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The Trap of Big Data for Driving Enterprise Sales

Giles House photoIn this special guest feature, Giles House, CMO of CallidusCloud, discusses how Big Data has its place within an enterprise sales organization and how the technology can provide the sales team with some surprising insights. Giles is an experienced marketing executive with a proven track record of successfully marketing and selling business software and technology for more than a decade. At CallidusCloud, he is responsible for the company’s global marketing activities, communications, brand and sales enablement programs. As a recognized thought leader, Giles regularly speaks on sales and marketing automation and alignment.

It’s difficult to read a “best practices” management-level article without coming across mentions of big data. Promised to have a transformative effect on business, big data is a hot topic for marketers, IT, finance, and sales. For sales at the enterprise level, big data can be an important tool, but it is not a cure-all. Buyers in large sales deals want to have a person they can work with to answer questions about budgets, timelines, and expectation. They want to establish some level of rapport and trust with the vendor because a considerable amount of money is on the line.

The benefit of big data within these types of sales comes with the added context that it can provide to the sales cycle. The data alone can’t set up and close deals – it stills requires interpretation, application to the sales process and a salesperson’s personal touch. Big data does have its place within sales, however, and can provide the sales team with some surprising insights:

  • The most valuable prospects and most lucrative potential repeat customers can be best identified through data analysis. Then the sales team can also adjust its sales methods based on data. For example, data may reveal that the biggest sales contracts in a certain area are garnered after first contact is made over the phone, not through email.
  • Big data is used as the basis for predictive analytics, which uses data to accurately estimate what will occur at a future date. Data can help predict customer’s behaviors, broader market trends, and other useful information. It’s important to note that predictive analytics is always based on known information; big data simply presents it in a clearer format.
  • Data can be used to look at how time is invested by sales staff and how that time relates to actual sales revenue. Armed with data, managers can, for example, provide underperforming sales staff with details on their weaknesses, which allows them to provide more relevant and helpful coaching.
  • The ROI of certain sales-focused investments can be better judged. Perhaps the enterprise invested a significant sum in a new business line that is not selling as expected. Big data can help uncover the underlying reasons for slow performance, whether it’s a process, the product offering itself, or a problem with the sales staff. Improving a few key processes that boost sales by a few percentage points can be crucial for large enterprises.

Despite these benefits, big data cannot replace intuition within the sales cycle. It should be used to provide context and to uncover inefficiencies. As has always been the case, the winning formula combines sales insight with sales instinct. Although today we have more effective ways at uncovering that insight, and a greater potential to use it, we still must have the right sales talent in place and the right processes to enable them to turn data into dollars.

 

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