AdRobot

Abstract

Digital Advertising and promotional e-campaigns have been a basic pillar of marketing. One of the main challenges marketers face nowadays is about associating the right promotion to the right customer. Making the product-customer assignment accurate is crucial to satisfy customer needs. However, manually analyzing qualitative data for the purpose of defining the right target audience is exhausting and time consuming, especially when the number of costumers is high. In this paper, our aim is to automatically assign personalized campaigns that match specific customer desire, therefore making promotional campaigns consistent with their interests. Automating the process of assigning the right promotion to the right customer according to its specific needs is appealing as customers often show little to no interest in random ads. Our solution, referred to as "AdRobot", aims at overcoming these challenges by gathering complex data and insights into the target audience using data collected from conversations via the designed chatbot. Our strategy consists of performing fine-grained audience classification by segmenting profiles based on some profiling and conversational constraints, so that the audience is matched with the right promotional campaign. In order to achieve this goal, we propose an algorithm that investigates profiling and conversational data collected along with the customers' intents using artificial intelligence heuristics. Results show that "AdRobot" accurately matches promotional campaigns with the right customers according to their needs.