Hyper-personalization: According to Statistics and studies

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Back in the day, brands could easily get away with generic push marketing.

We weren’t being marketed to. We were being marketed at. No authenticity. No context. No accountability. 

But today? Those days are over. 🙌

The consumers of 2019 are skeptics with a zero-tolerance policy for BS marketing. They hate being sold to, but love personalization. It’s no surprise marketers experience an average increase of 20% in sales when using personalized experiences. 

However, marketing now experiencing a seismic shift beyond personalization. 

A study by the IBM institute revealed that Gen Zers value individualization (read: advertising that exactly matches their desires) over personalized experiences. 

Enter: Hyper-personalized content.

A strategy that leverages AI and real-time data to deliver irresistibly relevant marketing personalized at a granular level. 

Whether you’re looking to level up your personalization—or just curious about hyper-personalization—this article shares nuggets of wisdom that you can apply to your current situation. So let’s get started.

Personalization vs. Hyper-Personalization: What’s the difference?

Before we dive into the nitty-gritty intricacies of hyper-personalization, let’s first look at its distinction from personalization.

Personalization uses customer profiling techniques to make assumptions about users based on specific traits.

Hyper-personalization does the same, but takes this step further by using customer history and real-time data to truly understand the user’s needs and intent.

For example, if you’re advertising back-to-school supplies to individuals who purchased school bags in August, hyper-personalization would take this a step further and optimize ads for the following:

  • Location of the purchase (say to determine season).
  • Mode of purchase (to provide ‘special’ card points, etc.).
  • Demographics of the customer.
  • What keywords the customer mentioned in the past.

As you can see, Hyper-personalization dives into the granular details, and is of course, much more effective than personalization. 

Simply put, Hyper-personalization is an ‘inception level’ marketing strategy— 

(Basically, you’re in the head of your target audience 😼).

Advantages of Hyper-personalization: Why it’s so fly?

Back in the day, merely using a consumer’s name in an email would pass off as personalization. 

But now, hyper-personalization leverages smart technologies like AI, machine learning and big data that brings a whole new perspective to targeted marketing.

Here are three benefits that make it an absolute no brainer to implement hyper-personalization:

Benefit #1: Hyper-personalized campaigns yield better results

Hyper-personalization maximizes the number of customer touchpoints for data collection—and the more the touchpoints, which inturn, leads to higher conversions.

For this reason, it’s not uncommon for hyper-personalized marketing campaigns to produce extraordinary results. Studies show that hyper-personalized e-commerce experience results in higher revenue, less product returns that, in turn, improve brand reputation. 

Here’s an infographic that details out the benefits of hyper-personalization in e-commerce— 

Source: Clever Bridge

On another note, Hyper-personalization yields a higher ROI from website content, which makes sense, especially when 74% of customers feel frustrated when website content is not personalized.

What’s more, email marketing tools are much more effective if they have data beyond the recipients name and can deliver 6x the transaction rates.

(Now you know why good content marketers swear by customer personas to create hyper-personalized content.)

Benefit #2: Better customer experiences 

Data show that 79% of consumers will likely only engage with an offer if it’s directly tied to their previous interactions.  

This is where hyper-personalization comes into play and uses multiple data points (think: demographics, user history, etc.) to offer better customer experiences. 

Hyper-personalization is particularly great for e-commerce platforms that can use this data to create personalized experiences across a customers’ journey—from discovery to purchase and even repeat purchase.  

For example, Naked Wines uses hyper-personalization to customize dashboards for its users— 

Source: Bigcommerce

What’s more, the data can be further used for predictive analytics to perfectly time-specific messages and drive responses that, in turn, will increase conversions. 

Benefit #3: Highly engaging social campaigns:

All successful Social media marketing campaigns have one thing in common—reliable user data. 

This is where hyper-personalization systems come into play, and helps serve as a monitoring tool to find relevant user data (think: user tone, lingo, hashtags, etc.) that’s used to launch highly relatable social marketing campaigns.

On another note, hyper-personalization can also be used to improve social support as you are basically monitoring your users in real-time (kind of like stalking 😉).

Examples of Hyper-Personalization

Top brands like Amazon, Netflix, and Spotify are the early adopters of hyper-personalization and have already started implementation by using predictive personalization to power their recommendation engines. 

Source: Stages of Personalization

And here’s how they’re putting hyper-personalization to work:

#1: Amazon

Amazon is an e-commerce giant a lot of online retailers look up to so it makes sense to watch and learn from them, more so, because they follow the best hyper-personalization strategies

For instance, Amazon uses recommendation engines throughout its site— 

Picture: Snippet of my recommendations bar

But here’s the real kicker—these aren’t randomly generated recommendations. Instead, it’s based on specific key data points: 

  • What I last purchase 
  • What items were in my shopping cart (and not purchased)
  • Things liked and purchased by other similar customers

You see, Amazon uses item-to-item collaborative filtering in its algorithm to make highly educated guesses. 

What’s more, Amazon takes this a step further and sends out perfectly timed emails based on similar data points—

Source: Kwasi Studios

Point is, Amazon uses hyper-personalization to find out exactly what you’re looking for (and when). It’s no surprise their recommendation engines bring in a whopping 35% in revenue.

#2: Starbucks

Starbucks is the biggest coffee company in the world and has always used some form of personalization in its marketing.

But recently, Starbucks has stepped up its game by adopting a real-time personalization engine that produces individualized offers for its customers based on previous behaviour and preferences. 

The data helps them understand the needs and habits of their users at a granular level—and with this knowledge, Starbucks sends out irresistibly relevant messages— 

Source: Email monks

Fact is, Starbucks sends over 400,000 variants of hyper-personalized messages (think: food/beverage offers) to its users based on unique user preferences and browsing history.

It’s no surprise the Starbucks’ hyper-personalization campaign is a massive success:

  • 300% increase in marketing effectiveness
  • 200% increase in email redemptions
  • 300% increase in incremental spends
  • 24% of total transactions now come from their app

These staggering statistics are a clear testament that hyper-personalization works and is the future of marketing. 

#3: Spotify

Spotify is one of the most popular streaming music streaming services that implements hyper-personalization in their marketing campaigns.

For example, Spotify uses a “Discover Weekly” feature to predict exactly what music each of its users listen to— 

Source: Discover Weekly 

Discover weekly works by analyzing your played tracks and comparing it with people who have listened to similar music. The goal is to align your tastes with those with similar tastes in music. 

This works out great, as different people have different tastes in music—and a personalized playlist takes this diversity into account. Fact is, this feature alone has exponentially increased user engagement that in turn, resulted in 5 billion tracks streamed from the app.

On another note, Spotify uses hyper-personalization to sell concert tickets— 

Source: Spotify concerts 

Seize the opportunity, be an early adopter

Going forward, organizations that implement hyper-personalization strategies will be able to keep up with the increasing expectations of consumers while still maintaining that competitive edge.

But for now, only 9% of marketing professionals have adopted hyper-personalization strategies i.e., the early adopters.

Yes, hyper-personalization is not an easy strategy—and you’ll most likely run into problems. 

But remember, you can never be right, just less wrong. So experiment and fine-tune your strategy till you find something that works for you. 

Moreover, if you start now, you’ll be ahead of the majority who are either just talking about it or have no idea about it.

The only question is, are you going to resist or embrace this paradigm shift?


This is a guest post by Mark Quadros. He is a freelance content marketer who helps SaaS and online-business develop content that not only drives traffic but also boosts user-engagement. In his free time, he loves traveling the world and living a minimalist life from his backpack.

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