Putting the "Person" Back Into Personalization

Why machine learning and AI are just the beginning

Bridget Fahrland

We are learning more and more about how giants like Netflix and Amazon are creating unique experiences for each visitor through a combination of deep machine learning, artificial intelligence (AI), algorithms, segmentation, and good old browsing and purchase history. Marketers are eager to learn how they can employ the latest and greatest technology and create experiences on the fly.

It all sounds so magical—and easy. But once again, the glitter of technology distracts from how to best build relationships with customers. Even a well-personalized experience, if not identified as such by the customer, will convert at best. But it won’t delve into deeper learnings through conversation, it won’t enable feedback, and it won’t get “credit” for aiming to better serve the customer. In short, “invisible” personalization misses a chance to build relationships. It misses a chance to make customers feel special.

There is no reason not to leverage machine learning and AI if you can, but while doing so your brand should do more. Here are four key steps:

“It all sounds so magical — and easy. But once again,
the glitter of technology distracts us from how to best build relationships with our customers."

1. Be transparent.

Customers are accustomed to personalized recommendations. They understand those recommendations are based on previous visits and purchases. But, if you are not transparent about the fact that the content or products being displayed are based on an attempt to personalize the experience, you miss a chance to speak directly to customers.

I love OpenTable’s transparency. It’s so simple. I trust the company’s expertise, given their data on reviews, ratings, and similar menus/price points. I know OpenTable is highlighting restaurants they think I would like versus the most popular.

Credit: Open Table

2. Encourage conversation.

Sure, you may know where customers are located, the referring URLs, the devices they are using, their previous browsing history, past purchases, and other demographic data. But, do you know what they want today? What are their pain points? What styles do they like? Stitch Fix is an example of a company that deftly balances explicit data (what customers tell you directly) with implicit data (what you know without them telling you). The company has developed a brilliant cycle of asking for input, matching it to an algorithm, getting feedback, and then refining the algorithm.

3. Tie personalization to loyalty.

How do you ensure that your personalization drives deeper relationships? How do you connect your personalization efforts across channels? How do you tie it to your loyalty program, and vice versa? Really, personalization and loyalty are two sides of the same coin. Your loyalty program has the data you need to refine your personalization, and personalized recommendations deepen loyalty and capture more data. It’s a virtuous cycle of learning, recommending, and rewarding. Sephora is an industry leader when it comes to omnichannel personalization because its loyalty program is the foundation of the company's recommendations and reminders.

4. Start simple, and start with a roadmap.

AI is sexy, sure. But you know what else is sexy? Driving results with simple personalization tactics like segmenting new and current customers, or geolocation.

Through my work, I help brands start simple and evolve with personalization roadmaps. These roadmaps help establish an overall vision, chart customer journeys, identify data sources, leverage existing technology, determine the need for new technology, and set phases for evolution from simple to advanced.

Personalization is certainly a hot topic, and as technology advances so will its applications. But, unless brands and marketers are willing to do their homework and build meaningful, honest relationships with loyal customers, the “person” element of the process is lost, and the user experience will fall flat.


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