Networked Insights, a data mining and analytics company, has added new functionalities to its platform.
The Networked Insights program can now mine third-party social networks, such as MySpace and company branded portals, for consumer data. Users can see information on customer behavior, sentiments and engagement in real time.
Facebook is currently off-limits to Networked Insights, but Neely hopes that an arrangement can be made with the social networking giant before long.
“We thought it would be cool to get customers interacting with each other and learn from that,” said Daniel Neely, founder and CEO of Networked Insights. “To combine that with transactional data would be the holy grail, so the next evolution is rich insights based on engagement, giving an indicator of where you should focus your efforts as a company.”
Neely went on to say that the system helps direct marketers because they can use it to figure out how to best leverage their mailing lists. Networked Insights can break out data by gender, age group and geographical region as well as discussion topics and interests.
“In the past, direct marketers have looked at historic data — how much did you buy, what did you pay — and using those as indicators to try to predict the future,” Neely said. “What they recognized was great in an instance where people’s attention spans were much longer than they are today, but today people change from brand to brand to brand in a week, depending on who is reaching their needs and who is getting them what they want. Direct marketers and their conventional wisdom around CRM are struggling because systems are not built to do that.”
The company has redesigned its platform to make the interface — which breaks down data into five areas of focus — simpler to read. The focus areas are customer needs, content, competition, brand and product/service. Networked Insights has also started giving community members “influence metrics” based on engagement.
“As a company, you should let customers tell you where you should focus, rather than try to figure it out based on transaction data from the past,” Neely pointed out. “Our system allows you to be predictive rather than reactive.”
