There’s a phrase that’s been thrown around a lot lately: hyper-personalization. But what actually is it? And how does it differ from good, old-fashioned, regular personalization?
In a nutshell, hyper-personalization is a marketing strategy that individualizes marketing tactics, such as email, ads, or website content, to make it seem like it’s designed just for you.
Hyper-personalization is a more sophisticated version of personalization – think of it as personalization 2.0 – leveraging more data, AI algorithms, and predictive analytics, to create a one-of-a-kind experience for your end users. Building unique experiences can significantly enhance customer satisfaction, loyalty, and engagement.
Let’s dive into hyper-personalization, its key characteristics, examples of what it looks like, and how you can use it in your marketing strategies.
You’ll often find that hyper-personalization has a few key characteristics that make it feel extra-targeted compared to traditional personalization tactics.
In-the-moment experiences: Leveraging data from various sources, such as website interactions, social media activity, and purchase history, to create highly personalized experiences in the moment.
Predictive analytics or predictive AI: Using data or AI algorithms to anticipate customer needs and desires, creating proactive recommendations and offers.
Contextual awareness: Considering factors like location, time of day, and device being used to deliver content that is relevant and timely.
Customer journey mapping: Understanding the entire customer journey and tailoring experiences at each stage to meet specific needs and expectations.
While personalization and hyper-personalization are both strategies to tailor marketing and experience to individual users, there are important differences.
Let’s say you purchase a dress from a clothing company and then a week later receive an ad from this company with recommendations for other items in your size. This is personalization because the company is using your purchase history to provide a list of similar goods.
If you were to browse the company’s website and it updated in real-time to show you products you may like according to what you’ve clicked on, that is hyper-personalization.
Take email marketing, for example. When you personalize emails, you’re often segmenting your contact base by similarity. This way you create custom communications for groups of people.
In the case of hyper-personalization, you could use AI-based email marketing to help you predict what your contacts would like to purchase next and incorporate that information into individualized emails.
It would be pretty challenging to predict customer habits or make recommendations without the help of AI. AI analyzes vast amounts of data to forecast the likelihood of future events, create proactive offers, and develop in-the-moment experiences.
To help you better understand hyper-personalization, it may help to think about some of the brands most of us use in our day-to-day lives.
Netflix (or your streaming service of choice) uses hyper-personalization to select TV shows and movies that it thinks you will like. Using predictive AI algorithms and contextual awareness (such as time of day, season, etc.), it creates a list of recommendations catered to you and your interests.
Spotify uses a combination of data and AI to create personalized playlists and recommendations tailored to your preferences and listening habits. Do you love listening to folk in the morning and heavy metal in the evening? Spotify has definitely picked up on those habits and your Daylist will reflect it accordingly. My evening playlist vibe is 70s-themed — honestly, pretty accurate.
Amazon suggests products based on purchase history and browsing behavior. Product pages are tailored to individual users (and that includes product descriptions and related items!) to cater to the aspects that you find most important.
If you’re not one of the Amazons of the world (and let’s be real, most of us aren’t), then you probably want to see what hyper-personalization looks like at smaller companies.
DailyLook, an online personal styling service, sent me this marketing text message on a Sunday evening during a football game that I was watching. To say the least, I was impressed!
This means that they have enough data to know my timezone and that I was likely watching the game Sunday evening. The fact that DailyLook sent a text message rather than an email shows their program has enough contextual awareness to know that I wouldn’t be checking my email on a Sunday.
While it’s pretty easy to determine a user’s location, Grove takes it a step further by referring to the cold snap we experienced in Colorado. This real-time data makes the information and products Grove provides feel more relevant, making me more likely to purchase their products.
Now that you have the meaning of hyper-personalization and examples under your belt, how do you actually implement hyper-personalization?
While you could attempt to set up hyper-personalization on your own, it requires a lot of data, maintenance, and knowledge of AI models. Instead, we recommend using tools that offer hyper-personalization features.
Consider using Twilio’s suite of products to get a better handle on your customer data and use that data to engage your customers with Twilio’s SMS and email solutions.
Twilio Segment is a customer data platform that helps you activate customer data, enrich customer profiles, and leverage real-time insights for your business. For example, you can learn how to set up a hyper-personalized contact center using Twilio Segment and Flex.
Twilio SendGrid supports transactional and marketing email. Its AI-based email marketing tools, such as email validation, neural protection, and deliverability insights, improve the email experience for senders and recipients.
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