7 hyper-personalization examples that changed the game

What is Hyper-Personalization?

Hyper-personalization is one-to-one personalization taken to the next level using AI, customer data, and behavior patterns. Why? To deliver content, products, services, and/or offers that feel specifically designed for each individual. 

But why bother with it exactly? 

Because the benefits are hard to ignore:

• Increased customer engagement - People respond to content that feels like it's meant for them. So, when you deliver hyper-personalized messages that perfectly align with their individual preferences, engagement naturally goes up.
• Higher conversion rates - Hitting customers with the right offer right when needed helps remove friction and paves the way for more sales.
• Improved customer loyalty - Hyper-personalized experiences create deeper emotional connections. These build loyalty and increase your customers’ lifetime value.
• Better customer experience - Delivering customers what they need before they even know it makes for a better overall experience.
• Optimized marketing spend - With hyper-personalized marketing, you typically target high-intent individuals only. Therefore, you are less likely to waste your marketing budget.

As you can see, the benefits speak for themselves. So, why not use them to your advantage?

7 Killer Hyper-Personalization Examples That Show How It’s Done

We've analyzed countless digital marketing strategies, watched trends change, and observed how brands use data and AI to truly connect with their customers. And now, we're about to introduce you to brands that we personally believe have made waves in the hyper-personalization department.

So, if the inspiration is lacking, check out these 7 hyper-personalization examples from top brands that will give you the blueprint to start using it!

1. Starbucks Transforms Coffee Habits with Real-Time Hyper-Personalized Offers

The Starbucks mobile app is a perfect example of what happens when you fully commit to hyper-personalization.

What they did:

Starbucks didn’t just build an ordinary ordering app for smartphones. They created a personal barista in your pocket, using your purchase history, drink preferences, and even the times you usually grab your coffee to offer tailor-made suggestions.

But they didn’t stop there! They took it further by gamifying the experience. With their "Star Challenges," the brand turned your daily coffee run into a game where you can earn stars and exchange them for free drinks or exclusive items. In the end, they made your coffee habit more rewarding—literally! 

Why it worked:

• Real-time targeting: The app knows when you're close to a Starbucks and uses real-time data to send personal offers, making it feel like this brand's satisfying your cravings at the perfect moment.
• Customized perks: Instead of generic discounts, you get offers that match your affinity for favorite drinks and snacks, making the app more personal and worth your while.
• Engaging experience: The gamified rewards make your coffee run feel like a game, compelling you to buy more to earn more points and prizes. 

Results:

• Personalized offers have driven repeat visits, making the app indispensable for consumer retention.
• The app now drives 31% of U.S. sales, proving that when you increase the level of personalization, the result is a boost in purchases.
• Tailored promotions have led shoppers to buy more per visit, increasing overall sales.

2. EasyJet Takes Past Customers Down Memory Lane to Boost Engagement

 EasyJet didn't want to mark their 20th anniversary by making it all about the airline. 

 They wanted to connect with customers in a hyper-personalized way.

What they did:

This brand dug into 20 years of customer data for an email marketing campaign that featured emails that told each individual their own ''travel story'' with the airline. They turned cold data into heartfelt stories by using imagery and clever copy to highlight past trips, travel milestones, and destinations visited.

The campaign aimed to celebrate EasyJet's history. But here's the truth: it was just as much about celebrating their customer journeys.

Why it worked: 

• Personal storytelling: By turning data into individual stories, EasyJet made emotional connections that made customers feel seen and special.
• Nostalgia factor: Highlighting past trips in messages brought back great memories, inspiring customers to book future flights.
• Emotional touch: Rather than a typical marketing pitch, they tapped into real emotions, making the experience feel authentic and personal.

Results:

• EasyJet saw over double the usual open rates and a 25% boost in click-throughs compared to their regular newsletters.
• The campaign generated 1.1 million impressions. It also sparked immense social media buzz, with 78% of the feedback being positive.
• 7.5% of customers who received personalized emails in their inbox booked a flight within 30 days. Meanwhile, conversion rates jumped by 30% in some markets.

3. Spotify Turns Data into Personal Stories with Wrapped Campaign

Spotify has mastered hyper-personalization. But nothing showcases this better than their annual Wrapped campaign that features year in review videos. 

What they did:

Launched in 2015, Wrapped gives users a personal, yearly recap of their listening habits. It breaks down the user's top songs, artists, genres, and total listening time. As a result, each user is provided their own musical story, packaged in a fun, shareable format that makes them feel like the main character.

Why it worked: 

• Personal storytelling: The platform uses data to make the user the star of their own musical show.
• Social sharing: Wrapped is designed for simple social sharing, resulting in it quite literally becoming a global phenomenon.
• Friendly competition: Users love comparing Wrapped stats with friends, adding a playful element that fuels conversation and engagement.

Results:

• Though newer stats are not available, in 2020, Wrapped drove a 21% spike in app downloads during the first week of December.
• Wrapped consistently trends on social media channels each year, as millions of users take to it to share their results.
• By giving users their own year-end recap, Spotify strengthens emotional bonds and improves retention year after year.

But why wait until the end of the year for a recap of your listening habits?

Plainly is your ultimate video automation software that enables you create unique videos just like Spotify Wrapped—anyime you want!

Don't trust us? Check out this video to see it in action!

Want to witness the full power of Plainly? Book a demo, and we’ll show you how easy it is to scale your video creation!

4. Cadbury Combines Tradition and Innovation in Hyper-Personalized Marketing

Cadbury cracked the code on hyper-personalization with their Cadbury Glow campaign, which tapped into India’s gifting culture.

What they did: 

To introduce Cadbury Glow as the perfect gift, they launched a campaign where users could create custom videos for their recipients. The videos pulled details from users' Facebook profiles—like names and photos—and linked them to the Cadbury Glow chocolate box. When the recipient got their gift, they could scan a QR code or click a link to watch their personalized dynamic video, making the whole experience feel extra thoughtful. 

Why it worked:

• Emotional connection: Pairing a heartfelt gift with a personalized video created a stronger emotional bond between the sender, the recipient/consumer, and the brand.
• Harnessing gift culture: Cadbury hit the sweet spot by taking advantage of India’s gifting culture, positioning Glow chocolates as the ideal gift to buy.
• Shareability: The campaign encouraged recipients to share their videos on social media to further spread the message.
  
  

 Results:

• 90% of people watched their video all the way through.
• Videos achieved a whopping 65% CTR.
• 33% of viewers followed through on the next promotion, showing that personalization drives repeat purchases.
• Over 12% of recipients shared their videos on social media, which extended the campaign’s reach.

5. Netflix Uses Machine Learning and AI to Personalize the Viewing Experience

Netflix's recommendation algorithm is one of the best hyper-personalization examples.  

It's also the reason why no two users have the same experience. 

What they did: 

Netflix’s recommendation engine uses technology like machine learning and AI to get a real sense of what you like to watch. It tracks everything from the shows and movies you’re into, how long you watch, and even the time of day you usually tune in. By combining what similar users are watching and what makes your favorite content unique, Netflix delivers recommendations that are adapted to your tastes.

Why it worked:

• Precision at scale: Netflix gathers tons of behavioral data, allowing its algorithm to curate recommendations that feel like they’re made just for you.
• Real-time personalization: The system keeps learning from your viewing habits and uses predictive analytics to keep things fresh and relevant every time you log in.
• Effortless discovery: Netflix makes finding new content easy, introducing you to shows or movies you might have missed when browsing.

Results:

• 80% of watched content comes from these recommendations, proving the system drives most of the engagement.
• The hyper-personalized experience reduces churn and boosts customer retention, saving Netflix over $1 billion each year.

6. Sephora Uses the Power of Hyper-Personalization to Drive Customer Loyalty

Sephora has changed how people shop for beauty through their data-driven beauty profiles, a.k.a Beauty Insider.

What they did:

Sephora’s Beauty Insider, launched in 2007, is an ecommerce loyalty program that collects info like your skin type, beauty concerns, and favorite products to provide personalized recommendations through their app, website, and in-store. It also offers fun beauty quizzes to get more insights and fine-tune suggestions, along with rewards.

Why it worked:

• Deep personalization: By knowing things like your skin type and favorite products, Sephora can recommend items that are spot-on for your needs.
• Seamless experience: These recommendations follow you everywhere, creating a consistent experience.
• Proactive recommendations: Sephora doesn’t wait for you to ask. Instead, they tailor products based on user profiles, making shopping easier and more intuitive. 

Results:

• Beauty Insider members spend 2-3x more per year than non-members, showing how personalization compels people to come back.
• Loyalty program members contribute 80% of Sephora’s total sales.

7. Run Malibu Makes Race Day Unforgettable with Hyper-Personalized Runner Videos

When it comes to creating a lasting connection with participants, Run Malibu knew exactly what they were doing. 

With the help of Augment Agency and Plainly, they made sure every runner had a tailored experience that they could hold onto (and share!) long after crossing the finish line. 

What they did:

Augment Agency teamed up with Plainly to create over 5,000 personalized videos for runners at the 2023 Run Malibu race. As a result of the collaborative approach between these three brands, each runner got their own custom recap video, showing off stats like their start time, average pace, and final position. To top it off, the video ended with an invite to next year’s race, making it not just a cool memento but also a fun way to stay connected.

Why it worked:

• Tailored experiences to each runner: Every video was personalized with the runner’s unique race stats, which made it feel more meaningful.
• Social media friendly: The videos were perfect for sharing. Consequently, they helped spread the word about the race on social platforms.
• Emotional touch: Highlighting each runner’s journey built a deeper connection, making them feel appreciated and inspired to join again.

Results:

• The videos were a huge hit—runners shared them all over social media, thus creating a lot of buzz for the race. 
• The videos also helped promote the next event, encouraging more sign-ups for future races.

Finishing words

Gone are the days when a simple ''Dear {First_Name}’’ was all it took. Now, brands and marketers are using real-time data and AI to craft experiences that truly resonate.

Just look at the hyper-personalization examples from brands like Starbucks, Spotify, and Netflix—they’ve proven how personal touches can transform routine moments into something memorable.

The best part? You don’t have to be a big brand to make it happen. With Plainly, you can tap into data-driven personalization to create engaging, custom video content that your audience loves—and do it at scale!

Ready to level up your customer experience? Give Plainly a try with our 14-day free trial and see just how simple it is to create hyper-personalized videos that drive results!

Frequently Asked Questions (FAQs)

1. What Is the Difference Between Personalization and Hyper-Personalization?

Generally speaking, traditional personalization involves using basic data (e.g., first name, last name) for customer interaction. Hyper-personalization, on the other hand, goes deeper. It uses real-time data, AI, and behavioral insights to create experiences at a highly individualized level.

2. How Can Smaller Businesses With Fewer Resources Use Hyper-Personalization?

Smaller brands can tap into hyper-personalization by using accessible tools like Plainly, which allows you to create custom, engaging, data-driven videos at scale without needing massive budgets or teams.

3. What Kind of Content Works Best With Hyper-Personalization?

Any type of content can be hyper-personalized. This might include videos, email campaigns, landing pages, targeted ads, etc.

4. What Kind of Tools or Platforms Can Help Implement Hyper-Personalization?

Many content automation tools can be used to create hyper-personalized content, including our Plainly. The choice of tool depends on the content type being created. Nonetheless, companies frequently use information from their CRM and analytics tools to extract the data points they need.

5. Are There Any Risks Associated With Hyper-Personalization?

The 2 biggest risks include: over-personalization (where customers feel like their privacy is invaded) and data security issues. However, these risks don’t mean one should abandon hyper-personalization altogether. It simply means it's important to exercise a level of caution when adopting it.