Big Data Tackles Longtime Salesperson HeadachesOne future direction for big data analytics: Help sales pros make productive use of the endless flood of information about prospects.
The grinning used car salesman in the green plaid sport coat may not have much use for big data streams, algorithms, and predictive analytics, but most salespeople would likely benefit from sophisticated data-analysis tools.
The online survey, "CSO Insights 2012 Impact of Data Access on Sales Performance Report: Why Big Data Should Be a Big Deal for Sales," found that nearly 90% of salespeople feel they miss opportunities simply because they can't keep up with an endless stream of information on sales prospects. The survey, conducted by CSO Insights for Lattice Engines, a sales intelligence software developer, polled 218 CEOs, CSOs, sales executives, and managers.
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Sales reps search as many as 15 external and internal data sources--including Facebook, LinkedIn, Twitter, search engines, and in-house CRM systems--for information on customers and prospects. But more than half of companies surveyed lack the technology capable of bringing this large amount of unstructured data to their reps, who must find it on their own, the survey found.
In fact, nearly a quarter of a salesperson's time is spent doing research.
[ Learn other ways sales and marketing organizations can put big data insights to use. See 5 Ways To Benefit From Big Data. ]
"There's lot of noise out there, and because there's so much more data, salespeople feel compelled to go through it all," Lattice Engines' chief marketing officer Brian Kardon told InformationWeek in an interview. "We don't know how relevant it is, but there's more and more information to go through. And probably machines--computers--ought to go through it, and not a human being."
Lattice Engines sells a big data analytics platform, SalesPrism, that's used by large sales forces in major corporations, including ADP, Dell, and HP.
"Instead of a human being looking at hundreds of kinds of information, we write computer algorithms that look through it all and--in real time--tell a salesperson what to do, and what to say on the phone," Kardon said.
In short, it's a big data solution to an increasingly common sales problem.
"Big data has been applied to a lot of areas--weather, discovery of diseases--but it really hasn't been applied in a systematic way to sales yet. We think that is the next wave," said Kardon.
Lattice Engines has few direct competitors in the sales intelligence software market, he said.
"Sometimes big companies have PhDs do statistical analyses of their data. We don't really compete with them," said Kardon. "And there are services like Google Alerts that alert salespeople to external events that are happening."
Sales intelligence systems can crawl through websites to ferret out important data. "Things like a prospect just hired a new CFO or CIO, announced the opening of a new office in Beijing, or just got a huge government contract," Kardon said.
They scan useful in-house information too.
"Most salespeople don't have access to purchase histories. But if you know that a given prospect has bought your product before, but only in December, then you (learn not) to call them in February," said Kardon.
A customer's past purchase history is often the most valuable piece of information. But few sales organizations allow their salespeople to access that data. But if you know what a customer has bought before, you can apply predictive analytics to understand what he or she might buy next, Kardon said.
Big data can help sales organizations operate more efficiently, much in the same way that Wall Street has benefitted from sophisticated data analysis tools.
"It's kind of like a trading room floor," said Kardon. "How does the price of oil in Kuwait affect the price of something here? How do weather conditions change commodities? The people who are doing really well on Wall Street are the ones who write computer programs that look at all this information."
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