There’s a reason we call today’s plethora of information “big data.” With almost every action and transaction we engage in leaving a digital trail,...

There’s a reason we call today’s plethora of information “big data.” With almost every action and transaction we engage in leaving a digital trail, we’re generating an unprecedented amount of data – 2.5 quintillion bytes’ worth – every day.

If that doesn’t compute, think about it this way: a full 90 percent of the data out there today has been created in just the past two years.

While the amount of information available today is mind-bogglingly big, insights from that information are available to more than just big corporations with global IT resources. Thanks especially to ever-more-affordable cloud computing, small- and medium-sized companies can also mine mounds of data for new sources of business intelligence.

IBM Logo“All companies have big data whether they realize it or not,” noted Stefan Groschupf, CEO of a data analytics company, in Forbes.

Small businesses in particular are “starving for the insights,” added another analytics exec.

So where does a small company’s big data lie? One key locale is online: any business with a website automatically generates megabytes and gigabytes of information: who’s visiting the site, where they’re coming from, how long they stay, which pages they browse. And all this is before even a single visitor sends you an email, downloads a brochure or orders a product from your catalog.

As soon as a browser becomes a customer – online or off – you gather even more valuable data that can be analyzed to fine-tune your marketing and business strategies. What time do most people tend to buy? Which price points are most popular? How many first-time customers become repeat buyers? How frequently do they buy?

A farm-to-table restaurant near Boston, for example, uses an online service to analyze payment data. This helps it identify when to send customers personalized messages ahead of special occasions, or when a favorite food item becomes available.

“Say it’s one of our best customers and they come every Saturday night and they love the salmon dish,” Farmstead Table owner Chad Burns tells Reuters. “If I get salmon in, I can send them a note and let them know I have their favorite dish.”

And then there’s the additional data available to small- and medium-sized businesses through their social media activities. In this Forbes article, data scientist Seshu Edala gives the example of a bakery that one day notices a major spike in traffic to its web page for strawberry shortcake. Checking the Facebook insights report, the bakery owner traces the traffic jump to a customer post that says, “Love the strawberry shortcake and the tiramisu but the tiramisu is pricey.” Using those insights, the owner can then do more to promote the bakery’s shortcake online, as well as offer a coupon for a discounted price on tiramisu.

Consolidating data from multiple sources can help a business generate even better insights.

For instance, the Cincinnati Zoo once used four separate point-of-sale systems to handle admissions, membership, retail sales and food sales. By bringing these onto a single platform with the help of IBM and BrightStar Partners, and then analyzing the resulting data, it was able to identify a number of ways to increase sales and cut expenses. One strategy – targeting potential visitors in specific zip codes – led to a 4.2-percent increase in ticket sales. Another change – optimizing the choice of available food items and planning better for peak purchase times – generated even greater revenues through a 25-percent hike in food sales.

“(W)e were able to increase our in-park spending by as much as 25 percent by utilizing 360 degree customer views,” said John Lucas, the zoo’s director of park operations. “It was instant payback.”

This post was written as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are my own and don’t necessarily represent IBM’s positions, strategies or opinions.