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Content Marketing

What is Hyper-Personalization in Marketing?

Today’s consumers demand more from the companies they do business with. They don’t want blanket offers or experiences – they want things personalized to them. In fact, 79% of consumers say they’re only likely to use a brand promotion if the promotion is tailored to them based on previous interactions with the brand. And by 2020, 51% of consumers expect companies will anticipate their needs and make relevant suggestions before making contact. The good news is, 57% of consumers are okay with giving a website personal information as long as it’s used responsibly and for their benefit.

Many brands do a decent job at delivering a personalized experience, but as marketing continues to evolve, hyper-personalization is where we’re heading. To ensure you’re able to keep up with the changes and get one step ahead of the competition, it’s time to work on your hyper-personalization strategy.

Personalization vs. Hyper-Personalization

Personalization adjusts brand communications based on the available information about the consumer, such as name, location, and purchase history. Hyper-personalization, considers that information along with real-time data and browsing behavior to adjust messages in the moment. It leverages artificial intelligence (AI) with the real-time data to deliver more relevant product and service information and content to each user.

Brands Getting Hyper-Personalization Right

Amazon

Amazon has long been personalizing the experience for its shoppers, but thanks to its various membership options and massive inventory, it has created a hyper-personal experience for its millions of users.

When a customer searches for a pair of headphones, a “Frequently bought together” section appears on the page to suggest other items to purchase.

Beyond this, the homepage is personalized for each customer based on their previous shopping habits, their shopping cart, and wish lists. Through anticipating their customers’ needs, Amazon makes it easier to find what they’re looking for, while also making it easy to find new products.

Amazon accomplishes this through the use of predictive analytics to gather data. Using both historical and real-time data allows them to get a deeper understanding of their customers, which allows them to improve customer satisfaction with these hyper-personalized marketing techniques.

Netflix

Netflix has been serving up suggestions based on the content you’ve watched in the past, but today, they take it even further. They personalize film covers to give prominence to the actors and actresses you’re familiar with.

Netflix uses massive amounts of data, getting granular and specific with their genre suggestion, to accomplish this for all its users. In a way, your watchlist is customized by them as much as it is customized by you. The streaming services knows when you stop watching a title halfway through, when you hit pause or play, and when you click the button to add something to your watchlist. By harvesting the information from user profiles and feeding it into its personalization engines, no two Netflix users has the same combination of rows on their homepage.

Age and gender are not factored into the recommendation system, because user behavior is a far more important metric. And Netflix doesn’t use the data just to change your suggested titles. The personalization can even adjust how the player looks in terms of design – and you’ll get different recommendations depending on when you login.

Starbucks

Starbucks has allowed customers to personalize their products – using non-dairy options, sugar-free syrups, and so on. But to take that even further, Starbucks now uses a real-time personalization engine to create individualized offers for their customers based on preferences and previous behavior. The data comes from their loyalty app, so they can understand the habits and needs of each customer. Using the information, Starbucks sends personalized emails with deals and updates that are relevant to them. People share their data with the app because it enriches their customer experience. Creating a loyalty program for your brand not only rewards your customers, but helps you to understand how they interact with your products or services so you can make use of the data for hyper-personalization.

Planning a Hyper-Personalization Strategy

When you’re ready to take your personalized marketing to a new level, you’ll need to ensure you have a plan.

Mine Data

Take a look at the data you have available and the kind of data you’re collecting. Consider what you’re doing with the data, because the more you’re doing to ensure its accuracy, the better your results will be. This means continually removing outdated, duplicate, and incomplete information. According to Eloqua, companies with consistent data hygiene processes generate 7x more inquiries and 4x the leads than those who don’t.

Craft a Personal Message

With hyper-personalization, you’re turning your company data into relevant messaging and offers that best address your customers’ needs. This approach is highly effective in email marketing, and can be transferred to other areas of your marketing, too.

Develop a Personalized Offer

Much like Starbucks has done with their hyper-personalization, you should aim to personalize your offer based on your customers’ past behavior. How effective the offer is will depend on the quality of the data you have. Beyond personalizing the offer itself, you should aim to make things as convenient and user-friendly as possible.

Use All Your Channels

When you combine all the consumer data you have available with multichannel marketing efforts, you’ll be able to create one-to-one relationships with each one of your prospects and customers. Websites, email, and smartphones all offer advanced customization and personalization options, and those options are also available for print marketing and direct mail initiatives.

Timing Matters

Contextual data, or the who, what, when, and where of customer behavior, helps you better understand how and why your audience interacts with messaging. Applying predictive analytics also helps determine the best times to deliver specific messages to drive the desired results.

Test, Test, Test

To build the most effective hyper-personalization strategy, you must continually test. It’s critical to identify the most compelling elements of your messaging, and you can only do this with multivariate and usability testing. These go beyond basic split testing to help you gauge the combined effect of multiple elements at once, so you can figure out which combinations perform the best.

Research from Ascend2 reveals only 9% of surveyed marketing professionals have completely developed their hyper-personalization strategy. Getting started now puts you ahead of the competition as an early adopter. Make your top priorities improving customer experience and applying your data insights to decision-making, and you’ll get the most benefit from your efforts. By improving your customer’s personalized experience, you’ll build goodwill and loyalty for your brand.

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