According to Forrester Research, 89% of digital businesses invest in personalization. These include: "Coca-Cola, Fabletics, Netflix, Sephora, USAA, and Wells Fargo."
Why? Because personalized offers, incentives, and services differentiate CX. In doing so, companies can increase customer satisfaction, retention, and revenue.
Hyper-personalization is the next frontier on this journey. Instead of personalization through customer segmentation, this approach aims to achieve "strategic individualization".
Defining Hyper-Personalization
Hyper-personalization combines customer data and AI to generate insights. Either through humans or automation, companies harness these to alter experiences for individual customers in real-time.
For example, perhaps a customer is browsing a company's website. That business can combine a host of insights - such as time spent on search, purchase history, and seasonality - to zero in on what matters most to them. Harnessing these insights, a virtual assistant can proactively reach out with a recommendation or discount to increase potential spending.
However, hyper-personalization extends far beyond marketing and into other departments. Consider the contact centre as another example. Bots can track customer conversations in real-time, proactively feeding agents information to streamline and personalize the conversation. Such information may include sentiment insights that encourage agents to adapt their call handling to satisfy the emotional needs of individual customers.
Use cases such as these are a step forwards from customer segmentation. Instead, the entire customer base is a "segment of one". In other words, companies can treat customers as though they are in a demographic of their own.
Hyper-Personalization vs Personalization: What’s the Difference?
There are several differences between personalization and hyper-personalization:
- Data Use - Personalization relies on basic demographic information like name, gender, and location to segment customers into groups. Hyper-personalization, in contrast, assesses the behaviour of individuals to proactively enhance CX.
- Complexity - Traditionally, companies configure bulk personalization rules across entire segments. Hyper-personalization rules are more complex as they target a cohort of one. Instead, businesses establish thresholds, and deviance within those determines the delivery of CX.
- Customer effort- Hyper-personalization often reduces effort by tailoring the journeys to the needs of the individual. For instance, many strategies predict customer needs and proactively fulfil them. Doing so removes the customer from the loop altogether.
- The technology required- Personalization strategies often rely on customer segment information and automation alone. Alternatively, sophisticated journey analytics and machine learning tools fuel hyper-personalization.
How to Hyper-Personalize Customer Experiences
Begin with a customer journey mapping initiative, in which CX teams assess touchpoints and isolate hyper-personalization opportunities. While doing so, also consider the potential customer data sources that will bolster hyper-personalization initiatives.
For instance, perhaps a customer lands on the homepage of a customer website. Consider whether it is possible to access data that details where the customer is coming from if they have visited before, and their geographical location? Using this information, companies can customize the website.
Another example from much later in the customer journey is real-time product notifications. These share updates with customers, informing them of the status of their shipment. Companies can also offer customers refills to take this strategy further. Analytics tools that identify trends in the purchase history of customers are central to such an initiative.