14 Ways to Use AI for Customer Engagement – Stories From Real Brands

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Finding products and services can be, well … exhausting. Sometimes, it's really hard to distinguish between competing brands. I can literally spend a couple of hours searching for a product and comparing it against others. What does win me over often, though, is how good the customer-facing team is once I take a leap of faith and buy a product.

A few months ago, I purchased a serum from a beauty brand based in Spain. I got it during the sales season, so I had to wait a little longer for it to be dispatched. But, when I reached out to customer support, they were very friendly and supportive. Even though I waited a full ten days for the delivery, I was so happy with the experience that I now shop from them regularly.

One of the best ways to keep customers engaged with your brand is to give your team some extra support from AI. Although the experience was seamless on my end as a customer, there is no doubt that the team used technology that made their responses personalized and efficient. Some companies find success launching a chatbot, for example, while others use it in the background for customer insights analyses.

In this article, I'll explain the different ways how AI technology could transform customer engagement - and perhaps a few will be the perfect fit for your brand, too.

14 Ways to Use AI to Engage Customers

1. Better Recommendations

As many as 81% of people surveyed by Forbes say they prefer buying from companies that offer a personalized experience. And, the reps surveyed in our State of Service report agree that personalization is now an expectation of most customers. By using AI, companies can analyze large volumes of data and offer experiences tailored to each customer.

Andriy Neborak, founder and CEO of Luxury Cleaning NY, uses AI for pre-cleaning consultations. This allows him to better qualify customers and offer more tailored recommendations. Before using AI, he says, the process of making an initial appointment typically entailed an exchange of emails or phone calls to gather clients' needs and property details.

"We designed a conversational AI-powered chatbot to make the process more efficient and easier," he explained. "The chatbot is integrated into our website and asks clients a number of questions about how they like their home to be cleaned, what their living situation is like, and special requests."

This approach has been very useful to the company. How so? The AI collects a whole new set of data points for each user. This helps provide a more accurate cleaning quote and personalize their services accordingly.

For example, the chatbot recognizes that a user has a pet, and recommends pet hair removal add-ons. Or, asks if there are fragile surfaces at home to advise on extra precautions and care. With this level of customization, Luxury Cleaning NY not only started meeting but surpassing their clients' expectations right from the start.

"Moreover, the chatbot gathers precious insight into customer behavior (e.g., the levels of cleanliness people prefer, the specifics of their property), which we use to adapt our service catalog to meet customers' needs and to tailor future marketing campaigns," adds Neborak.

2. Proactive Outreach

Instead of waiting for customers to interact with a brand, marketers can use predictive analytics to anticipate their needs and send tailored offers. This not only allows companies to stay on top of customers' minds but also boost loyalty.

This is the kind of approach that Ninja Patches follows. Their Head of Marketing Brooke Webber told me they use an AI tool to help analyze users and suggest the right personalized emails for outreach.

"Mass email marketing doesn't really work anymore, and it certainly does nothing to maintain and grow our relationships with our customers. With AI, we can understand each user at scale and tailor emails based on past interactions, preferences, and behaviors. So, we're creating messaging that has real relevance and value for them," says Webber.

By automating so much of their email marketing process, Ninja Patches has more time to connect with customers meaningfully and create campaigns that speak to them.

"We've seen increased engagement and open rates because everything is tailored at the individual level without eating significantly into our small-business budget," adds Webber.

3. Customer Feedback Analysis

Customer feedback is an information goldmine. But if we wanted to go through each conversation manually it would take an awful lot of time. It's hard to believe that some time ago, we actually had to do it by-hand. Nowadays, companies can use AI to better understand their customers, spot trends and tailor offers. It even helps them identify emotions, and adjust specific touchpoints in a customer journey to better meet customer needs.

For example, you might discover that clients dislike having to file complaints exclusively via a form. By knowing this, you could offer alternative methods for filing complaints to keep them happier.

4. Sentiment Analysis

If someone told me I could only pick a handful of AI-driven customer engagement features, this one would easily make it to my list. Using natural language processing (NLP), AI can go through all of your past interactions with clients and scan them for the use of positive or negative terms.

For example, say that a client used a lot of positive words in their conversations with your support team in the past. They said they "love the product" or are "super happy with the quality."

Suddenly, they start using phrases like "worried," "I'm still experiencing issues," and "I would like a refund." Your AI could alert you about this change in sentiment as soon as it takes place so you can rectify the issue (and prevent clients from leaving).

Naturally, sentiment analysis doesn't apply only to individual customers. You can run it for your entire client base and divide them into "positive," "neutral," and "negative" groups.

That's what altLINE Sobanco does. As the company's president and CEO, Gates Little told me that you need a ton of data at your disposal in order for these large scale analyses to work well. Remember that you're not limited to text-based interactions with clients.

"We convert voice recordings into text using Amazon Transcribe and combine that with data exported from chat logs for analysis," Little says. "From there, we use Amazon Comprehend to perform sentiment analysis and gain insights that help us across virtually every department."

Thanks to this AI for customer engagement, altLINE Sobanco can spot common product pain points, verify customer success efficacy, and even gather ideas on how to refine its marketing messaging.

"AI helps us see our customers' needs on a much deeper level while keeping the process easily manageable and scalable," Little concludes.

5. Real-Time Language Translation for Global Support

One of my first jobs in the late 2000s was at a call center for a global web hosting company. Each shift needed an employee who spoke English, Spanish, and German, which usually translated to 2-3 staff members.

Nowadays, AI can help with real-time translation if you don't have a multilingual team. I was surprised to see that an early 2024 study even puts its accuracy rate at as high as 97%.

This AI feature is most common in text-to-text communication between brand and client. Depending on your company size, you can either use a professional tool that does the translating directly in the chat window or rely on ChatGPT's translations in a separate tab.

While not many brands use it (at least for now), AI can help with real-time translation, offering voice-overs on phone calls or captioning for video conversations with clients. If these voice-based tools work well, too, then companies won't have to worry about language barriers any longer.

6. Handling Interactions During Peak Season

People are impatient - they want their queries answered ASAP. And this can be hard, especially during peak hours or seasonal events, when the number of customer queries springs up like mushrooms. AI with its ability to quickly go through large data volumes simultaneously can be a huge help.

You've probably noticed that it's now difficult to find a brand that doesn't use AI chatbots, and it's no surprise, given their effectiveness and response accuracy. According to HubSpot's State of Customer Service Report, 77% of service teams are using AI, and 79% of service pros using AI find it effective. Harmony Lab & Business Supplies is no exception.

Their Principal Sean Clough shared with me that they have embraced AI to enhance their customer engagement, particularly through the chatbot system. This AI-powered tool has significantly improved their customer experience by providing instant, 24/7 support for common queries about their lab equipment and safety products.

"Our chatbot can quickly answer questions about product specifications, availability, and shipping times, freeing up our human staff to handle more complex issues. This means our customers get faster responses, even outside of business hours, which is especially valuable for labs that operate around the clock," says Clough.

What's really impressive is how quickly AI learns from each interaction. It's constantly improving its responses based on customer feedback and the questions it receives. This allows the brand to continually refine its service and address customer needs more effectively.

Clough says that "because of this, the chatbot has also strengthened our bond with customers by providing a personalized touch. It remembers previous interactions and can make product recommendations based on a customer's purchase history. For instance, if a customer frequently orders certain types of safety goggles, the AI might suggest complementary products or notify them of relevant sales."

7. Predictive Customer Support

AI can also let you stay one step ahead of your customers' requests or needs.

Say that you have a SaaS platform, and your website is experiencing unexpected downtime. You could use AI to prepare an emergency plan for scenarios like these. For example, you could set it to automatically send alerts to all customers the minute you confirm there's an issue. In your message, you could reassure clients that you're working on the problem.

Assuming no data was affected, you could also include a message confirming that their information is secure. This way, clients will learn about the issue from you and won't become anxious about potential attacks.

Of course, predictive support doesn't only work for crises. You could also use it to offer a discount code for products your customers have recently viewed numerous times or suggest complementary services based on their purchase history. There are countless ways you can be proactive with AI and boost trust.

8. Process Automation

Using AI for automating processes is becoming a necessity - it's no longer just a trait of innovative brands.

According to estimates, companies that use AI to handle omnichannel communication will boost their operational efficiency by 25% by 2025. This will be achieved primarily by giving AI high-volume, data-heavy tasks like data cleansing, segmentation, predictive analytics, and real-time data tracking. Meanwhile, employees will be able to dedicate more attention to building relationships with customers, offering that unforgeable human touch.

Finding the perfect balance between using AI and offering human support depends largely on your industry and client base (particularly, whether they're open to interacting with AI-like chatbots). For Frost Bank, finding that sweet spot is about keeping AI in the back office, while still putting humans in the front.

As a rule, the Texan bank avoids setting up AI on their website in any 'beta' or other experimental form. It appears that they don't want to take the risk, realizing that a single bad experience could hurt their relationships with clients.

Each communication channel has an agent available 24/7. This doesn't mean that their customer-facing staff doesn't use AI. When they speak to clients, they are able to use AI to summarize past conversations and generate suggested replies or edit their own for tone of voice.

While some could say they're too careful, Frost's use of AI-powered automation has helped them secure the number-one spot in customer satisfaction scores in the retail banking category - for the 15th year in a row.

9. Better Customer Segmentation and Profiling

Building customer profiles manually is usually a very tedious task, as you need to dive into a lot of data and find common traits and patterns among clients. It's not easier for emerging brands, as their customer profiles are often made in a 'hit or miss' fashion. But without this understanding of clients, no company can boost their engagement.

Nowadays, it's much easier, as brands can create accurate customer personas and segment their existing customers through criteria like behavior, demographics, psychographics, order value, and others.

Fintech brand FinlyWealth, for example, has identified a customer segment that tends to overspend on certain product categories.

"When our AI detects this, it fires off tailored budget tips," says the company's founder, Kevin Shahnazari. The AI then recommends relevant features that can give them more control over spending. "This proactive approach increased user engagement time with our app by 37% and improved customer retention rates by 22% in the last six months," he says.

FinlyWealth believes that the AI properly identifies customer groups, as they've seen a 45% increase in positive feedback - a lot of which specifically mentioned the tailored suggestions.

That said, client profiling wasn't entirely assigned to AI. "We found that coupling AI-driven advice with periodic check-ins by human financial advisors gives us the best of both worlds," Shahnazari concludes.

10. Great Omnichannel Experience

Here is an eye opening statistic: 91% of customers prefer brands that offer an omnichannel experience. And companies that use this strategy, retain on average 89% of their clients. You need to be able to meet your customers where they are.

If they start interacting with your brand on-site and then switch to an app or social media profile, they need to get a consistent experience. And that's what AI lets you achieve, as it can integrate data from multiple sources to help you close the gap between different channels.

For example, if a customer browses a product on a mobile app, they should see a tailored product recommendation when they switch to a website.

11. Competition Analysis

One of the best ways to engage customers is to understand how you're different from competing solutions - and, especially, what you can do better. This will not only help you retain clients but even attract new ones who might not be entirely happy with their existing brand.

Competition analysis usually takes weeks, if not months, and is never a done job. You must keep track of how others' offers are changing. All this is something AI can help you with.

You can provide it with a list of competitors, links to their websites, customer review scores, product information, and pricing, among others.

AI can cross-refer all the data and generate ideas, like what existing market gaps it found. Or, what are the most common issues clients report that you could use for your unique selling point. Using AI as a research assistant here will help you engage better with customers as a brand that actually "gets" their needs.

12. Content Recycling

What if I told you that you could use AI to recycle your content? Creating engaging content that is high quality takes a lot of effort, so it would be a real shame not to make the most of it, right?

RecurPost has integrated AI to revolutionize how they manage content recycling through their evergreen content libraries. Debbie Morgan, their Marketing Manager, explained that the AI-driven feature identifies top-performing posts and automatically schedules them for future publishing, ensuring that high-impact content continues to engage audiences without manual intervention.

How does it work exactly? For instance, if a post receives exceptional engagement, the AI tags it as evergreen, optimizes the timing for re-posting, and even suggests variations to keep the content fresh.

"This approach has significantly boosted our clients' content longevity and audience engagement. They benefit from consistently high engagement rates as their best content remains visible and impactful, boosting overall brand presence and connection with their followers," adds Morgan.

Some AI tools, like HubSpot's Breeze AI, let you automatically generate ideas for how to repurpose your content. This is a great way to make the most of your buck - you write just one blog post and can turn it automatically into multiple content formats for various channels. Genius!

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13. Personalized In-App Journeys

This AI for customer engagement method is particularly applicable to digital products. Instead of offering clients a nice personalized touch here and there, you could build out an entire personalized user path.

A great example of this is Traffic Think Tank, a training platform. The company's Community Advocate Leigh McKenzie told me that they use AI to drive content personalization throughout the entire user journey.

Whenever a learner starts interacting with specific course material, AI learns about their preferences and potential current skill sets. As a result, it tailors recommendations throughout the remainder of the training.

"If we don't have any data on a user yet, they can see recommendations based on what's popular on the platform," McKenzie adds.

"Our ultimate goal is to deliver more of what people want and guide them to the right resources, modules, and mentors the first time around. If we fail in that, it hurts our ability to provide value to the user and retain their business on our subscription model. Using AI to improve that customer experience is a win-win for everyone," he said.

14. Content Creation Ideas

How do you decide what content to create? You probably run a little keyword research and check Google to see what your competitors are up to. And if you're truly motivated, you might run a survey to ask your customers what they would like to read about. But did you know you could use AI to generate content ideas backed by data?

Mary Zhang, Head of Marketing and Finance at Dgtl Infra, said that her team uses natural language processing to analyze comments and questions on our articles about digital infrastructure. "This tool helps us understand what topics our readers find most interesting or confusing," she explained.

For example, we noticed a trend of questions about the environmental impact of data centers. In response, we created a series of in-depth articles and infographics on green data center technologies. This AI-driven insight allowed us to tailor our content to our readers' interests, increasing engagement and time spent on our site."

And there is more to it. The AI also helps the brand identify potential industry trends early, keeping their content fresh and relevant. By responding to their readers' needs more effectively, Dgtl Infra has seen a 30% increase in return visitors and a 25% boost in newsletter signups.

"This approach has really helped us build a loyal community around our niche tech content," adds Zhang.

AI-Driven Customer Engagement - The Future of CX

It's not a question of 'if' but how AI technology will transform customer engagement. Some brands are ready to go all in on AI's capabilities by implementing a chatbot and automating most customer-facing messages.

Other companies, particularly those where users might not be very tech-savvy, decide to use AI in the back office for better customer analysis and to relieve employees from mundane, time-consuming work.

While it's up to you to decide on the degree to which you want to use AI, I think skipping it entirely would be a mistake. If your competitors use AI, then so should you to keep customers engaged.

Topics:Artificial Intelligence

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