Artificial intelligence has revolutionized the customer experience landscape. Customers are no longer interested in archaic approaches to personalization — “people who bought this also bought this.”
It’s too broad and doesn’t account for unique factors like individual passions, lifestyles, needs of the moment, current location, and more.
For example, a customer who orders shampoo and conditioner from a drugstore app is not interested in complex hair serums in their product recommendation — no matter how many times people have bought these things together.
Effective AI personalization tapping into the user’s browsing history would tell the retailer that this particular user spends considerable time when buying advanced chemical-based products. A complex hair serum is not something they would buy on the fly. A better product recommendation, for this unique buyer, would perhaps be a skin moisturizer that they usually get or a lip balm that they may be running on low depending on their last purchase date.
Hyper-personalization allows customer experiences to be tailored for each, individual customer. Browsing history and order history are only two of the multiple-hundred factors that AI systems study to create and identify user patterns.
Some popular ones include location data, customer preferences, customer service interactions, demographics data, and more.
In this article, we’ll cover AI’s influence on experience personalization and its impact on building better customer relationships.
What is AI personalization in customer experience?
AI personalization in CX means getting to know your customers to the last degree. It means throwing away the dated customer personas and focusing on treating each customer as a unique individual. It also means creating brand experiences for them that are tailored to their personalities and preferences.
Artificial intelligence studies diverse sets of customer data to help businesses achieve this state of hyper-personalization. These may include things like website visits, past purchases, CS interactions, demographic data, sentiment analysis, content consumption habits, and more.
With AI personalization guiding your marketing and retail, you can reduce a lot of cognitive load from users and help them make informed purchase decisions.
Instead of expecting customers to browse through your extensive inventory, you can leverage AI to identify their needs and patterns and help them find products and services faster and more accurately, ensuring better sales and improved customer loyalty.
How does AI improve CX Personalization?
Artificial intelligence uses a list of techniques to enrich customer experience and improve personalization. We list a few of them below.
1. Sentiment Analysis
Sentiment analysis is an AI technique that helps you identify, analyze, and understand the sentiment and emotional tone in your customer feedback.
Customer feedback includes things like product reviews, social media comments, customer emails, CS support interactions, and more.
When your CX is infused with sentiment analysis, it can:
- Tell you what emotion your customer is feeling (happy, frustrated, confused, etc.)
- Assign the feeling a score, underlining its intensity ( “89 Needs Attention Score” translates to “Act NOW to help this customer”)
- Suggest the best ways to help fix the situation for this particular customer (Offer them a discount? Arrange free delivery? Provide a free return?)
Sentiment analysis happens after the fact — when a customer has already left a review — and it can happen in real-time too, as customers engage with your customer service reps.
In both situations, sentiment analysis quickly helps you figure out what your customer is feeling and suggests the best possible ways to address their concerns. By improving customer service interactions, sentiment analysis helps you protect sales, customer loyalties, and brand reputations.
2. Precise ad targeting with geolocation
Location is one of many hundred factors that AI looks at when delivering extremely targeted customer experiences. Location may impact how quickly you’ll make a purchase — if you’re near a brand store, you’re more likely to step in for a cup of coffee or a quick perusal through the dress racks —, how much money you’ll be willing to spend, and how likely are you to act on a targeting notification sent on your mobile.
Geo-specific ad targeting allows you to use your marketing resources more wisely, so you only make the effort with people who are likely to respond, with offers that they are more likely to be interested in.
Starbucks is a popular brand taking advantage of this strategy.
Starbucks has claimed that the likelihood of a person entering their store after seeing a location-based ad increases by 100%. While it may be a claim, there’s no denying the general effectiveness of location-based marketing.
According to a report by Factual, ads targeted based on location result in an 89% increase in sales, 86% growth in customer base, and 84% increase in audience engagement.
3. Content personalization
Social media is popularly referred to as an echo chamber. Though the title doesn’t contain any positive connotations, the foundational idea is about creating super-tailored experiences for individual users.
What you like, click on, and view is the kind of content that the algorithm will feed you more.
Spotify is one of the leading technology and entertainment brands that are proud of the kind of hyper-personalization they offer their listeners, calling it ‘serving the narrowest of tastes’. So no matter how picky you think you may be about your music, Spotify claims that it can understand you and direct you toward artists and albums that you are most likely to enjoy and find appealing.
Spotify also releases a Discover Weekly playlist for each of its 100s of millions of users. Each list is unique to the company’s over 300 million users and contains 30 songs that the user has never heard before.
How does Spotify achieve this feat?
They combine editorial insight with algorithmic intelligence to fine-tune their music and podcast recommendations. Studying a user’s streaming history, the company tries to understand the kind of music they respond to — down to the beats per minute in their favorite songs — and gives them music suggestions that are as closest to their tastes as possible.
4. Product recommendations
While AI has made waves across the board by proving its relevance to everything from logo-making programs for small businesses to improving gun safety in US schools, its impact has been the most longstanding for making increasingly relevant product recommendations.
Businesses have always turned to AI to help them learn what their customers may want to buy next. It has become so prevalent that 52% of customers now expect offers to always be more and more personalized.
The latest AI models not only study customer data but also product data in detail. By knowing the most minuscule attributes about the products, these models succeed in recommending the right kind of product to the right user.
For example, if a frequent shopper on your online store visits again, a highly sensitive product recommendations algorithm will study their customer profile along with the portfolios of products currently available in stock.
So these product recommendations are going to be finer than ‘Here are 6 more pairs of shoes for your perusal’. Instead, the user will be shown a grid of product images with 6-inch stilettos, in varying colors of red, all in a certain price range, and ready to be shipped overnight.
5. Dynamic websites
Providing personalized ad and product recommendations is good, but imagine if you could bring this sort of granular individuality to the entire experience, starting from the very beginning — your website?
Dynamic websites are the more intelligent answer to static websites. With a static website, you have a uniform set of pages for your entire user base from Timbuktu to Tahiti.
Anyone who visits the site is shown the same homepage, the same product listings, and the same checkout experience.
With a dynamic website, there’s more fluidity and compassion in the experience.
Your social media sites (plus Netflix and other streaming services) are some of the leading examples of dynamic website experiences where your entire feed is suited to your personality.
Dynamic websites allow you to present different versions of your website to different users. Based on their past interactions with your brand and their unique user profile (plus a hundred different other factors), a dynamic website will change its appearance and content to suit what this unique user prefers.
Dynamic websites are created with behavioral data and server-side codes, kind of on-the-fly, and have different content for different users. Not only such a homepage will address your user by name, but will also show their past purchases, recommend products based on that data, and facilitate quick sales.
Once again referring to the example of our e-commerce user, a dynamic website will present itself to her very differently compared to another user who is there to buy hiking shoes for their next trip. Everything from the hero image on top of the page to trending items, and from a relaxed browsing journey to a straightforward jump to the checkout page is going to be tailored to their unique personalities, current needs, and purchase behaviors.
To make your dynamic websites work more effectively, consider offering responsive pricing where the AI systems make subtle changes to your product prices based on inventory levels, competitor pricing, customer location, weather changes, and more.
Conclusion
Modern customers expect their online experiences to be extremely personalized. They are savvy enough to spot a mass-targeted offer when they see one, and they aren’t interested. For most of them, personalization is such an important part of the customer journey that they feel upset when there’s a lack of it.
Utilizing insights and information gleaned by AI-powered tools, businesses can incorporate personalization at every step of the customer journey map. Browning history, past purchases, demographics data, current inventory details, location information, and hundreds of other factors can come together to help your business offer highly targeted and tailored experiences to each of your customers.
Whether you are a small business or a large enterprise, AI helps you meet your sales goals, improve your brand loyalty, and adjust your offerings by serving your customers in increasingly personalized ways.
Image Credit: hauntedeyes @Unsplash
