Hyper-personalization
Evolving consumer expectations require hyper-personalization to create meaningful connections with customers by utilizing modern digital experience platforms (DXP).
What is hyper-personalization?
Hyper-personalization uses artificial intelligence (AI) and machine learning (ML) to go further than segmentation and allow you to create a customer experience that is unique to an individual.
With the use of big data, analytics, individual journey maps, and personalized content, hyper-personalized experiences help attract customers, drive profits, and reduce costs. Ongoing efforts to better segment customers are useful but AI is more effective at responding to changes in a visitor's behavior quickly. Using hyper-personalization, marketers can proactively adapt experiences to create unique touchpoints that are personalized to individual visitors.
Hyper-personalization aims to build lasting relationships, evoke meaningful responses, and deliver unique experiences to increase conversion rates and grow customer lifetime value.
How hyper-personalization works
Real-time data combines with AI processing to control how you deliver content, suggest next steps, respond to events, thereby controlling every touchpoint in your journey map based on customer data. While it cannot design your strategies or replace your multivariate testing, you can use the data to control how you deliver experiences to users.
Hyper-personalization requires you to model different behaviors and use algorithms with real-time data to decide when the optimal time is to deliver a communication, alert or offer. Every touchpoint in your journey map can benefit from hyper-personalization by engaging with users directly and anticipating their needs accurately.
Benefits of hyper-personalization
Traditional personalization techniques helped companies engage with customers and create targeted content and experiences based on historical analytics. Hyper-personalization still requires CX designers, multivariate testing, and experimentation to build journeys but uses personalized delivery algorithms to optimize the entire experience.
Companies that implement hyper-personalization benefit from:
- Reduced obstacles in sales journeys that cause complications in the experience and hinder visitors from becoming customers
- Preventing overburdened customers from abandoning carts by using specific algorithms that limit choices based on a visitor's current and past behavior (instead of relying on segmentation and automation alone)
- Attracting and retaining new customers with unique messages, communications, offers and content that drive revenues
- Keeping up with customer expectations as they evolve and ensure the content, journey and overall experience matches the latest trends
Hyper-personalization best practices
Hyper-personalization requires organizations to continuously optimize journeys based on the real-time collection of data. Experimentation with different content and experiences will enable you to improve the framework and create optimized algorithms, while the technology behind the process will allow you to automate almost every element in your delivery process.
To get the best ROI from hyper-personalization, you should:
- Collect the right data during every visit and record as much unique information about visitors as possible
- Provide customized offers based on previous interactions and use AI algorithms to continue optimizing the journey for every subsequent visit
- Deliver personalized content and messaging across all your websites, social media, apps and any other emerging delivery platforms
- Test different hyper-personalized experiences and use this information to perfect your content designs, delivery methods, and more importantly, determine when to deliver the content
You'll need to use all pertinent data that you collect to help your AI and ML model evolve with your customers, understanding where friction points emerged so you can eliminate them over time.
Hyper-personalization process
Creating a hyper-personalized experience starts with leveraging new and existing data to create detailed profiles for each visitor. A DXP enables you to get started quickly, helping you to personalize content based on your existing touchpoints, optimize your segmentation for unique profiles, and streamline your delivery across all channels.
These are the major elements of a hyper-personalization process:
- Data -- Start with gathering and optimizing consumer data by identifying specifics about every individual journey. You can then create a personalization strategy for the best way to utilize this information in your hyper-personalized customer journeys.
- Content -- Next, create the content specific for each individual journey you think can influence the overall experience. Decide on the type of delivery (email, pop-up messages, or specialized offers) that will likely convert visitors into returning customers.
- Deliver -- Ensure you deliver consistent, individual experiences across all digital touchpoints at the right time, optimized for the applicable device, and according to the customer's personal preferences. Your analytics will help you to optimize your content management system (CMS) and delivery schedules.
- Unify -- Bring all the other elements together using a DXP that automates the delivery schedules according to unique profiles, allowing you to continue content experimentation, and set up the algorithms to continue optimizing all experiences.
Hyper-personalization use cases
Hyper-personalization isn't entirely new -- many organizations have proven the value of following this strategy when designing their digital journeys. What is new is the systems that provide these new capabilities are no longer just available to the biggest ecommerce and SaaS companies.
Some of the organizations that benefited from hyper-personalization include:
Airbnb
Started using location services to populate a variety of forms automatically, depending on what service the visitor wanted to sign up for on their site. Once the visitor did sign up, every journey is unique to the person while it keeps a complete history of all their interactions on the site.
Reebok
Even when someone doesn't complete a purchase on the Reebok store, the site will track all the visitor's events and if you're signed up to receive communications, send you a personalized email that recommends the best products according to your browsing history. Reebok keeps track of each user's visit, uses algorithms to identify the related products, and creates an automated product list with a unique message using hyper-personalization.
Amazon
Once again, Amazon is one of the early adopters who built their entire ecosystem on hyper-personalization. Users get unique homepages, highly accurate product recommendations, the opportunity to increase orders with supporting items, and a seamless checkout experience. From the beginning, Amazon continued to reduce friction points according to an individual's routines and preferences.
Delivering meaningful connections with Optimizely's DXP
Realizing your digital potential depends on delivering unique, optimized experiences with automated content delivery, rigorous experimentation and hyper-personalization. Most CMOs need to drive profit, innovate new products, and continuously improve experiences by making data-driven decisions. Hyper-personalized content helps achieve these goals when delivered at the exact time required and evolving with the user's unique journey.
Optimizely provides you with a comprehensive set of capabilities to unlock your digital potential and deliver truly unique experiences to your customers. Analytics help you make better decisions while our experimentation tools take the guesswork out of your content delivery and user journey maps. With Optimizely, you can deliver meaningful digital experiences that speak to each visitor individually.
For more information about Optimizely's DXP and hyper-personalization capabilities, reach out to one of our agents and discuss your needs today.