Hyper-Personalized Marketing: How to Do It Right?

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Few people would dare dispute that personalization holds the key to improving customer relationships.

This strategy revolves around the process of tailoring marketing campaigns and messages to preferences of individuals, instead of large groups and audience segments. Basic customer data is the main building block of this approach, one that informs decision-making.

Hyper-personalization represents a newer development, hailed as the next stage in the marketing evolution. It builds on the foundations of personalization and helps marketers reach new heights when it comes to effectiveness.

The solid evidence in favour of hyper-personalization is all around us. 

It’s estimated 80% of customers are more likely to make a purchase if a company provides personalized and meaningful experiences. This figure is poised to rise in the years to come. 

Thus, it’s to wonder many brands are transitioning away from traditional personalization. They realize highly curated experienced and offers are the way to go. 

Digging Deeper than Ever Before 

Nowadays, people are pampered with brands offering highly-personalized service and experience. 

Most businesses extract customer data and carry out rudimentary segmentation. They follow a narrow vision, primarily storing customer’s content info, location, and purchase history. The goal is to bundle customers together and target them with somewhat customized campaigns. 

This practice proved to be quite fruitful, but the winds of change are blowing and the business ecosystem is adapting. 

Hyper-personalization has come around as a response to various disruptive developments. It’s no fad, but a concept that is rapidly becoming a norm across industry sectors. 

You could even say it’s a real game-changer in times of dwindling attention spans, information overload, and mounting competition. It helps you cut through the noise and get the messages across, letting you survive and thrive in a digital economy.          

Personalization in an Overdrive Mode 

The key thing to realize is that hyper-personalization differs from personalization in some important ways. 

First off, it takes marketing a step further by implementing advanced technologies, such as IoT, machine learning (ML), and artificial intelligence (AI).  These innovations have armed businesses with tools necessary to leverage big data and accelerate digital transformation. 

Secondly, hyper-personalized marketing ventures above and beyond basic consumer data. It taps into behavioural and real-time data, collecting it across a wide array of sources, touchpoints, and channels. 

The goal is to accomplish higher marketing penetration, engagement, and relevance. 

Ultimately, such a data-reliant strategy is supposed to breed greater success and return on investment (ROI). Of course, the trick is not to just do it for the sake of being trendy, but to do it right. 

Personalized Recommendations 

To gain a deeper understanding of hyper-personalization, let’s examine a couple of concrete examples. 

In recent years, the ability to recommend products based on previous purchase decisions has served many businesses well. A hyper-personalized strategy may employ the same tools, targeted ads, and recommendation systems, but it also optimizes them beyond the scope of what was previously possible. 

Today, one can take advantage of insights relating to the exact location and purchase time, as well as online behaviour, payment history, and other details. In other words, hyper-personalized ads are more likely to hit the mark on the account of extensive data findings built into them. 

You may argue the difference is a matter of quantity. Well, it’s true that personalization is only as good as the data that supports it. But, hyper-personalization is also more than a sum of its parts, the data points. 

It profoundly impacts the quality and appeal of marketing. It tends to improve conversion rates and lead generation, two hallmarks of marketing success in a digital age. Besides, sheer quantity doesn’t account for much if it’s not the right type of data you are collecting.

The vast majority of the available data pool is downright worthless, meaning you have to be very selective. 

Getting Smart with Email Marketing

Another practical example is associated with marketing’s most reliable workhorse, the email. 

Namely, a typical personalized email campaign includes little in a way of customization. Usually, there’s a recipient’s name in a subject line and that is it. 

Back in the days, this simple trick was enough to create an impression you are speaking to someone directly. Modern customers, however, are well-educated, tech-savvy, and spoilt for choice.  They expect more from brands and who can blame them really? 

The good news is hyper-personalized marketing offers a way around the obstacle. 

It analyzes activity in real-time and sets up event-based triggers in order to contextualize and time the messages right.  Likewise, the content of the message changes according to factors such as time and location of opening an email.

So, for instance, a customer may receive an email the moment he/she abandons the shopping cart. 

The tailored-made message is much more than a desperation move. It can alleviate concerns regarding the safety of payment methods, denounces hidden costs, and promises timely delivery.  A little bit of hyper-personalization goes a long, long way. 

Covering all the Bases 

A hyper-personalized approach can be applied to all stages of the buyer journey. 

It makes sense to then first grasp the big picture and map that entire journey. Once that is sorted out, you can dive in deeper with customer journey analytics, also known as customer data platform (CDP). 

This process hinges on robust data, which originates from a matrix of individual customer interactions. 

This is a good time to note that hyper-personalization is rooted in multi-channel marketing methodology. Platforms like social media, websites, and mobile apps have their own personalization/customization features we have to put to use. 

Well, customer journey analytics facilitate this endeavour. They help you connect the scattered dots and make sense of a host of gathered data. Being able to understanding past and current journeys, you are also in a position to shape the future ones. 

To get there, however, you have to seamlessly integrate findings with your tech stack. We’ve already mentioned customer journey analytics as a means of gaining a wide view of consumers.

A viable alternative would be to find CRM software that fits your needs. It keeps track of all interactions and equips you with tools for improving them. You can use it to cover all your data needs in one place. 

Supporting Tech Pillars

Apart from CRM and CDP, there’s a heap of advanced marketing tools geared toward hyper-personalized, automated campaigns.

You shouldn’t even try to tackle hyper-personalized marketing manually. There are too many parts you would have to spend a tremendous time juggling. 

Instead, follow the example of industry leaders in the league of Amazon, Netflix, and Starbucks. They rely on predictive personalization to maintain their competitive edge. To be more precise, they are versed in using AI and ML to develop individual recommendation systems.  

Amazon champions a solution called “item-to-item collaborative filtering”. It comes up with amazing recommendations, which are a product of four different data sets:

  • Purchase history 
  • Items added to the shopping cart
  • Liked and rated products
  • Items purchased or liked by similar consumers

Amazon uses these four to craft comprehensive customer profiles and deliver a unique user experience (UX). It’s not hard to see why this particular combo produces such stellar results. 

The streaming top dog Spotify is another telling example. The platform’s algorithm analyses individual music choices and then compares them to the choices of people who have listened to the same songs. 

The result is a system that delivers personalized playlists and live event recommendations. And it does the trick more often than not.  

Baby Steps before Leaps and Bounds 

It’s perfectly fine to start small, with just one or two personalization criteria. 

They could correspond to differences in gender, occupation, age, spending tendency, or some other factor. Once you establish a baseline, you gradually add new factors to further segment and refine the audience. 

At one point, you should have enough criteria to flesh out a hyper-personalized campaign and nurture one-on-one relationships with customers. 

On top of the criteria we already disused, some vital data points to consider are:

  • Search queries 
  • Brand affinities 
  • Category browsing patterns
  • Average spending 
  • Daily online activity trends 
  • Major life events 
  • Responses to prior messages 

The list goes on and encapsulates some less common options. Depending on your business case, they might be worth exploring too. And when we say worth, we really mean it. 

Hyper-personalization hasn’t hit the mainstream yet. This is to say becoming an early adopter will pay dividends down the road. Don’t let the competition beat you to it! 

It’s time to get personal with marketing and amplify your communication. 

Onward and Upward 

Personalization had a good run but it has run its course. 

Hyper-personalization ushers in a new era in the evolution of modern marketing. Like it or not, merely slapping a name to the email subject line doesn’t cut it anymore. 

You have to keep up with shifting consumer demand and step up your personalization game. 

Start by embracing a data-fueled approach to marketing and stocking up on tech tools. Make sure the timing and context of messages are aligned with individual preferences and work to your advantage. 

Always act with a strong sense of purpose and get more eyeballs to your content, ads, and messages. 

Following these steps, you should be able to generate goodwill, trust, and loyalty around your business.  You will separate yourself from the crowd and capture a bigger market share. 

About the author

Daniel Bishop

I started off my career in digital marketing by working for a few local companies. After a year or two of learning different aspects of the job, I moved on and worked for DesignRush as a content advisor. Right now I'm working for ReallySimpleSystems as an assistant editor and a marketing consultant. Other than that I enjoy good coffee and Otis Redding.

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