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A simple Google search for the word information gives an Internet user 347 entries. This is only one indicator among many of the level of information bombardment the average individual experiences. If this average individual is also a company director, the degree of the information barrage skyrockets. Currently, executives are going through the highest levels of information flow in history. A study recently carried out by the University of California (UCLA) concludes that in the last 30 years, Humanity has generated more information than in the previous 5,000 years.
Professors Peter Lyman and Hal Varian, of the Berkley’s School of Information Management and Systems, recently set out to quantify the information generated on the entire planet, during one year only. Their study put numbers to what is already clear to the majority of companies: society generates such an excess of information –the volume is duplicated an average of every two years–, that it is practically impossible to process it usefully.
Some data speaks for itself:
As we said earlier, while the average individual feels overwhelmed by the excess of information, the case of company directors is even more serious, since information is the principal tool on which companies base something as incredibly sensitive as strategic decision-making.
How much of the information directors receive daily is processed correctly? What information is true? What information can we trust without risk? How can we untangle, process, analyze, and clearly express so much information?
The challenge is as urgent as it is exasperating for many business leaders, who every day face the delicate task of making decisions based on rigorous information. The gathering and analysis of financial data has evolved considerably over recent years. However, the same cannot be said of sales and marketing information.
. Tools as controversial as CRM applications have without a doubt contributed to improving the flow of customer information that companies deal with. But it is essential to distinguish between the gathering, storage, and organization of data, and the subsequent analysis and interpretation of it. CRM is still another business tool that requires an appropriate Customer Intelligence strategy, capable not only of organizing data, but also “exploring” it and reaching irrefutable conclusions.
A survey carried out last year by Daemon Questii showed the precariousness that the Sales and Marketing Management of large companies faces in order to correctly process and analyze customer information. Some revealing data:
The avalanche of data that overwhelms business leaders daily has created a new generation of “info-addicts” and “infoxicatediii” executives; a generation of executives that demands and untangles information indiscriminately, but who at the same time are victims of the “consumption” of both correct and incorrect data…
The causes of jump from an Information Society to an Information Anxiety are multiple and complex, but among them stand out:
How can we access documented and reliable information that supports strategic decision-making? The answer lies in organizations’ generalized adoption of scientific marketing, capable of turning data into knowledge that backs up the decision-making process.
The 21st century will most likely go down in history as the century of the scientific boom. Analysis methods are beginning to go beyond scientific fields, although they are only timidly entering companies. Why not apply scientific advances to the sales and marketing fields? Why are financial fields already based on rigorous, scientifically proven methods, while marketing often continues to be based on such subjective and volatile criteria as intuition?
It is becoming more and more pressing to develop a scientific marketing that, like a still, “distils” all of a company’s customer information, giving directors “the essence”, that is, conclusions based on empirical data, that drive an accurate decision-making process.
New Customer Intelligence strategies are making headway, based on techniques that directly emanate from the statistics field, mathematics, modeling, and other scientific areas. At the foundation of these techniques are the company’s own internal databases (or Data Warehouse, if the volume of information is considerable), but also public and external ones. Both information sources are crossed using sophisticated analytical techniques, in order to reach precise conclusions regarding the present, past, and future behavior of real and potential customers. Among the most commonly used techniques in the field of High-Tech marketing are:
The term “mining” in the expression “Data Mining” was not chosen randomly: just as a miner tirelessly searches for precious metal hidden in rock, “Data Mining” allows us to find the “gold nugget” hidden among the informational sludge. Models, conclusions, correlations, patterns, or trends are automatically, and, more importantly, quickly revealed with “Data Mining” techniques. Thus, the head of any company can have scientific tools at his or her disposal that assist in strategic decision-making. Data Mining is capable of diving into a sea of information in order to predict behavior and act accordingly.
. “Data Mining” is not synonymous with statistics, although it shares many common points. The main difference between the two concepts is that while Data Mining “explores and predicts”, statistics basically “confirms”.
The techniques “Data Mining” is usually based on are:
The combination of these techniques is allowing for surprising advances, not in exclusively business fields, but in a certain way perfectly suitable, surprising as it may seem, to the marketing world. Let’s look at a few examplesiv:
Do all companies know that these techniques are perfectly applicable to the world of marketing and customers? The applications are as useful as they are varied. Let’s imagine the sales team of a large distribution company. The members of this team are most likely capable of figuring out that a high percentage of consumers that go to the “hypermarket” to buy detergent, also end up buying fabric softener. What they could never know is that many of them also buy wine, especially if it’s Saturday afternoon. Only “Data Mining” techniques, applied with computers and controlled by specialists (analysts, mathematicians, statisticians…), are capable of illuminating these types of correlations, which the human brain cannot access, but which are extremely useful for business management. Knowing that customers who go to the hypermarket to buy detergent on a Saturday afternoon have a high probability of purchasing wine, our management team will most likely consider some type of promotion involving both products, or they will place them close to one another on the aisles.
Data Mining’s main objectives are the creation of descriptive models (discovering correlations, patterns, or tendencies) in order to understand the “hidden” reality, as well as the creation of predictive models that help foresee the future and, as a result, define intelligent strategies.
Knowing who the minority of customers is that generates 70% of a company’s benefits; figuring out how demographical, geographical, and social factors condition the purchase process; designing more accurate and affordable marketing campaigns; calculating how much it costs us to add a new customer to our portfolio; predicting which customers have a high probability of leaving us and going to the competition… These are only some of the immense possibilities that these new techniques open for the company. Like the oracles of Ancient Greece, “Data Mining” is data’s hidden voice; a voice that knows, predicts, and guides human beings.
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