The new normal has compelled businesses to transform how they operate. In the post-Covid era, organizations are looking for ways to improve the customer experience, and evolve their customer interactions to be more digital, targeted, precise, and personalized. However, to achieve this, they need to leverage customer data at the most granular level. Adopting a hyper-personalized customer targeting and communication strategy will enable organizations to communicate effectively and contextually with their customers.
Businesses are expected to not just meet the needs of the customers, but also anticipate and exceed them. Having a comprehensive communication strategy is not enough anymore, businesses need to harness the power of analytics and Artificial Intelligence (AI) to create stronger and more authentic interactions with customers.
A recent study by Accenture revealed that 75% of customers are more likely to purchase from an organization which offers personalized services based on their individual preferences. As a result, several businesses are shifting to a more personalized approach in providing services to their customers.
Hyper-personalization enables brands to target individual customers through a tailor-made marketing strategy. Through the use of data, analytics, AI, and automation, hyper-personalization empowers companies to design contextualized communications. It focuses on gathering real-time behavioral data of customers through IoT and other digital channels such as their online activity log to understand their needs and desires. For instance, a digital marketer can study the online behavior of customers through their past interaction with the brand and cookies to tailor-made advertisements that appeal to the customer.
While creating hyper-personal experiences for customers, the importance of context cannot be undermined:
A hyper-personalized experience is incomplete without context. Hence, creating a hyper-personalized marketing approach is easier said than done. Businesses need to take a lot of factors into consideration such as context, data, analytics, and these factors need to work in tandem.
Here are the critical steps for creating a hyper-personalized framework:
Data Collection – The first and most fundamental step in the creation of a hyper-personalized framework is the collection of data. Without behavioral data, it will be impossible to understand the customer. As per a report by IBM, around 80% of customers feel that brands fail to understand them as individuals. A business interacts with an array of customers, hence it is important to understand their individual tastes and preferences. Collecting accurate and relevant data becomes a must for successfully customizing experiences.
Customer Segmentation – When a business has collected a significant amount of data to run analysis, they can segment their customer into various subsets based on factors such as average spend, location, demographic, satisfaction, brand interaction history, etc. This allows businesses to understand the taste and preferences of customers as a group and design specific messaging for each group.
Targeted Journeys – Once businesses have identified and segmented their customers, they can initiate hyper-personalized communication. Based on the analysis, businesses can choose the right platform and time for delivering the targeted campaigns. This enhances the chances of customer interaction with the brand.
Measurement and Analysis – Just running a targeted campaign isn’t enough though. It’s important to measure the success of the campaign too. Understanding the customer segmentation wouldn’t work for long if there aren’t properly defined metrics to measure the efficacy of the campaign. The measurement metrics allow marketers a deeper insight into customers’ behavior and patterns, which further enables them to strengthen the campaign.
Here are some examples of businesses that have successfully integrated hyper-personalization in their customer interactions:
Stitch Fix is an online retailer that offers customers access to personal stylists who help them find clothing based on their specific tastes. What makes this platform so unique is its personalization process. Stitch Fix asks customers a series of questions to gauge their style and a stylist handpicks five items for the shopper. The items are sent to the customer’s home where they can try everything and only pay for the items they’d like to keep. This way Stitch Fix engages with the customer better, at the same time get insights into their personal style and preferences for future targeting and products offering.
Amazon, the biggest online retailer, by making use of data, analytics, and AI creates a personalized homepage for its shoppers based on factors such as shopping history, wishlist, and shopping cart. By understanding its customers’ behavior, Amazon makes their shopping experience seamless and less time-consuming.
Grammarly, a digital writing assistance tool based on artificial intelligence and natural language processing, expertly uses productivity reports to boost engagement from their users through their ‘Weekly Writing Update’. In the hyper-personalized email that goes out to their users, they include a number of useful insights – with a gamification flavor – from writing style and productivity all the way to vocabulary and tone. It offers the user a personalized and engaging experience, but also draws their attention to the value they get from the platform.