Marketing efforts in the era of hyper-personalisation

Abstract

Marketing has evolved from Traditional Segmentation which is sub-division of the market into homogeneous sub-sections of customers, where anyone can be selected as a target market to Micro-Segmentation which is more granular approach than traditional segmentation as the segments are further classified in micro-segments using RFM analysis and intent-based segmentation (RFM:- Recency, Frequency, Monetary, Intent:- Probability of User Achieving a goal). Now, In the present era of digitalisation, Customer data/Information is readily available, which can be used to get insights about customer psychographics, rationale and behaviour patterns. This data can be leveraged to send personalised ads/offers using advanced analytics. Ads can be sent at the best time of the day based on real-time media usage data of the target customer. Moreover, since organisations can identify and tap into their customer needs, product-centric marketing can be replaced by personalised customer-centric targeted marketing campaign techniques, which therefore has a larger ripple effect on the traditional marketing strategies. According to Capgemini, "Hyper-personalisation is defined as advanced and real-time customisation of offerings, content and customer experience at an individual level".Hyper-Personalisation involves usage of Artificial Intelligence in real-time to provide the right content to the right customer at the right time. Some of the applications which are used in Hyper-Personalisation are Predictive Analytics, Open-Question Chatbots, Website content curation in real-time. As we can observe from the Personalization Maturity VS Revenue curve, the revenue increases almost exponentially with the increase in Personalisation maturity. While most of the organisations lie at the beginning of personalisation curve which involves (Single Mailing Message, Field Insertion and Rule-Based Segmentations), Companies like Amazon, Spotify and Starbucks are at the top of the curve and using predictive personalisation to target customers.