It’s popular these days to say that customers are in control of marketing, since digital commerce is propelling a healthy democratization of the company-customer relationship. Data available to companies and consumers enable both sides to know more about what the other is thinking and doing.

Gaining Customer Data Insights is Crucial

Online data, especially, is creating new opportunities for businesses to generate new types of value for consumers and new sources of profit, as it represents without a doubt a rich resource of customer knowledge that can support smarter marketing decisions across multiple channels.

You can make use of the insights gained through analytics for campaign management strategies or take action on it by embedding analytics into what you’re doing with your different marketing campaigns, both in batch or real time. And that’s not even too difficult as the internet, email, data warehouses, radio frequency identification technology (RFID), enterprise resource planning (ERP) software, iPods, cell phones, or virtually any technology that stores digital information, are all repositories for potentially valuable data.The key challenge is rather how to create business value out of all the data available and how to combine all of it in the first place.

“If you can learn to look at data in the right way, you can explain riddles that might otherwise have seemed impossible. Because there is nothing like the power of numbers to scrub away layers of confusion and contradiction”, Steven Levitt and Stephen Dubner wrote in their bestseller Freakonomics. And indeed, by mining multiple databases and asking smart questions, there simply has to be an appropriate outcome of useful information. Besides, there has never been a better time than living in the digital age where it is possible to collect and store huge amounts of data easily, to start such a venture. Unfortunately, marketers in the past generally over invested in the technology to store and collect data, but did not invest not enough in the key automated analytic capabilities to apply the data to decision management – but it’s time now to analyze and monetize your data by gaining more insights into the heads of your customers.

Integrate analytics into every facet of marketing

If you want to properly leverage the data for customer profiling and segmentation, or predictive modeling and forecasting responses to a campaign, there is no other way than to make use of technology that automates the execution of decisions across a complex operating environment.

Making their decisions based on segments has been so far easy for mass marketers, as all they had to do was send a predefined set of offers to specific customer groups, which was a one-time, one-way communication.  However, with the advent of the internet and other two-way channels, vastly redefined segmentation, which has gone from the basic two segments to millions of segments, is becoming more important to operations.

Today’s customers expect to receive differentiated treatment across different points of interaction, which puts added pressure on marketers to find the right balance in segmentation: it has to be personalized enough to be perceived as “individual” by the customer, yet broad enough so that operations can achieve profitable operating levels. Not to mention that if it is too broad, customers will get turned off and if it’s too personalized, a company’s operations may become so complex that it will not be cost effective.

Predictive analytics to determine possible outcomes from a contemplated decision

Predictive analytics is the practice of relating what you do know, at the time you make a decision, to what you don’t know and might happen in the future. By using a variety of statistical, computing, and mathematical techniques, consumer businesses use predictive analytics to find behavioral patterns in historical consumer data that forecast the likelihood of a particular outcome. It is a powerful tool that is able to manage high-volume decisions in near or real time by analyzing billions of historical data points and transactions to isolate patterns and characteristics.

The approach of making use of predictive analytics makes obvious that technology, commoditization, deregulation, and globalization has simply changed customer relationship management forever – allowing power and choices to the customers. With a few clicks, they can either buy from you or your competitor. They’re not just lining up to buy what’s offered, they expect to be valued participants in the process, be treated well as individuals, and not just account numbers, and not to have waste their time with empty banter.

Taking all this into consideration, it doesn't make it easy to create relevance as marketers still truly need to understand their customers and find a way how to get to know their online behaviour, preferences, and campaign contact history, before being able to develop and design relevant marketing campaigns.

Thus, first of all, customer information data has to be collected, aligned, shared, and integrated, which is actually no problem as the availability of raw data keeps getting cheaper to generate. Nowadays, physically and virtually everywhere our lives operate on continual streams of digital data, residing on computer databases, both private and public. It’s a fact that there isn't a business or consumer anywhere today that hasn't been touched by the trillions of revealing bytes moving through wired and wireless, stationary and mobile information technologies. All 21st-century operations, no matter the industry or where or how they operate, therefore face the same challenge and opportunity: How to make most out of the unprecedented access to such huge amounts of digital data as well as what to do with this data to stimulate the next wave of business innovation?

Internet data masters, such as Amazon and Netflix, have made analytics and algorithms the hottest buzzwords in business, but how many executives really understand what analytics can do for them? Be assured, that it is not all about data, math, analytics or software technology, although all of these elements are important. Successfully using all the data mined and analyzed with powerful software, be it data about customers, markets, industries and competitors, can’t help that much at the end of the day because it all depends on the decisions made by YOU!

By Daniela La Marca