Juniper Networks subsidiary Mist Systems announced its entrance into the data analytics game today with Mist Premium Analytics.

The service is designed with two goals in mind: improving network visibility for a more proactive stature and providing insights into customer traffic and behavior by analyzing location data collected by Mist access points.

The two features appeal to different groups — companies that want to better understand their network, and organizations interested in how people think and move, Christian Gilby, Mist’s director of product marketing, told SDxCentral in an interview.

While improved network visibility has broad appeal among enterprise customers, Mist's retail customers are more excited about business insights, said Gilby.

"I would say the engagement analytics is definitely appealing more to our retail base as well as folks in logistics or warehousing," he said.

Mist access points, which track users via WiFi and Bluetooth, can help businesses understand how customers or employees move through a venue or use office space, according to Gilby.

That data can also help businesses better allocate sales associates based on historical data, streamline workflows in a manufacturing plant, or determine the effectiveness of retail marketing campaigns.

The service also attempts to solve one of the biggest challenges facing network visibility: correlating data from multiple vendors.

With heterogeneous networks, "there's data, but not really a way to pull it and analyze it,” Gilby explained, adding that few vendors can analyze data from multiple parties.

AIOps vendor Nyansa, which was acquired by VMware earlier this year, is one of the few vendors to claim support for heterogeneous networks.

While many jumping into the network performance and monitoring space are quick to tout their use of machine learning (ML) or artificial intelligence (AI), Gilby said Mist Premium Analytics isn’t an AIOps platform, at least not yet.

"I think there is a view that in the future we would look to integrate it with Marvis, our AI engine," he said. "I want to be real about what it is. We aren't leveraging AI in it today, that would be a focus for the future."

For now, the service is focused primarily on data analytics, Gilby said.