When analytics first gained traction, retailers considered activity involving websites, cookies and links proxies for understanding consumer interest. Analysts interpreted visitor metrics based on these elements to show that a customer displayed purchase intent, a purchase or curiosity.

Today visitor data is as likely sensor-generated through kiosks and devices on a retail floor location as through a website. Thus heralded the birth of location-based analytics solutions that organize dimensions and metrics to reflect these sources.

And that birth is rapidly morphing into nuanced measurement needs, thanks to geospatial technology.

Bending Time and Space

But adopting the physical world into measurement details has analysts seeking better real time associations of time-stamped and location-stamped consumer data. Scaling data to space and time to match real time decision-making analysis has proven a challenge.

Enter SpaceCurve, a 30-employee company is based in Seattle.

Introduced in late 2014, SpaceCurve is a spatial data platform that measures spatial data sourced at IOT-related device such as kiosks and displays. SpaceCurve is touted as “the first platform purpose-built to spatially organize and analyze machine-generated data sources in real-time and at extreme scales.” 

The results provide faster application of operational intelligence from an IoT environment.

Imagine a retailer making immediate decisions based on shopper activity, such as the number of potential customers arriving, their origin to a given area, and the time intervals in which they arrive. Now imagine this based on fusing varied data sources – some captured at a different time and with little context -- and you get a strong sense of the revolution SpaceCurve is looking to lead.

Company Objectives

In a conversation with CMSWire, two SpaceCurve executives — CEO Dane Coyer and Founder/Chief Technology Officer J. Andrew Rogers —discussed the company's goals and development.

With more than 30 years of executive leadership experience, Coyer has worked in information technology system development and executive sales management. He has held positions at IBM, Lockheed Martin, Northrop Grumman and venture-funded startups. 

Rogers pioneered the development of distributed database technologies for real time geospatial systems. He has led development efforts on large-scale analytic and geospatial systems with Google Earth, CBS News and UK Met Office.

In our discussion, Rogers shared how device influence of analytics is a significant departure from examining historical data in a traditional analytics tool.

“When you look at web pages, there are linkages to analyze. The physical world has none,” he noted. This led Rogers to ask, “Why can’t we build an analytics system in the physical world?”

Another concern was volume of data created by devices. “Machines generate data at a higher velocity and volume than what is seen on the Internet,” said Rogers. His experience from working on the backend of Google highlighted how indexing at scale creates unprecedented challenges.

Coyer shared how location-based analytics can surface new measurement concepts, such as the impact of weather or environmental conditions and competitor influence when people arrive to a retailer’s measurement space. 

“Do people or vehicles stop at a competitor on the way to or from my location? The industry has achieved a breakthrough in having many sensors provide a continuous view of what is going on,” Coyer said.

Time Sensitive Data

That continuous stream of information also enhances operational speed. Coyer explained that one partner benefited from “being able to have a model available based on seconds-old information.” 

That means a faster ability to model customer dynamics based on more time-sensitive data across a number of sources. 

Retailers will dispatch personalize offerings rapidly such as offering a deal when physical traffic in the area suddenly drops lower than usual.

Can you imagine better inventory management or new flexibility in customer service because a fusion of streamed data? SpaceCurve promises to create such nuanced interpretations to distinct up-to-the-second information and scale meaningful to fast-paced business needs.   

Current SpaceCurve customers come from a variety of industries influenced by the Internet of Things (IoT).

It’s reasonable to expect more tools dedicated to IoT concerns, but for now, SpaceCurve seems to gotten ahead of the curve for advanced IoT measurement.

Creative Commons Creative Commons Attribution-No Derivative Works 2.0 Generic License  Title image by h.koppdelaney.