Personalization vs Hyper-Personalization: Is it just hype or does it deliver results
Personalization has been a buzzword for some years. Tailoring a user experience according to the preferences and interests of your customers makes great business sense: it can build trust, strengthen relationships, and boost sales by showing customers more relevant product recommendations. Unfortunately, personalization as we know it simply doesn’t go far enough. If you genuinely want to realize the benefits of personalization, you need to speak to customers on a granular, individual level. You need a hyper-personalization strategy.
What Is the Difference Between Personalization and Hyper-Personalization?
Personalization is the practice of providing personalized experiences based on a customer’s preferences and behavior. Online businesses may recommend products based on their customers’ recent purchase history or send targeted email campaigns to customer segments with similar interests.
Hyper personalization is a personalized marketing approach that goes beyond traditional personalization campaigns by leveraging real-time behavioral data and advanced algorithms to provide a far more customized experience for individual customers. Hyper personalization doesn’t just consider a customer’s past behavior and preferences. It considers their current context, location, time of day, and even the weather to provide personalized content, recommendations, and offers to the customer.
The main difference between personalization and hyper-personalization is the level of customization and the use of real-time data. Personalization uses historical customer data to create a tailored experience for customers, while hyper-personalization uses real-time data to provide even more customized and contextually relevant experiences.
A personalization campaign might see an ecommerce company recommend products based on a customer’s purchase history and browsing behavior, suggesting similar products to those the customer has already purchased or viewed. In other words, the company offers a tailored experience based on past behavior.
If the same company decided to launch a hyper-personalization campaign on the other hand, they would use real-time data such as a customer’s location, time of day, or weather to offer even more personalized recommendations, e.g., a clothing retailer suggesting warm winter clothing to a customer based on a recent cold snap in their hometown.
You could say that personalization provides relevant experiences based on past data and that hyper-personalization takes personalization a step further by using real-time data to provide even more customized and contextually relevant experiences.
How Does Hyper-personalization Work?
Hyper-personalization uses a combination of real-time data, AI, machine learning, and advanced technologies (including predictive analytics) to deliver individualized experiences to customers.
Artificial intelligence (AI) and machine learning
Artificial intelligence (AI) technologies are used to analyze large amounts of data in real time and create personalized recommendations for individual customers. AI algorithms can learn from behavior and preferences to provide even more accurate and relevant content over time.
Hyper-personalization relies on real-time data analytics to collect and analyze customer data, including browsing behavior, purchase history, and demographic information. The data collected is used to create a complete picture of the customer’s needs and interests.
Customer relationship management (CRM) software
CRM software is used to collect, store, and analyze customer data, including contact information, purchase history, and customer interactions with the company. The data collected is used for creating personalized marketing campaigns and can assist the company with creating hyper-personalized experiences.
Location-based technology, such as GPS and beacon technology, is used to provide contextually relevant experiences to customers based on their current location. Using Bluetooth beacons, a restaurant may send personalized offers to customers when they are in the vicinity of the restaurant, and an omnichannel retailer can send personalized offers or suggestions via their app to customers when they walk into the store.
Chatbots and natural language processing (NLP)
Chatbots and NLP are used to provide personalized recommendations and assistance to customers in real time. Chatbots can analyze customer data and provide personalized responses to customer inquiries, while NLP can analyze customer sentiment and provide personalized responses based on customer mood and tone.
Once you have more data at your disposal, AI can be trained to predict user behavior and become far more proactive, providing customers with special experiences they may not even know they needed.
Benefits of Hyper-personalization
Hyper-personalization has numerous benefits, especially for ecommerce businesses, including:
Increased customer engagement
Hyper-personalization creates a more engaging and relevant experience for customers, leading to higher engagement rates and a deeper connection with the brand. When customers are consistently presented with messaging and products that are relevant to their interests and needs, they feel greater affinity with the brand and are more likely to return to the site again and again.
Higher conversion rates
By providing personalized recommendations and offers based on a customer’s current interests, hyper-personalization can increase conversion rates and drive more sales. Customers are far less likely to abandon their cart if an AI bot offers support when it recognizes that they have gotten stuck, and they are far likelier to make a purchase if presented with the most relevant offer or appealing price available.
Improved customer satisfaction
Hyper-personalization can lead to higher customer satisfaction. Customers don’t need to scroll through pages looking for something they want or need because the hyper-personalized engine can recognize what they are looking for and present them with the best possible match. Shopping becomes far more exciting and less frustrating.
Increased customer loyalty
When customers feel that a brand understands their preferences and needs, they are more likely to remain loyal and continue doing business with the company.
Improved customer insights
Hyper-personalization can provide valuable insights into customer behavior and preferences. This can only be used to inform marketing and product development strategies but to make better decisions about inventory and buying, reducing overstock and boosting profitability.
Hyper-Personalization Strategies For ECommerce
ECommerce companies can use hyper-personalization in a number of different ways. The most common application has been the use of AI algorithms to deliver hyper-personalized product recommendations to customers, e.g., Amazon’s Recommended for You section that displays products to customers based on the interests they’ve shown online.
The data collected can be used to send marketing emails based on a customer’s behaviors and interests. Instead of recommending the same pair of socks to every customer that bought a pair of running shoes, hyper-personalization enables companies to recommend different styles of socks to each customer and recommend sweatbands to the customers that already bought socks in recent weeks.
Marketers can use retargeting ads to show personalized ads to customers based on their previous browsing and purchase behavior when they are not on the site, while chatbots can provide customer service support to individuals while they are online.
Ecommerce companies can also use hyper-personalization to offer individualized rewards and incentives to customers, choosing the exact incentive that is most likely to convert the customer. The same principle can be applied to pricing, e.g., travel booking sites offering personalized pricing at the exact point that a customer is most likely to convert.
Hyper-personalization in Other Industries
Ecommerce isn’t the only industry that has utilized hyper-personalization. Services like Netflix and Spotify use personalization to recommend movies, TV shows, and music based on a user’s viewing and listening history. Hotel and airline websites often use personalization to recommend destinations, hotels, and flights based on the customer’s past searches and bookings. Banks and credit card companies use personalization to recommend financial products and services based on a customer’s spending habits and credit history. Even healthcare providers use personalization to tailor treatments and recommendations based on a patient’s health history and current needs.
Coffee brand Starbucks uses AI to send their customers unique offers based on their activity and preferences. They’ve generated over 400,000 variations of hyper-personalized marketing messages so that caffeine addicts always feel special when they receive communication from their favorite coffee shop.
TastryAI works with wineries to help customers choose a wine, even if they aren’t familiar with the variant. By completing a simple 20-second quiz, AI can make a recommendation from thousands of wines based on their answers. Once they’ve tasted and ranked their wine, the app will continue to finetune their recommendations.
Another great example of hyper-personalization in action is the travel brand Secret Escapes. They used the keywords and paid ads users have clicked on or searched for to take visitors to a personalized landing page with imagery and copy that reflects their intent. The company is said to have boosted its sign-up rate by 26% through this campaign.
It’s clear that hyper-personalization is a key strategy for virtually all industries and businesses with an online footprint. By leveraging real-time data and advanced AI-driven technologies, companies can create truly unique and tailored experiences for each individual customer and boost loyalty, sales, and engagement for good.
If you want to book a free consultation with us on how a hyper-personalization solution can work with your e-commerce store, send us a message.
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