AN ANALYSIS OF CUSTOMER'S EMOTIONAL-AI USING NATURAL LANGUAGE PROCESSING

Abstract

It is imperative that today’s companies create compelling, differentiating customer experiences through marketing. Predictive marketing (Artificial Intelligence) changes the game for marketers: it gives firms the ability to anticipate consumers’ needs and interests, and more importantly, their likely reactions to marketing messages. AI can be more focused on delivering ads to people, with less guesswork. AI predicts that some 55% of all digital advertising dollars will be driven by programmatic initiatives in 2015, as machine learning takes precedence over human analysis. The figure is predicted to rise to 63% by 2016, which represents $20 billion in programmatic ad buys. With AI, marketers will be able to understand consumers on an intricate level.1 The entire experience will be tailored to the recipient to ensure every ad is relevant, a far cry from the days of blanket coverage and disruptive marketing techniques. Just like billboards on roadsides, pre-AI ads relied on a disruptive advertising strategy, designed to distract and conquer. Unfortunately, these efforts translated to little more than guesses about what consumers may want to buy based on the few details the company could glean from their IP address. This approach to advertising, however, failed to understand the context of individuated customer searches, an issue AI overcomes through ‘intelligent learning’. The proliferation of digital devices raises an opportunity and a threat for marketers: with more data than ever before, marketers can better understand their customers and attempt to serve them more relevant, tailored messages and suggestions. The flipside for many marketing organizations today, is that they are now faced with more than they can handle. Too much data emerging from too many data sources present difficult challenges to customer intelligence and marketing teams’ ability to generate and act upon meaningful insights. Artificial intelligence becomes necessary to accelerate the loop from [vi] insights to execution. Without it, marketers will struggle to achieve their objectives of delivering truly personalized 1:1 marketing interactions in real-time. Artificial intelligence will drive innovation in marketing, by helping marketers move from post campaign optimization to a more predictive execution and optimization of campaigns. In February 2017, Rocket Fuel commissioned Forrester Consulting to explore predictive marketing and AI themes to better inform marketers and agencies about the benefits and challenges of its application. The survey covered France, Germany, Italy, UK, US and Australia.