Marketing shifts toward AI-driven tailoring

Customers expect more from companies than ever before. While brand recognition, solid value, and a quality product still matter, Customer Experience (CX) is quickly becoming one of the hottest buzzwords in marketing circles. In fact, 73% of all people point to customer experience as an important factor in their purchasing decisions, while only 49% of consumers say companies provide a good customer experience.

Digital marketers are beginning to bridge the gap by using AI to provide a more personalized customer experience. Essentially, these firms are collecting massive amounts of data, crunching the numbers, and using machine learning algorithms to put together the pieces of the puzzle.

“Big data, supported by AI and predictive analytics, is also helping brands to learn more about their audience and customers,” concludes Michael Brenner for Marketing Insider Group. “It’s enabling hyper-personalization of customer experiences and marketing messages at scale.”

This technology helps marketers get the right message out to the right people at the right time. Keep in mind, however, that these organizations are not replacing their people with machines; instead, AI plays a supporting role that enables employees to be more effective.

Recommendations by Stitch Fix

One of the most common ways that companies use AI for personalization is to offer recommendations. By combining data about customer demographics with their purchase history data, they identify trends and make educated guesses about what the customer would like to buy next. Companies like Starbucks and Amazon are prime examples of this classic technique.

A more interesting example — a company taking this one step further — is Stitch Fix. This personalized styling company disrupted the fashion retail industry by offering a unique service. Bernard Marr at Forbes explains, “With input from the customer and collaboration between artificial intelligence (AI) and human stylists, the online styling subscription service eliminates the need for their customers to go out and shop for clothing or even browse online, because they deliver personalized recommendations right to their door on a regular schedule.”

What makes Stitch Fix unique is that its technology performs the analytics and offers suggestions to the expert stylists who, in turn, create recommendations for the customer. This provides an exceptional example of how companies at the cutting edge combine human and technological resources to craft a superb customer experience.

Eric Colson, chief algorithm officer at Stitch Fix, said it best: “Our business is getting relevant things into the hands of our customers.”

Value from Under Armour

Another company that’s breaking the mold with AI personalization is American sportswear manufacturer Under Armour. They’re using tech to capitalize on another growing trend in marketing: providing free value to customers to increase brand loyalty.

Under Armour partnered with IBM to use “Watson AI” as a virtual coach, health consultant, and fitness trainer for their mobile app, Record. By collecting data about the user’s exercise habits, sleep patterns, and diet, the software makes personalized recommendations for goals and workouts.

As reported by The Baltimore Sun, the founder and CEO, Kevin Plank, claimed, “We’re now at a point where a shift is occurring, and consumers are demanding more of this information. This partnership will allow us to provide value back to the customer in an unprecedented way.”

By tapping into AI’s potential for creating personalized recommendations, Under Armour is going beyond offering product recommendations. They’re providing real value to their athletic users. It just so happens that those users are also their target customers.

The Trailblazer, Amazon

We would be remiss if we failed to mention Amazon in a discussion of using AI for personalized digital marketing. This e-commerce giant pioneered the field. They set the example for what a personalized customer experience looks like, and they are the benchmark for the industry.

One prime example is when Amazon began recommending products to customers in 2010. Since then, they’ve added features like Customer Questions & Answers and Frequently Bought Together. These were seismic shifts in the marketing landscape.

Amazon is still reaping the rewards, as they found that 35% of all their sales are generated by the recommendation engine. For a company with a net revenue of $232.88 billion USD in 2018, that’s a lot of money.

Smaller enterprises, however, can still get their slice of the pie. They can harness all the power of Amazon’s AI engines thanks to Amazon Personalize, a service offered via the Amazon Web Services (AWS) cloud. The service “allows developers with no prior machine learning experience to easily build sophisticated personalization capabilities into their applications, using machine learning technology perfected from years of use on Amazon.com.”

It has now been made available to all AWS customers. Amazon Personalize provides and manages everything from the pipeline to the creation of personalized search and customized direct marketing. Custom personalization models can be created in just a few clicks and can be easily integrated into websites, mobile apps, content and email marketing systems.

Even larger brands like Domino’s, Yamaha, and Zola are using Amazon Personalize for a wide variety of use cases, “including specific product recommendations, individualized search results, and customized direct marketing,” writes BusinessWire. This shows how this software-as-a-service (SaaS) enables businesses to scale by accessing tech without requiring infrastructure.

The Takeaway

AI personalization is just another tool in a digital marketer’s arsenal for making great customer journeys, which can pay huge dividends. As a report by McKinsey & Company concludes, “We know that personalization can deliver five to eight times the ROI on marketing spend, and can lift sales by 10% or more.”

Simply put, it’s a good business case. The tech pays for itself — and then some.

It is also important to note that, for the most successful companies, AI is part of a larger digital marketing outlook that relies on a company’s entire data infrastructure in addition to employee engagement. Good marketing does not appear robotic or unfeeling.

That’s why the robots play a support role. They work in tandem with the people who form the strategy and deliver the message to the customer.

This is also just the beginning. As machine learning becomes increasingly sophisticated, we can expect to see more reliable analytics and even more precise recommendations. And who knows — there are probably going to be plenty of things that we could have never predicted.