Introduction

In the early years of this decade, the euphoria over Customer Relationship Management (CRM) software, widely shared in the 1990s, evaporated and consumers publicized their despair over the poor financial results realized from their investments akin to the disillusionment with other information technologies. With the benefit of hindsight, customers can now see that the early CRM technologies had a modest objective of accumulating transaction data. The truth is that the “irrational optimism?about CRM clouded judgments in the 1990s. The “irrational pessimism?that ensued missed the promise of CRM, i.e., the ground had been prepared for decision support solutions including predictive analytics.

On the rebound from the bubble pop, an increasing number of customers realize that the payoff from the investments in CRM will come from the efficiencies that can be realized from the surefooted implementation of business strategies. Gut feeling and intuition is giving way to statistical forecasts as large data sets and their analysis with a new generation of analytical and forecasting software helps to make decisions with more predictable outcomes.

Business uncertainty has increased in recent decades with globalization, technological and demographic change. Consumers have many more products to choose from and product obsolescence is much more rapid. Companies cannot any longer expect to dominate mass markets and have to learn to select activities that will be most profitable given their competencies and resources.

Unlike in the past, mass media is not any longer able to hold the attention of large numbers of consumers. Network television faces intense competition from cable and satellite television. Newspapers and magazines have to cope with the Internet and Blogs. Companies have other means of promoting products such as public relations, events and viral marketing. These channels interact in a variety of ways that were not foreseen in the past.

Similarly, companies have to choose from a host of channels for distribution of their products. Besides the traditional channels like direct sales force and convenience and department stores, e-commerce offers several different choices.

Fortunately, business intelligence and analytics software enables companies to navigate their way in this environment of pervasive clutter. Unlike in the past, companies cannot any longer afford the trial-and-error methods since they would have to conduct several experiments before they find one that works for them. Instead, they need to be able to predict, with acceptable levels of accuracy, the customer segments, the products, media and distribution channels that will be most profitable.

Armed with the data and analysis they need, companies can now conduct targeted marketing campaigns with better results. The data gathered from marketing campaigns helps them to improve the quality of their databases, make better forecasts in the future and improve their returns from customer acquisition, retention and extension.

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