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Mining Big Data For Sales Leads

Tech Leads Online will scour the Internet and parse the data to find potential clients for your sales organizations.

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Email blasts are a scattershot approach to online marketing, particularly ones fired out randomly and haphazardly to a mass audience. If you don't know who to target, your pitch might be received as enthusiastically as a Nigerian email scam.

So what's a sales organization to do? One option is to aggregate and analyze all the publicly available data you can find online, and use the information to aim your marketing message at companies and people most likely to be receptive.

In fact, this data-crunching approach is favored by Tech Leads Online (TLO), a competitive intelligence software-as-a-service (SaaS) platform for sales and marketing pros. TLO tracks more than 5,000 technology products and 200,000 companies, with 20,000 to 30,000 new companies added monthly, the company says.

[ What is the key question when it comes to big data? Read Big Data's Big Question: What To Keep. ]

Armed with TLO's data, sales organizations find companies that use their competitors' products, and pitch directly to them.

"We've set up a data aggregation process where we pull in data from all public sources. We utilize social listening techniques to aggregate the information, and then process the data utilizing machine learning technology," Oliver Deng, TechLeads Online chief strategy officer, said in an interview.

"The issue that most companies face is not just the quantity of data, but really the type of data they have in order to figure out whom to target -- what types of companies and people," he added.

Deng wouldn't name the sites that TLO mines for data, but said they include "any public site where you don't have to log into."

The company is selective, however. "We do research to find out how much relevant data we can find on the site. If it's publicly available, we will send out scrapers to aggregate the information," he noted. Deng said TLO's "secret sauce" is it data processing engine. The company guarantees a 90% accuracy rate for its information. "The processing piece is the neat thing about it," he noted. "It's highly accurate, and we fine-tune it."

Deng said that competing sales-lead services often take an old-school, phone-based approach to gathering data.

"They have a very manual process to find out information," he said. "They call these companies and … build relationships. They check in with them."

TLO has competitive intelligence data on 250,000 companies, Deng said. Most of the company's customers are technology firms hoping to target potential customers with greater efficiency.

"The example I give is of a company sending out a blast of 10,000 emails," he said. "Are they being sent to the right people?"

In many cases, they aren't.

"I just got an email the other day from Symantec, pitching me their cloud-based antivirus solution," Deng recalled. "I'm already one of their customers. So the data set they're using obviously is not vetted out."

Online data can provide other, less obvious sales leads too, provided you know where to look.

Deng said that a big tech firm asked TLO to find all the companies running Oracle databases on servers with Intel Itanium processors. The client was trying to benefit from the contentious HP-Oracle lawsuit, a result of Oracle's 2011 announcement that it would no longer port its enterprise software to run on the Itanium chip, which is used almost entirely by HP.

"Servers with Itanium chips have specific model numbers," said Deng. By checking its archive data for those model numbers, TLO was able to extract the necessary server information, combined with Oracle database data, to come up with a list of companies for its client to target.

"There's so much data," said Deng. "It's amazing, all the different sources where you can find data."

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