Personalization

The right content. At the right time. For the right customer.

You’ve probably seen multiple variations of this phrase if you’re researched or worked on creating a personalized digital experience for your users. This is the version I use most often. It’s exactly what we’re trying to achieve when working toward personalization.

What does that mean? It often means something different for each individual customer/user, and something different to each individual organization whose goal is to provide this content. The main underlying similarity is that it means presenting content based on data and context.

For the customer

It means user experiences tailored to their needs and intents. This is something that retail personnel can tap into using conversational intelligence and having a dialogue with the customer. In the digital space, it means using information from past visits: to the digital real estate, retail, IVR, and chat. Any customer contact can be used to help present the right information in the right context for this specific visit.

 

For your business

It means ramping up your content creation efforts. That doesn’t necessarily mean more person-power. It should mean working smarter. That can consist of many things, like building content and design modules intended for reuse, a/b testing to determine the most effective content and design combinations, and creating a content intelligence system that allows your team to make better decisions based on data.

Rage with the machines

The end goal of that last point is to reach a place where you have a framework, workflow, and governance in place to create, review, and maintain your experiences. It should also mean working toward automation, utilizing AI and Machine Learning to enhance the decision making process, speed up content creation, streamline maintenance, and increase speed to market.

The struggle is real

This not only requires changes at the ground level in how you plan and work tactically. It’s also heavily reliant on leadership to see the benefits of leaving some decisions to AI. When your workflow is enhanced by AI and Machine Learning, you shouldn’t expect to see marquee x in slot y, even in an unauthenticated state. Experiences can be logically and usefully personalized based on cookied information, such as recent visit activities like searches, product views, adding items to cart, reading reviews, etc. Behaviors like that can help us determine what marquee is relevant to the current user.

When you get to an authenticated state, the only limits to what your can personalize are privacy concerns and customer suspicions. And leaders unwilling to move beyond static ads highlighting the latest offer, not personalized ads highlighting what’s best for the customer.

How did we get buy-in?

I created the following low-fidelity prototype/animation and a number of other resources to help explain the concept. With support form our leadership, we pitched it to a number of different teams.

Did it work?

It resulted in approval for us to host a personalization summit in Bothell, WA last fall. This summit brought together 30+ leaders from across our B2C and B2B organizations, including design and content, product marketing, technology architecture and development, brand, and others. We had pitch sessions, shared our personalization visions, collaborated, brainstormed, and eventually operationalized a task force, a smaller version of which is now working on a project to bring a true personalization architecture to AT&T. We’re also working through workflow and other considerations to make thoughtful personalization a reality.

 

Other materials

The pitch required numerous discussions, working sessions, presentations, and other temporary deliverables to be created. Here are a few of them.

 

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