AI for CX: How AI can help improve customer experience
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McKinsey and Co. declared 2023 “generative AI’s breakout year” and, less than a month into the year, The New York Times has already declared 2024 the year AI will ‘Leap forward.’”
However you spin it, this year AI will experience rapid advancements along with increased adoption rates that will change how businesses operate.
Customer experience is already undergoing its AI-driven transformation, and the businesses that consciously make AI a part of their CX strategy now have a lot to gain in the future.
When considering how best to incorporate AI into any business function, it can be helpful to think of it as a new hire on your team. Consider what it is great at, and use that information to identify the jobs it will be best at.
Today’s AI has a number of core competencies that can be helpful when improving the customer experience, including:
Analyzing data: No human can process, understand, and analyze large, complicated data sets like AI algorithms can. With AI, businesses can make sense of the customer data they have collected to identify patterns and trends.
No off switch: Robots don’t need breaks or sleep, meaning they are available to service customers around the clock.
Making predictions: AI can use historical data and statistical modeling to make predictions about the future.
Generating content quickly: ChatGPT and DALL-E have proven that AI can generate serviceable content on just about any topic — and fast.
Automating manual and repetitive tasks: When AI takes the more tedious tasks out of your team’s day, there is more room to elevate the customer experience.
One of the most exciting things about AI is that we can’t really predict what other skills it will pick up over time. But we can assume that it will get better and better at the core competencies listed above, and will expand its skillset in some categories like content generation.
Taking the list above into consideration, here are just some of the ways AI can help improve customer experience right now, and how that could get even better in the future:
Nothing beats a human-to-human interaction, but delivering that kind of personalization to tens of thousands if not millions of customers on a daily basis is simply impossible. With the help of AI, you can personalize interactions at scale, across the entire customer experience.
The most popular and common use case here is recommendation engines. These use data to surface the most relevant products or content pieces based on a particular customer’s behaviors and activities.
But personalization doesn’t — and shouldn’t — end there. Already, AI-powered live chat can surface information like order status, account details, payment history, and more to personalize interactions with customers, and marketing automation tools allow you to personalize emails and SMS content with ease.
Example of a personalized email from Loom, source reallygoodemails.com
Many businesses are already using AI to offer personalized offers. For example, the AI might learn that a certain customer would be interested in a product or service that is complementary to one they’ve already purchased. It could then offer either a dollar-based or percentage discount if they sign up. Even the amount and type of offer could be calculated by the AI based on the offers they’ve taken up in the past.
These are just some examples of how AI can fuel greater personalization. Overtime, this will become even more sophisticated, and customer-brand relationships will be we
We’ve already seen how quickly AI tools like ChatGPT can generate how-to and explainer-style content for self-service libraries like knowledge bases for SaaS products. There is a limitation here though — the AI needs existing content on any given topic to reliably produce a new article. And when we’re talking about creating a net new how-to piece on a new product or feature, it’s unlikely the AI will have enough to work with.
There is, however, another huge opportunity with AI content generation. This year, as The New York Times says, “Chatbots will expand well beyond digital text by handling photos, videos, diagrams, charts and other media. They will exhibit behavior that looks more like human reasoning, tackling increasingly complex tasks in fields like math and science.”
This means AI could help businesses create different types of educational content, based on the information in your existing knowledge base. For example, if you have a lengthy piece on how to use a certain feature, the AI could turn it into a video and product diagrams or charts.
By creating different types of content, you are improving the customer experience by servicing different types of customers and helping more people find the information they need.
Improving customer service often involves decreasing wait times and increasing response rates. Delivering on these two objectives when customers live in different timezones or simply get online outside of business hours can prove a struggle for companies with a centralized customer service team.
Today, AI makes it possible to provide basic support outside of hours thanks to chatbots or search engines that surface information from your knowledge base or customer data. Over time, as the AI learns more about your offering, the gap between the AI’s service and your human team’s service will slowly bridge so that, eventually, only very high-level or unique queries will need to be escalated.
Every time a customer does something like visit your website, see your advertising, speak to your support team, engage with your owner content, or complete a form or survey they are creating another data point. All these data points create a mass of information that a human would take weeks if not months to sort through.
AI can quickly process that data and identify patterns in behavior to help you map a more accurate customer journey. The insights gained from this can be used to create a more helpful customer experience and one that ultimately improves business performance over time.
Translating email content, knowledge base articles or blogs, customer service interactions, and more into any language can be a time-consuming and expensive task. With AI, translations happen quickly and easily in real-time.
While the best translations still come from human translators, AI does a reliable job of translating content to help you service more customers in their preferred language.
An exceptional customer experience happens when a business can get ahead of problems before they arise. Predictive analytics can help you do just that — AI can make predictions about a customer’s future behaviors to preemptively send help documentation about their next best action or prompt a customer support agent to reach out if a customer is at risk of churning.
Large businesses with multiple support platforms including live chat and phone calls will generate a huge volume of feedback from customers. AI can take the transcriptions from these interactions to identify common themes, phrases, or terms, generate insights about where in the customer journey support is most frequently called upon, and report on the type of customer most likely to require additional support.
These insights can help you make data-driven decisions about things like expanding your team, creating or updating knowledge base articles, and creating journeys that are more helpful for your customers.
Data has been informing how businesses prioritize new product releases, service offerings, and feature updates for some time. AI can assist with these decisions by identifying patterns within datasets from things like customer feedback and social listening. This can be particularly useful when you have large datasets like those from social listening, and when you want to get unbiased (or less biased) information on how to prioritize.
When it comes to existing products or services, AI can also help you predict how much inventory or human resources you’ll need to serve your customers at any given time using predictive analytics.
Giving the people what they want and resourcing appropriately gives your customers a better experience because their needs are being met, and they are not subjected to constant out-of-stock notifications, website crashes, or huge delays between appointments or consultations.
If you feel like understanding the end-to-end customer journey is a mammoth task, you’re not alone. It is more complicated than ever before, with an overwhelming number of channels, platforms, and data points to digest. Using AI will take the heavy lifting out of the jobs to be done, working hand in hand with humans to deliver an exceptional customer experience.
Chloe Schneider is a content writer, strategist, and editor with over 14 years experience telling brand stories that get repeated at dinner parties. Her career started in editorial, but she quickly made the shift to branded content and integrated marketing, leading her to roles including Director of Branded Content at Mashable and VP, Brand and Integrated Marketing at mindbodygreen. Chloe prides herself on being a pragmatic creative who builds content strategies that are equal parts data-driven and intuitive.
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