38 Content Personalization Examples Guaranteed to Increase Conversion Rates
With more and more businesses and services operating online, competition is hotting up when it comes to keeping your visitors engaged in your content. Whether you manage an online store, blog, or a movie streaming site, converting visitors to repeat customers is becoming increasingly difficult. Trying to appeal to the masses can often result in bland, unexciting content that is more likely to send your users to your competitors than keep them coming back for more.
Content personalization could be the solution you’re looking for to ensure you stay ahead of the competition. Rather than showing every visitor the same content, you can tailor it to the individual, providing a far more relevant experience for each and every user. This powerful marketing technique is used by many of the most successful online businesses, and can really help you increase conversion rates.
Read on to discover how the following 12 content personalization examples attract brand-new customers, and keep the attention of their existing users time after time:
With so many great TV shows and movies available nowadays, it’s hard to know what’s worth your time. Using content personalization, Netflix makes the choice easy by implementing advanced machine learning and powerful search algorithms to provide a tailor made list of the content you’ll enjoy. Netflix uses several tools to point users in the right direction.
Because You Watched
Netflix collects data from each subscriber, such as previous watch history, user behavior, and data pathways. This data is fed into powerful algorithmic tools to accurately suggest new movies or shows for users to enjoy.
Each user has an alert button, which shows them new recommended content, new releases, trailers for their favorite shows and movies, and reminders to pick up where they left off on a series or movie. This content is built up using information such as subscriber preferences and data pathways.
Top Picks For You
Similar to the ‘Because you watched’ feature, this tool uses search and data history, combined with data pathways, to suggest content that relates to a user’s favorite choices and lists.
This final feature allows users to personally pick the content that they are interested in. By adding to a list of movies or shows that they currently watch, or want to watch, subscribers allow Netflix to gain a wide array of information to feed into their algorithms and power the other features.
There’s a good reason why Amazon is one of the top e-commerce sites in the world, and as a content personalization example, they’re well worth paying attention to. From the home page to the search bar, almost the entire platform is tailored to the individual. Relevant product recommendations are visible throughout the site, helping the user discover the things they didn’t know they needed, and helping Amazon sell ever more goods.
Personalized First Page
When users log onto Amazon, the chances that 2 customers will see the same homepage are extremely slim. The site monitors user behavior and activity streams, as well as more generic demographic information, to put the focus on products that each individual is more likely to be interested in. Additionally, the most relevant deals and promotions will be highlighted, as well as the more common categories that each user searches.
Product Recommendation Analogy
User habits are monitored and paired with details from individual customers' profiles, as well as their history. After feeding this data into advanced AI utilizing powerful machine learning, the e-commerce giant is able to suggest the ideal products not just for the individual user, but also those that they may buy gifts for.
When Amazon customers search the website for the goods they’re looking for, they’ll be shown a list of content that has been personalized to them, based on their previous searches and interactions. As such, rather than just showcasing products that are specific to the search term, Amazon is able to optimize the user experience and rank the most relevant products to the individual higher.
While new to the market, Disney+ strives to compete with Netflix, offering a smaller selection of more niche movies and shows, mostly from the Disney portfolio. Like Netflix, they also use tools such as watch lists and recommended for you, though they have a way to go if they want to catch up with market leaders. Most of the personalization is arrived at through direct user interaction, and as such, it takes some time for the results to begin to show.
Subscribers are encouraged to create their own lists by saving their favorite movies or shows, or creating a list of content they’d like to view in the future. This user-data can then be used to generate further personalized content.
Recommended For You
Using data from watch lists, as well as data pathways, Disney+ can recommend new shows and movies to its users. The algorithms responsible for choosing the recommendations also take into account the wider user behavior across the platform.
As one of the most well-known music sites in the world, Spotify has used content personalization to gain an advantage over its competitors. They are able to suggest the music that is most relevant to their subscribers based on previous searches, and the songs, albums, and artists that they’ve listened to recently. Additionally, user data from all of their subscribers is fed into powerful algorithms to find suggestions for new music to listen to, based on current preferences.
Music For You
Subscribers are offered personalized content as soon as they open the homepage. Data is collected based on the music a user has previously listened to, in order to recommend the music they will most enjoy hearing. This streamlines the user experience and makes it quick and easy to start hearing the tunes they love.
Your Discover Weekly
Spotify doesn’t just recommend the songs that they know their users like to listen to. They also use search history data, as well as playlists, to suggest new songs and artists for users to discover.
This simple feature lets each user easily find the music that they’ve listened to recently, further optimizing the user experience.
Based On Your Recent Listening
By trawling through songs and playlists that a user has listened to previously, combined with data from the wider user-base, Spotify suggests similar content to try out.
Made For You
Rather than just suggesting pre-made playlists or specific artists, Spotify uses data from a user’s search history, library, and personal playlists, to create a brand new playlist. This will typically feature a mix of favorites, as well as music and artists that the user may never have heard before.
Personalized emails use location data, paired with user preferences, to notify customers of relevant upcoming concerts and events in their area.
YouTube is home to a huge array of videos, including documentaries, music, movies, e-learning, and vloggers. Their use of content personalization has ensured that users are able to find the content that is relevant to them quickly and effortlessly. Data derived from search history, watch lists, and subscriptions allows YouTube to make recommendations that keep regular users hooked. Meanwhile, location data and wider user data is used to provide basic personalization for new users.
Recommended and Subscriptions
Taking into account videos that a user has previously watched, as well as their search history, data pathways, and playlists, YouTube creates a tailor-made front page for each user. Feeding this data through algorithms allows YouTube to know whether a particular user prefers music videos, documentaries, or playlists, and provide the most relevant content. Data derived from subscriptions allows further personalization and provides recommendations based on that.
Mixing location data with channel subscriptions and preferred playlists, users are notified whenever new relevant content is released. It’s great for hearing about new albums, trailers, and announcements from their favorite channels.
Latest YouTube Posts
Users need never miss an update from not only the channels they’re subscribed to, but also related content. New videos, playlists, or even comments are announced, allowing users to keep up to date and discover new content.
All YouTube users can create their own library board, in which saved videos and playlists can be added. Watch later choices and liked videos are also stored within the library, and this data is used to suggest personalized content throughout the rest of the site.
As a content personalization example, LinkedIn is proof that it can work wonders across a broad spectrum of online services. Connecting employees, employers, and companies, it’s the leading business of its kind, and functional personalized content arguably contributes to this status.
Personalized Feed Page
LinkedIn provides a host of recommendations based on profile data, location information, and search entries. The resulting feed page is fully personalized, ensuring their users are shown only content that is relevant to them. This includes new articles, topics, companies, and connections.
Add To Your Feed
Subscribers are constantly able to add to their feed, and are provided with relevant content to choose from in a side window. Data pathways, interests, and connection data, are collected to arrive at the most useful suggestions for every single user.
Customizing Your Public Profile URL
A final nice touch is the option for users to customize their own URL, ensuring they rank higher on search engines.
This UK based online fashion retailer has gained global success over the years, and it’s not just for their wide range of affordable clothing. The entire process of finding the right clothes for you is extremely intuitive, and it’s a great example of how personalized content can hook a user from the get-go.
New users are offered different landing pages depending on location and gender. Based on this input, they’re shown only the most relevant content. Meanwhile, registered users are offered apparel suggestions based on their purchase history and favorites lists.
Asos enables users to save products to their personal favorites list, in order to either buy or view later. In doing so, they enable Asos to gather a wide array of data pertaining to the type of products they’re most interested in. Asos then uses this data to make personalized recommendations.
Shop The Look
This feature uses information such as data pathways, user preferences, and cookies to make apparel suggestions. When a user selects a product they’re interested in, the following landing page will have a section displaying the look of the entire model, suggesting products that might work well with what the user has selected.
Find Your Fit Assistant Size
Saving even more time, the fit assistant allows users to define their details such as age, height, weight, and even tummy shape. Based on this data, they’re shown the most relevant content.
Starbucks has grown far bigger than a simple coffee shop, and their app is a great example of content personalization. Indeed, the personal recommendations aspect of the app is extremely powerful and gives the user the feeling that Starbucks is truly aware of their preferences, encouraging brand loyalty.
Upon starting the app, a personalized homepage greets each user, offering information about their personal rewards, as well as carefully tailored recommendations
The Starbucks app collects and capitalizes on huge amounts of data, including time and date information, user preferences (how often they visit a store, at what time of day, etc.), location data, previous purchase history, and personal details. Using this data, suggestions and special discounts then adjust according to the time of day. The idea is to encourage a customer to drop by their local store, for example, for their 11am break to grab their favorite combo, or perhaps something new.
Starbucks Rewards — Redeem Account
The Starbucks Rewards scheme uses customer preferences, personal details, and data pathways to offer unique, one-off offers and exclusive content. Huge amounts of customer data is gathered via the rewards scheme, such as spending habits and unique preferences.
Renowned as one of the world’s largest travel sites, TripAdvisor has changed tact in recent years, and aims now to be the world’s most personalized travel community.
Recommended For You
While browsing through content, data is compiled regarding customer preferences and inputs such as saved favorites, direct bookings, and destinations to revisit. Together with data gathered from the wider community, recommendations are made for destinations users will love, but might never find otherwise.
The TripAdvisor homepage has a personalized feed section, which is constantly updated with recommendations and posts from friends, brands, and influencers. The content of the feed is personalized by analyzing data such as search history, previous trips, posts, and even comments. Users can pick and choose what they see in their feed, providing TripAdvisor with even more data as to their personal preferences.
EasyJet is a cheap and immensely popular European airline. While their low fares have done a great job of attracting custom in the past, an influx of new budget airlines has led to them adopting new tactics. This content personalization example harnesses the power of nostalgia to massively increase conversion rates.
Focusing primarily on creating mega-personalized emails, EasyJet gathers data from past purchases and trips, as well as personal details. This data is used to send out emails featuring travel stories from destinations that users have previously visited.
At the end of each story, the company recommended another relevant destination, based on data from the user’s search history and other data pathways.
This next personalization use case shows the power of using personalized content as a marketing tool to gain wider reach. It’s also a masterclass in how using online tools to create personalized, offline products can be a great way to set your business apart from the crowd.
Cadbury launched an innovative video campaign using Idomoo’s personalized video as a service (PVaaS) technology. The system gathers data from Facebook, including age, gender, location, and interests, to match users with one of 12 new flavors. The resulting video incorporated the user’s profile image from Facebook, and encouraged them to share the video with a simple hashtag. A fantastic way to reach a wider audience using personalized content.
Product Personalization From The Website
Working in a slightly different way to the other examples, Cadbury gives their customers the opportunity to personalize the packaging of their favorite chocolates. Customers can add their own images and messages to create personalized gifts for friends and family.
Perhaps it’s the footwear, but Nike seems to go the extra mile when it comes to content personalization. With not 1, but 6 different, though interconnected apps, Nike is able to offer an exceptional customer experience. Nike+ is the main app, and features personalized recommendations based on the users search history, previous purchases, and personal preferences, as well as location data.
Two other Nike apps monitor fitness goals, while a fourth is dedicated to lovers of the famous sneakers and offers personalized information regarding local events and new releases. The fifth app scans jersey tags and uncovers exclusive offers and content, while the final app is capable of controlling connected footwear
Nike strives to personalize both online and offline customer experiences through its apps, allowing a complete customer journey. This makes it easier for the customer, raising satisfaction considerably. In-store experiences can be started online via the apps, and completed offline by scanning codes or picking up orders. All the time, the apps are collecting huge amounts of data to be used elsewhere.
Data from all 6 apps, including fitness activity and movement data, is collected and used to make personalized recommendations for events, products, sports classes, and other related content.
Using push notifications and in-app messaging, Nike is able to alert its users to the latest news, products, and events, all tailored to their unique preferences.
Improving Conversion Rates For Your Business With Personalization
With users saying yay or nay within seconds of landing on a site, online business owners cannot afford to look generic. If you can provide personalized content that is relevant to each individual user, you’re far more likely to capture their attention and keep them interested in your product. The above content personalization examples are leaders in their respective fields, and it’s safe to say that personalization plays a key part in their success.
Prepr is an advanced content management platform that enables digital teams to manage, optimize, and personalize content in one seamless solution. Check out how Prepr can help your organization personalize content and increase conversion rates.