Personalization has been the buzzword. Customizing a user experience according to customers’ preferences and interests is good business sense: it builds trust and relationships while selling more relevant product recommendations to customers. Unfortunately, the personalization we know is just not good enough. To truly reap the rewards of personalization, one must communicate with the customers on an extremely granular and individualised level.

What is personalization?

Personalization is the tailoring of products, services, or experiences to suit the choices and wants of individuals. Data employed for personalization include user demographics, past behaviors, purchase histories, and the method of searching for things that are made more relevant for the current instance at hand. For example, showing recommendations for movies on a streaming platform based on the ones you have seen in the past, or showcasing products in an online-store browsing session based on the items you have searched for: that is all personalization. Its goal is to provide a feeling of being understood and accepted, thus enhancing the overall experience and engaging the users.

What is hyper-personalization?

Hyper-personalization takes everything one step further by utilizing advanced technologies like artificial intelligence (AI), machine learning, and real-time data analytics. Hyper-personalization tries to make the most individualized and immediate experiences by taking into account much deeper insights, such as location, the current time, device being used, weather conditions, and even real-time behavior. For example, an app that helps you book a flight for the moment you begin a search for vacation destinations, or an email campaign that adjusts the content of the message the minute you open it, according to a recent action you took. Hyper-personalization aims to emulate human-like interaction with users involving timely and contextually relevant encounters having a very positive impact on satisfaction and conversion rates.

What Is the Difference Between Personalization and Hyper-Personalization in Marketing?

Personalization refers to providing customized experiences according to the preferences and behavior of a customer. If an e-commerce business were to recommend products according to recent purchase history, it would be considered personalization. Targeted email campaigns can also go out to customer segments with the same interests.

Hyper personalization is defined as an extension of personalization to a much higher degree. Hyper personalization manages to take marketing beyond personalization campaigns through real-time behavioral data with complex algorithms for much more detail in crafting experiences for individual customers. Whereas personalization takes into account customer past behavior and preferences, hyper-personalization considers all present contexts, including location, time of day, and sometimes even weather, to provide tailor-made contents, recommendations, and offers to the customer.

The primary distinction between personalization and hyper-personalization lies in the degree of customisation introduced and the usage of real-time data. Personalization takes all historical customer data to make customer experiences into a customised one, while hyper-personalization then moves ahead by utilizing real-time data.

A personalization campaign could see an ecommerce company recommend products based on a customer’s purchase history and browsing behavior, recommending next things that the customer has either already purchased or seen. That is, the company offers an experience tailored to a customer’s previous behavior.

It would be very different if this same company were to run a hyper-personalization campaign, whereby real-time data like a customer’s location, time of day, or weather would provide an even higher level of personalized recommendations, were a clothing retailer to suggest warm winter clothing to an individual seen purchasing summer clothing recently based on a very cold snap in that person’s hometown.

You could then say that personalization gives relevant experiences based on past data, while hyper-personalization goes further by making real-time data useful for providing more customized and contextually relevant experiences. 

How Hyper-Personalization Works?

Hyper personalization delivers individualized experiences to customers through a combination of real-time data, artificial intelligence, machine learning, and other advanced technologies, including predictive analytics.

1. Artificial Intelligence and Machine Learning

AI analyzes an enormous set of data in real-time in order to personalize recommendations offered to individuals. Meanwhile, based on the study of behavioral habits and preferences over time, AI algorithms will optimise in relevance and precision when it comes to assigning content. Discover London’s premier hub for training and consulting in Artificial Intelligence and Machine Learning where data-driven insights meet precision personalization.

2. Analytics

Hyper personalization is mainly based on real-time analysis of customer data, which includes browsing behavior, purchase history, and demographic information. The collected data portrays the full picture of what the customer needs and is interested in.

3. Customer relationship management (CRM) software

CRM software collects and stores information about customers, including such things as who they are, what they buy, and their interactions with the enterprise. The attributes of this information make it possible for some personalization in marketing campaigns, as well as perhaps facilitate the creation of hyper-personalized experiences.

4. Locality-based technology

Location-based technology connects the customer to specific contexts with regard to his place through GPS or beacon technology. For instance, a restaurant may use Bluetooth beacons to personalize specific offers to customers around a restaurant or use an omnichannel retailer to personalize offers or prompts to customers walking through the store.

5. Chatbots and natural language processing (NLP)

NLP and chatbots can be used to create customized customer experiences with real-time recommendations. For example, chatbots are systems that analyze customer data to provide personalized responses to inquiries, whereas NLP does the same with sentiment.

6. Predictive analytics

Once the database is big enough and expanding, it can train the AI to automatically think about what the user might do next and become more proactive, even providing customer experience that might be classified as “special” because the customer didn’t even know he or she needed it.

Hyper-Personalization Strategies For E-Commerce

Different applications of hyper-personalization could be adopted by eCommerce companies. The most common has been the usage of AI algorithms that personalize product recommendations in hyper-personalized styles like those of Amazon’s Recommended for You feature that shows the products associated with a customer based on his interests seen online.

Such data could also be used to send marketing mails to customers based on what they did or did not do. For example, rather than just saying that every customer who bought running shoes now needs to buy the same socks, hyper-personalization can recommend a different style of socks to each customer and maybe sweatbands to those who have bought these socks during the last few weeks.

Marketing retargeting advertisements to customers showing personalized ads about their previous browsing and purchasing behavior may happen when they are off-site, whereas chatbots provide customer service support to consumers while they’re online. 

Hyper-personalization may also be applied to tailor particular incentives or rewards to individual customers; the specific incentive is ideally chosen for maximum chances of conversion. The same principle can work with prices, such as “travel booking sites offering personalized pricing at the exact point a customer is most likely to convert.”

How to achieve Hyper-Personalization

Time to enter hyper-personalization, if you haven’t already. We then impart some ideas about its implementation and how to build highly customized digital marketing campaigns to connect, engage, and convert well.

1. Data is everything: saying data is everything is almost an understatement when it comes to hyper-personalization. The information that you collect from your users basically determines the success of your campaigns. The more you know about your users, the more you can hyper-personalize your communications with them. 
2. Automation: It is completely impossible to understand and use behavioral data for each individual manually. An automation platform must, therefore, be set up to collect this data automatically. Platforms like Frizbit collect all behavioral data points so you need to set up your multi-channel marketing campaigns only once. Combining this with dynamic parameters enables the sending of hyper-personalized messages containing highly relevant content.  
3. Multi-channel communication: At this level of hyper-personalization, marketing takes a step further with combining hyper-personalization over different channels. Use web push notifications, email, and SMS collectively to connect with customers on their channel of choice to provide the most useful information.