Hyper-personalize… or die slowly!!

5 Examples of Hyper-Personalization That Worked and Why

Personalisation makes your customer experience so much better. In this new age of evolved consumers who buy almost everything online, creating a great and unique customer experience has become more like “personalise or die slowly”!

Some organisations do the basic — personalise their sign-up forms or address their clients by their first name in emails. Others create personalised workout programs or, as Coca-Cola did with their “Share A Coke” campaign, print popular names on Coke bottles.

Buyers prefer experiences that reflect their personalities, beliefs and aspirations. According to Deloitte, 80% of customers would rather buy from brands that provide personalised experiences, and 90% of customers said personalised experiences appealed to them a lot more.

What can I say? It’s the age of personalisation! We live in an era where customers expect brands to understand or even anticipate their needs.

So you’re probably thinking, “Alright, get to the point. Who’s doing this personalization thing, right?”

Ok, ok, let’s get to it.

VI Hyper-Personalized Fitness

Vi is a digital fitness app that motivates users to run more. It acts as a virtual trainer and real-time audio running coach with personalised training plans for each customer. Vi uses a combination of Artificial Intelligence (AI) and real-time data to monitor users’ heart rate, speed and progress. Users can also join running communities and compete with other members in virtual races.

Vi has a really large community of runners who have run over 1 million miles. Their hyper-personalisation has yielded excellent results, increasing their conversion rates and driving customer loyalty and brand trust.

Amazon

Amazon has been incredibly successful in integrating recommendations during the shopping process.

Their recommendation algorithm, item-to-item collaborative filtering, uses 4 data points to create hyper-personalised user experiences — Purchase history, Items in shopping cart, Items liked and rated by the user, Items liked and rated by other users. These suggestions also provide visibility to typically unpopular products and drive revenue growth. So far, their personalised suggestions are responsible for 35% of sales, and they have 60% higher recommendations than other e-commerce sites.

Netflix

Netflix has over 103 million users and is one of the biggest markets for digital content consumption.

Their personalisation starts right from the homepage. The user selects the content they like, and this information is used to create specific categories filled with similar content. Beyond this, their recommendation algorithms match content to people most likely to be interested in them by using the content’s stream count, predictive learning, rating and general behavioural attributes and sending suggestions to users.

Spotify

With over 150 million active users and 5 billion streams, they’re undoubtedly the most successful music streaming application.

They’re also effective hyper-personalisation strategists — their algorithms study each user’s song choices and cross-analyse their playlist with the playlist of users who have listened to the same songs, then creates a hybrid playlist for each user. Spotify’s AI engine analyses the amount of time a song has been played, added to users’ playlists and each user’s unique listening habits.

Starbucks

Starbucks created a mobile app with an interface customised for each user and an algorithm to send over 400,000 different hyper-personalised messages to different users!

The app sends push notifications recommending customised orders for each user based on their purchase history, activity, preferences and taste. The Starbucks app also has personalised games for the 13 million members of its loyalty program. It gives its users extremely detailed information such as the stores closest to them and the payment options available in each store. It’s been so successful that even though it’s not an online payment platform, it was the most used platform for mobile payments until Apple Pay edged them out of the top spot in 2019.

Hyper-personalization is great and adds excellent brand value, but it could also hurt some brands because there’s a thin but very real line between keeping users engaged and annoying them.

Some users are pretty private, and hyper-personalisation can be perceived as spying. This could lead to negative reviews and high customer churn. It’s not a one-size-fits-all strategy; what worked for Vi Fitness might not work for Amazon. So it requires a company-specific strategy, roadmap and flawless execution.

Which of your favourite brands do you think are doing hyper-personalization right? Let me know in the comment section!