Building a Foundation for AI Personalization 

by Brian Flanagan, Perficient Digital 

Most companies know that personalization is an effective way to increase relevance and build long-term customer relationships. In fact, 93% of marketers agree that personalization helps to advance customer relationships (Evergage). However, many companies still struggle to deliver personalized experiences.

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The problem isn’t the ability to deliver targeted information to an individual user, but rather to deliver personalization at scale. It’s easy to think about five or 10 variations of an experience, but what about millions? This why many organizations are looking towards artificial intelligence as a way to automate personalization.

The potential for AI is unbound. With machine learning, we can use data to observe, understand and anticipate the needs of customers. However, AI isn’t a silver bullet that’s going to do all of the work for you. You first have to develop a strategy around personalization and then use technology to enable it. 

Understand the Journey from the Customer’s Point of View

Creating an effective personalization strategy starts with understanding the customer journey. The goal is to be able to customize every touchpoint to match the individual’s needs, preferences, and intent. To achieve this, you have to develop a 360-degree view of the customer and then identify opportunities to improve their experience with relevant content, offers, and calls to action. 

You also have to consider that your customers’ journeys will likely involve third parties and interactions you don’t own. Let’s say you’re a utilities provider and your customer purchases a Nest thermostat from Home Depot. That product will impact your customer’s energy experience, but you won’t know they’ve installed it unless they tell you, right? You want to learn what products they own so you can continue to build their profile and support their journey, but first you have to show them how providing that information can improve their experience.

We helped a utilities client in this situation by implementing feature we call “Milestones.” With Milestones, a customer can add information to their account profile (e.g. “On this day, I installed my new Nest thermostat”) and then track the impact that product had on their energy usage and monthly bills. So even though the company was not directly involved in the purchase of the thermostat, they are able to create an improved experience by connecting to it. Showing your customer that you can make their lives easier and help them achieve their goals will earn lasting loyalty and encourage them to engage with you even more.

Develop a Content Strategy that Keeps Up

Many organizations struggle with content strategy, but it’s crucial to making personalization work effectively. Where there used to be one version of content for everybody, there now may be five or six content versions based on different audiences that need to be managed and expanded as personalization efforts grow. 

AI can help carry the load by determining the right content for an individual and then automating delivery from the pool of content you’ve created. It can even gain insights from factors like customer behavior and use those to further personalize without requiring new written content. For example, Uber can say to a user, “Hey, you took 40 trips this year, traveled 350 miles, and met 25 different drivers.” Nobody had to generate that content. Uber would just need to define rules and train the AI to pull the data and plug it into the customer-facing story. 

Know Your Systems and Capabilities, and Grow Them

Personalization isn’t possible without the right technology - and knowing how to use it. We see a lot of clients that have great tools in place, but don’t really know how to use them to drive personalization. It’s like owning a Ferrari, but only using to go to the grocery store.  

So how do you go from the grocery store to the Autobahn? From crawling down side streets to flying down the highway? Well, you have to start small and then build a foundation for propelling more advanced experiences. Perficient Digital has a model that we use to illustrate the different personalization types, ranging from simple to complex, and the progression from rules-based personalization to cognitive. Over time, your solution should evolve from simple rules-based targeting against broad segments to cognitive solutions that understand and respond to individual customers’ intent.

Perficient Digital’s Personalization Spectrum

Perficient Digital’s Personalization Spectrum

The more effectively you can use strategy and technology to understand customers’ intent and personalize experiences to meet their needs, the more they will trust and rely upon you to make their lives easier.

Brian Flanagan, Perficient Digital

Brian Flanagan, Perficient Digital

About the Author: For more than 20 years Brian has worked with clients to design and execute cutting-edge user experiences. As a digital experience strategist, he is responsible for driving digital strategy for enterprise clients and oversight in delivering best practices. In this role, Brian keeps Perficient Digital and its clients on the cutting edge of new design strategies for next-generation technologies to consistently exceed client and peer expectations.