ºÚÁÏ´«ËÍÃÅ

Continued IT advances such as artificial intelligence (AI) and machine learning are shaking up the way we shop and browse online. Technology now allows marketers to use data to identify a customer’s exact needs, habits, and behaviors to serve them more personalized content and individualized experiences. In the marketing world, this is known as hyper-personalization.

Hyper-personalization is the most advanced way brands can tailor their marketing strategy to individual customers. It leverages big data, analytics, AI, and automation to create custom and targeted experiences in real time.

When done effectively, hyper-personalized marketing can be a win-win for companies and consumers. It allows brands to more meaningfully engage customers, build new relationships, strengthen existing ones, and improve the customer experience.

In fact, recent research shows:

• 86% of companies report seeing a measurable uptick in business results from hyper-personalization.
• of consumers say they find personalized marketing appealing.
• 40% of consumers say they’ll likely buy from a brand again after a personalized shopping experience.

Hyper-Personalization vs. Personalization

With standard personalization, you might get a geo-targeted Instagram ad or an email with your first name in the subject line. It uses more basic data, such as your location and purchase history, to serve you relevant marketing content. This tactic worked well in its early days, but as the digital marketing space became more crowded, using personalization in this manner became less effective so companies needed to leverage fresh ways of engaging their customers.

Enter: hyper-personalization.

Because it uses more advanced technology, hyper-personalization provides a much deeper perspective of individual consumers. Marketers can tap into millions of data points from website cookies, mobile apps, social profiles, and other connected devices to gather real-time behavioral data. The result is highly individualized communication sent at the right place and time—and through the right channel. A prime example of this is Netflix’s Recommendation Engine, which uses real-time data and AI to come up with a personalized grid of movie and TV suggestions catered to your specific tastes.

Segmentation vs. Hyper-Personalization

Segmentation is one of the core elements of marketing campaigns. It groups customers into subsets (based on shared characteristics such as age, gender, location, average spend, etc.) in order to target shoppers and develop relevant offerings. Hyper-personalization does this too, but dives much deeper into the data so that the customer segment is reduced to a single individual. This segment-of-one approach allows organizations to tailor their marketing so they can deliver most relevant messaging via the most relevant channels.

New research suggests that consumers are expecting, if not demanding, hyper-personalized experiences. In fact, a study by Epsilon found that surveyed want personalization from retailers. However, hyper-personalization comes with a price—and that price is data. While many consumers say they want a more personalized experience, not all are willing to give up their information and privacy to do so.

A Pew Research Center report found that lack confidence that companies will use their personal information in ways they’re comfortable with. To help overcome this concern, it’s important that organizations and business professionals be transparent in how they use customer data—and that the privacy-for-personalization tradeoff is communicated clearly.

If you’re a business professional, or studying to become one, there are a few things you can do to strike a balance between personalization and consumer privacy concerns.

First, make sure your content is relevant. After all, hyper-personalization only works if it matches what a consumer finds valuable. Today’s consumers expect brands to know who they are and provide them with content they care about. That means delivering the right message at the right time.

Second, listen to customer feedback. Simply asking customers what they like or dislike can help you better understand consumer expectations and create a hyper-personalized marketing plan that fits their needs.

Lastly, build trust. The balance between personalization and customer experience ultimately rests on how well your business protects its data privacy and addresses security concerns. This starts with understanding the legal requirements surrounding data privacy and complying with them before implementing hyper-personalization. Brands who strike this balance are able to do a better job of building trust among their consumers.

As hyper-personalized marketing strategies continue to grow, businesses will need more computer scientists and IT experts to take the lead. If you’ve been thinking about getting your online IT or computer science degree, there’s no better time than now.