course, generative AI has more functional
and consequential applications than picking a beach destination. For
businesses, this technology offers an entirely new way to interact with and
From creating engaging content to powering
unprecedented chat experiences to ushering in a new era of support automation,
generative AI promises new ways for businesses to meet shifting customer
AI-generated content will create better
The key advancement of generative AI is its
ability to not only analyze or aggregate existing information but to create new
outputs. Paired with natural language processing, this technology is capable of
generating organic-sounding, conversational responses to prompts.
That has significant implications for
businesses at a time in which content has become central to delivering
meaningful digital experiences. Delivering quality user journeys means creating
and updating vast libraries of content across various owned and third-party
properties… a process that requires significant effort across the enterprise,
from sales to marketing to operations.
Though ChatGPT isn’t going to take over as
your staff copywriter any time soon, LLMs do offer a path to more efficiently
creating content at scale. Imagine taking a description of a product or a blog
post and generating a list of FAQs from it. Or automatically generating a
response to a customer review in order to streamline workflows.
What’s more, AI-powered analytics systems can
in turn monitor the usage and impact of these knowledge resources and
automatically create additional content assets to fill the gaps in customer
This isn’t just a matter of saving time and
money. By increasing a business' capacity for creating high-quality content on
the fly, generative AI improves the business’ ability to deliver better digital
experiences to each and every customer.
Conversational experiences will augment
Various applications of generative AI have
already been woven into consumer search experiences. Popular search engines
like Google no longer strictly rely on keywords and backlinks, and instead use
AI to better understand the actual intent behind a user’s search query.
But the real difference maker will be the
proliferation of conversational experiences, which are increasingly used to
augment or even replace search in certain cases.
Not only can generative AI assist with natural
language understanding (NLU), it can return information in a more
conversational format. These thorough, readable answers lend themselves to more
“encyclopedia-style” searches like “how does knowledge management work?” or
“why do I need a CRM?”
Chat can also take the history of the
conversation into account, allowing a user to ask follow-up questions and dig
deep into certain topics. This makes chat ideal for sales and customer support
use cases (more on that in a moment).
Chat will never replace search entirely;
search will remain a superior solution for actionable, intent-focused queries
like “best CRM for SaaS companies” or browser-centric experiences like
ecommerce. But more users will gravitate towards conversational experiences for
certain tasks as the technology continues to advance.
Bing and Google have already announced conversational interfaces and this trend
will continue as the legacy search engines attempt to retain market share.
Automated customer support will improve
One of the best use cases for generative
AI-powered chat is customer support; perhaps no component of the customer
experience is as ripe for disruption. Chatbots and other automations have been
widely adopted as companies attempt to efficiently scale their support
offerings, but technological limitations often still lead to unsatisfactory
Generative AI is changing that. Just as with
search, its ability to understand the meaning of queries — rather than match
keywords — powers hyper-specific responses to user questions.
Backed by this technology, support chatbots
will provide conversational experiences that feel more like an interaction with
a real person. And not only will they reliably surface FAQs and support content
relevant to the individual user but, thanks to its automated content creation
ability, the AI will be able to intuitively create new content based on data
collected through support interactions.
Improving these interactions will ultimately
lead to improved customer loyalty and lifetime value.
Generative AI is still only as good as the
knowledge it possess
As impressive as ChatGPT and other early-stage
generative AI systems are, they’re still limited by the data on which they’re
trained. AI can’t use information it can’t find; a problem presented by
companies with poorly structured or siloed databases.
Knowledge graphs, which structure complex and
disparate data sets in a way that allows AI systems to draw connections between
different things in the world around us, will play a critical role in
businesses’ ability to get the most out of this new technology.
By investing in knowledge graphs and data
protections now, companies can set themselves up to hit the ground running as
generative AI tools become increasingly available on the market. That will mean
a more intuitive, positive digital experience and happier, more loyal