Personalization is widely used to attract and retain customers in online business addressing one size fits all issues, but little is addressed to contextualise users' real-time needs. E-commerce website owners use these strategies for customer-centric marketing through enhanced experience but fail in designing effective personalization due to the dynamic nature of users' needs and pace of information exposure. To address this, this chapter explores hyper-personalization strategies to overcome users' implicit need to be served better. The research presents a hyper-personalization process with learning (ML) and artificial intelligence (AI) techniques for marketing functions like segmentation, targeting, and positioning based on real-time analytics throughout the customer journey and key factors driving effective customer-centric marketing. This chapter facilitates marketers to use AI-enabled personalization to address customers' implicit needs and leverage higher returns by delivering the right information at the right time to the right customer through the right channel.
TopPersonalization And Artificial Intelligence
Recent growth in online business has resulted in increased use of different personalized services to develop one to one customer relationships, effective marketing, and to attract users and retain customers. Ecommerce websites use personalization as an effective strategy by providing one to one services like product recommendation, information and ratings of the product by satisfying individual users' needs. Personalization is used in different dimension like information, interface and structural navigation of the website on one to one basis, information and navigation personalization increase satisfaction level with highly relevant content which reduces cognitive efforts on ecommerce website over information overload (Desai 2019). Ecommerce Websites like Amazon.in provide product recommendations based on collaborative filtering techniques and also suggest some frequently buy items with people having similar interest in products. User's’ navigational behavior and search is analyzed and extracted knowledge is used to target users by showcasing advertisements catering their implicit need e.g. Facebook.com, and gmail.com. Personalization of Social Networking websites have also shown significant impact of control to develop trust towards website (Desai 2021) which can be significantly used as an effective marketing tool for advertisement. Vendors are also using personalization to match advertising and promotions with customers’ individual needs and preferences in what is known as targeted or behavioral advertising. Personalization is widely used and has always been one of the key drivers of creating enhanced customer experience in the digital business to remain in the marketplace across industries. A Gartner survey in 2019 found that 38% of customers stop interacting with the e-commerce website and unsubscribe if they find personalization efforts by the business are irrelevant and creepy. Marketing leaders strive to achieve a highly tailored message to customers to cater to the dynamic needs of the customer. However, with evolving customer awareness, digital marketing, and brand promotion in business need to elevate and redesign marketing strategies to push personalization to different levels by enabling adaptive content, functionality, and interaction in real-time in the digital landscape.
Personalization is extensively used in marketing but struggles in design of marketing strategies for customer centricity due to its dynamic needs. Hyper-personalization has emerged as an advanced way of marketing with real-time analytics of data, Artificial intelligence, and automation to bridge the gap. Artificial Intelligence is not only used in the ecommerce sector it is emerging to facilitate customers from various other domains like financial, healthcare, ecommerce services etc. Recent studies focus on handling strategic marketing issues to achieve personalization and its impact like unstructured data handling to integrate with existing areas of marketing, recent studies trying to tackle strategic marketing issues. Balducci and Marinova 2018 identified use of unstructured data for several areas of marketing, Agarwal et al. 2020 explored use of analytics for consumer value in healthcare, Tong et al. 2020 used machine learning technique for prediction with personalized mobile marketing, and Kumar et al. 2019 used AI for engaging customer using personalization, also Desai 2019 found positive impact of personalization on customer satisfaction.
AI enabled personalization caters highly contextualized experience to individual consumers to meet distinct implicit and explicit needs across each touch point consumer journey using real-time data analytics, 360-degree customer view, and providing communication of the right product or service, at the right place, right time, and right channel. Hyper-personalization gives more insight to understand customers better, dives deep to analyze their behavior, preferences, likes, and understand needs and wants of customers. Hyper-personalization leverages real-time data analytics and AI to generate a highly contextualized customer experience.