The mission of building one-to-one communication and engagement is not a new concept. Back in 1993, Don Peppers and Martha Rogers, Ph.D., proposed that organizations could use technology to gather information about, and to communicate directly with, individuals to form a personal bond. The book, The One to One Future: Building Relationships One Customer at a Time, stated that technology had made it possible and affordable to track individual consumers, to understand each person's individual journey, and to provide contextual offers at the optimal time of need. Six years later, internationally recognized best-selling author Seth Godin published Permission Marketing. He built a logical case for creating incentives for consumers to accept advertising voluntarily.

The mission of building one-to-one communication and engagement is not a new concept. Back in 1993, Don Peppers and Martha Rogers, Ph.D., proposed that organizations could use technology to gather information about, and to communicate directly with, individuals to form a personal bond. The book, The One to One Future: Building Relationships One Customer at a Time, stated that technology had made it possible and affordable to track individual consumers, to understand each person's individual journey, and to provide contextual offers at the optimal time of need. Six years later, internationally recognized best-selling author Seth Godin published Permission Marketing. He built a logical case for creating incentives for consumers to accept advertising voluntarily.

Financial Marketers in recent years, have been actively leveraging all types of traditional and new-age marketing channels to engage customers on their digital and mobile journeys. However, customers still expect Financial Institutions to know their preferences and provide a much richer personalized experience. In this era of hyper-personalization, data about users is paramount. Even with all the digital transformation in progress, data is largely available in silos among different departments such as Marketing, Sales, Operations, and Customer Care. Users visit financial websites and mobile applications at different times and on different devices and these visits could often be mistaken as different users. Having a single view of the user and engaging them through consistent messaging is important.

AI and machine learning are making the customer experience more personalized and contextual than ever before. Banks and credit unions are using advanced technology to make websites, emails, digital advertising, social media and other content more efficient and effective. This is increasing marketing ROI as well as customer satisfaction. Subscribe to The Financial Brand via email for FREE!There is a great deal of discussion of the potential value of artificial intelligence, machine learning and robotics in banking. Unfortunately, much of the implementation of these technologies lags the potential by a significant margin.

Introduction This article describes the initial stages of an effort to develop a knowledge-based financial marketing consultant system. The project for Financial Marketing Expertise (FAME), is to produce a system that addresses the area usually referred to asfinnncial nzarketing. This term characterizes the financial decision processes used in the marketing of products and services of such large scale that they can significantly impact a company's financial status. In particular, our project emphasizes financial marketing as it applies to the marketing of computers. For instance, a customer interested in buying computing technology on a large scale is usually concerned that the financing plan being used to acquire the technology is safe, sound, and attractive from a financial investment point of view. Therefore, in making very large sales, financial considerations often become as important as the computing considerations. We have found financial marketing to be a very interesting and ...

This article describes an effort to develop a knowledge-based financial marketing consultant system. Financial marketing is an excellent vehicle for both research and application in artificial intelligence (AI). This domain differs from the great majority of previous expert system domains in that there are no well-defined answers (in traditional sense); the goal here is to obtain satisfactory arguments to support the conclusions made. The experience gained in the initial prototyping effort is currently being used to further expert systems research and to develop an extensive system that ultimately can be used by the marketing organization.