Pricing products effectively is essential to maximizing profit. But in order to do this, a salesperson must give credence to more than just price. He must look at the entire sales cycle, paying mind to each customer’s specific needs and predilections. Yet for years, salespeople treated this function as an art, rather than a science. It was based more on feel than fact, and chances are, they left money on the table as a result. This is the old way of thinking in today’s hyper-competitive markets. The world is changing into one where sales will no longer be conducted based on the mood, desire or preference of the salesperson, but rather on data.
Enter Big Data
What separates Big Data from plain old data? While the exact definition of Big Data is tenuous, a useful working definition is known as the “3 Vs,” which was first promulgated by Gartner analyst, Doug Lacy. Variety is the first V, which refers to the diversity of the data; Volume is the amount of data; and Velocity is the speed at which the data can be processed. While this evolution and growth of unstructured data presents every B2B enterprise with a set of challenges, it also holds a set of real opportunities. It is the secret sauce that is transforming sales into a science.
If leveraged properly, Big Data can profoundly bolster the sales function. Imagine that you could pinpoint the precise prices to quote on a deal for each and every prospect. What if you could track all of your salespeople to understand how many times they made contact with a prospect before a sale closed, and then adjust the sales model to avoid protracted deals? Harnessing the power of Big Data makes this, and so much more, not only possible — but inevitable.
Is Big Data a silver bullet?
Though ensuring successful sales 100 percent of the time may be a stretch, efficiently leveraging a business’ data does have the potential to predict behavior before you ever come into contact with the customer. That knowledge has the ability to turn the entire sales model on its ear.
Big Data is a rapidly evolving space, but most applications still require data scientists or analysts to mine the data, filter out the noise and decipher meaning. However, intelligent software is emerging that automatically analyzes data using predictive analytics-based algorithms, which provides business users with actionable guidance in ways to improve their business.
These kinds of Big Data applications can provide sales leaders with concrete, algorithmic data that indicates customer behavior and purchasing patterns and enables sales people to prioritize prospects.
Tune in to my next blog post in which we explore how new applications of Big Data are transforming the manufacturing industry.
Neil Lustig is CEO of Vendavo. He is an accomplished executive with over 25 years of experience in the IT industry. After joining Vendavo in 2007, he led the global commercial team for three years prior to assuming his current role. Before Vendavo, Neil successfully directed Ariba’s North American field operations for two and a half years. Follow him on Twitter @vendavo.