According to Salesforce, 51% of customers expect that brands will anticipate their needs and make relevant suggestions before they make contact – by 2020. Well, here we are!
It’s amazing how much business has changed in the last 20+ years, and yet, it’s incredible how much it hasn’t. Take for example the concept of 1:1 marketing, introduced by Don Peppers and Martha Rogers in the late 90s. They defined 1:1 marketing (also called relationship marketing or customer-relationship management) as “being willing and able to change your behavior toward an individual customer based on what the customer tells you and what else you know about that customer.” Sounds like something that has been referred to as “personalization” in recent years but has evolved even further to “hyper-personalization” in 2020.
Let’s start with some definitions.
What is hyper-personalization?
Interestingly enough, there is not a clear definition of hyper-personalization; my search online found several very different definitions, some of which didn’t sound like anything much different from the definition of personalization. Here are two that I felt fit what I think of as I consider the meaning of this term.
Capgemini defines hyper-personalization as “an advanced and real-time customization of offerings, content, and customer experience at an individual level. Designed to perfectly match a customer, hyper-personalization leverages Big Data to deliver such tailor-made solutions in real time.” And, they note that hyper-contextualization is an integral part of hyper-personalization. Clearly, there’s also an element of speed included in this concept.
Three Deep says that “hyper-personalized marketing is the process of a brand speaking directly to one customer.” I like this definition and would only clarify it by putting quotes around “speaking” because hyper-personalization doesn’t just have to be about content and messaging.
Hyper-personalization includes – but also moves beyond – data-driven to analytics-driven. Artificial intelligence, machine learning, predictive analytics, and prescriptive analytics are important tools in the hyper-personalization toolbox.
How does it differ from personalization?
Personalization also takes many forms and has many definitions. Some will define it as simply as addressing customers by their names in emails and recognizing or acknowledging products they’ve purchased in the past. These are obviously simplified examples, but they are meant to be so as to clearly differentiate between the more-advanced and artificial-intelligence-driven nature of hyper-personalization.
Just addressing emails to customers by name is no longer adequate. Customers have changed. Customer behaviors have changed. Customer expectations have changed. They no longer say, “Know me.” Now it’s “Hear me. Know me. Understand me. Show me.” And “show me” translates to a lot of different things, like context, relevance, and timeliness. Context, as noted previously, is important to hyper-personalization. Context can come in the form of location, channel, time of day, product category, previous brand interactions, why a customer is buying, and more.
What does hyper-personalization require?
What do you need in order to create a hyper-personalized experience? Where do you start? It’s probably no surprise that the requirements are no different from designing, developing, and delivering any other kind of experience. It begins (must begin!) with customer understanding: Who are your customers? What are their pain points? What problems are they trying to solve? What are their needs and expectations? What are their preferences?
To get the answers to these questions, as well as the benefits and challenges of hyper-personalization and brands doing it well, check out the rest of the article on GetFeedback’s site.
Instead of one-way interruption, personalized marketing is about delivering value at just the right moment that a user needs it. ~ David Meerman Scott