ADOTAS – A recent study from the University of California San Diego’s Global Information Industry Center found that businesses, governments and other organizations are processing 10 zettabytes of information a year. If you’re not familiar with the term “zettabytes,” you soon will be. It’s 10 to the 22nd power, or 10 million million gigabytes.
According to the report, the total volume of information is growing at between 30% and 40% a year. The research firm IDC forecasts a similar explosion in information, expecting the global volume of data to increase 29 times over the next 10 years.
Is all this data buoying us up, or burying us under its weight?
Probably both, but more so the former if the data is being efficiently and effectively managed and analyzed. Just as the technology to generate, move and store this data has been steadily advancing, so too have the techniques, tools, and software to help us analyze it.
In its fundamental form, business analytics apply advanced mathematical modeling, simulation and optimization techniques to help sift through vast quantities of information and discover meaningful patterns — fast.
The opportunities for marketing are profound.
These analytics allow marketers to see not only historical information about customer behavior, but also real-time data that can be analyzed to drive instant decisions and to generate predictive models that point the way to optimizing future actions.
Marketing and media mix modeling are not new (but they are getting better and faster). Message modeling is. Measuring the relative return on investment for a particular message, or combination of messages, allows the marketer to optimize the balance between, for example, brand, product and promotional messaging. This is invaluable for telecommunications, automotive and retail advertisers, among others.
Sophisticated analytics allow us to “listen” to the social media, measuring both the intensity and the nature of consumer sentiment in real time.
We can figure out which consumers matter most – without knowing their names or addresses, but by observing patterns of behavior (online and in stores) and creating archetypes. Then we can tailor messaging to these consumers and find them when and where they are most receptive to it, increasing both effectiveness and efficiency. We can avoid costly over-saturation of messaging and unnecessarily incentivizing highly profitable customers who are already loyal to us.
But this isn’t easy. There are two critical caveats for the marketing mix to come together.
First, as with all initiatives dealing with customer information, marketers have to make sure that all protocols related to protecting customer privacy are followed to the letter. That will be of paramount importance for winning consumer acceptance.
Second, and most important, the techniques, tools and software of business analytics make data analysis faster, cheaper and easier to do, but they are only as smart as the people who design and choose how to use them.
At the end of the day, when it comes to the next 20 zettabytes of data, and with apologies to McDonald’s, “I’m diggin’ it.”