While sales and marketing have always been closely intertwined, the arrival of big data analytics in the enterprise offers new and exciting opportunities for the two disciplines to overlap even further. Sales analytics, in particular, allow team members to have a better idea of the types of strategies that make lead generation and conversion processes more successful. In a sense, sales analytics enable the department to market itself, adjusting inquiries and interactions in line with approaches that have proven more adept at hooking potential clients.
This is an opportunity to offer more responsibilities to members of the sales team, based on analytics prowess and their ability to utilize data-driven marketing strategies in their approach. This can be especially helpful if marketing departments are struggling to make analytics meaningful. While the successful implementation of a big data approach almost mandates radical organizational shifts, a majority of organizations aren’t yet equipped to make sense of customer data.
According to a recent study by IBM, while 94 percent of chief marketing officers in enterprise organizations think that big data will have a make or break impact on their companies’ futures, 82 percent said that their businesses aren’t yet able to take advantage of all of the information they have at their disposal.
“After speaking with CMOs around the world, it became evident that more companies across all industries are striving to integrate their physical and digital presence in order to provide a more integrated, seamless customer experience,” commented John Kennedy, vice president of marketing, Global Business Services, IBM.
Engineering change with sales analytics
One way to start scaling the small mountains of unused data is to incorporate customer response information into sales strategies. Sales analytics can benefit salespeople by offering a meaningful, data-driven evaluation of individual and team performance, which employees can then use to improve their own approach. This process can be extended to incorporate marketing initiatives, which personnel can deploy and see if they improve their own performance. It doesn’t have to be a full-on marketing push, but it makes sense to use predictive analytics, for example, to increase a salesperson’s resources when he or she reaches out to a lead.
By combining forces, employers can help put more value on sales and marketing efforts, which then becomes more data that can be factored into sales and marketing strategies, and so on. In time, a company can develop a robust, data-driven machine in which salespeople are vital cogs. The promise of additional responsibilities – and rewarded successful implementation – can also help organizations “sell” sales analytics to the team, wrote The Wall Street Journal contributor Thomas Davenport.
“Selling has for too long been considered a black art that can’t be over-analyzed without disturbing salespeople,” he wrote. “It’s time for data to shed more light on the function.”