TechBytes with Robin Williamson, VP Engineering, Teralytics

Robin Williamson
VP Engineering at Teralytics

Location data is turning out to be an important datapoint for marketers. We spoke to Robin Williamson, VP, Enginnering, Teralytics to understand the nuances of this emerging technology.

MTS: Tell us about your role at Teralytics and the team you handle?
Robin Williamson: As VP Engineering, I manage some of the top data scientists, software engineers and machine learning experts in the world. Our global team contains PhDs, alumni from some of the biggest tech companies and a number of grads from ETH Zurich, the highest ranked computer science school on a global basis. It’s a pleasure to work with such bright minds on complex problems.

MTS: How does Teralytics empower mobile marketers with end-to-end journey analysis?
Robin: We understand human journeys better than anyone else and our primary focus is to service smart cities, travel and transportation organizations. We help cities decide what infrastructure to build when and where, and we help transport operators allocate resources and operate more efficiently. While mobile marketing platforms are not our focus, our solutions can also open up opportunities for cities and mobility businesses to target specific audiences based on their travel behaviors and demographics. For instance, if ride-sharing companies want to understand their market share of total mobility in a city or region, we can help them. Similarly, if a city wants to understand which venues are most frequented by tourists, we can help them find the answers.

MTS: At Teralytics, how do you distinguish between mobility data and location data? What are the similarities/ differences between the two?
Robin: Location data is the general term that’s used widely across industries. We differentiate between cellular, WiFi and GPS data based on the original data source. Cellular data is derived from mobile networks, WiFi data comes from hotspots and GPS data is received from ad networks, apps, vehicles and other connected devices. Each of these data sources has strengths and brings challenges.

We have identified cell tower signals from telecom operators as the most valuable data for understanding human mobility. It allows us to build solutions tailored to solve a variety of problems. We can see how many people travel from point A to point B by which mode of transportation and how long it takes. Our technology also uses data to observe neighborhood demographics, where people live, where people work and if there are changing patterns. We can understand if people in the area are visiting, commuting, resting or traveling through on their way to another destination. We can even analyze data to understand who is affected by unexpected events, such as natural disasters, train outages or traffic incidents and we reveal how they move before, during and after an event.

MTS: How do you unlock the potential of data on human mobility for B2B commerce?
Robin: Understanding how people move is an essential element for various use cases. Depending on the customer’s needs, real-time and historic data on human mobility can help improve the efficiency of operations or the return on infrastructure investments.

As self-driving cars and the internet of things become a reality, in my view, we’ll need to transform the existing infrastructure and transport systems in our society. Toll road operators, public transit agencies, city governments and car OEMs are all feeling the paradigm shift we’re experiencing. They need to better understand how people move first before we introduce and embrace the complexities of modern mobility services. That’s where we come in: We provide the dynamic information foundation for the future of cities and mobility systems.

MTS: What are the pain points for mobile marketing platforms that are yet to adopt commercial AI technologies?
Robin: While we don’t focus on mobile marketing platforms, the challenges we observe with our customers are probably similar: There is so much information out there that it becomes increasingly harder to differentiate between noise and signal. That’s the case for our customers and I’m sure it’s similarly difficult for marketing businesses. In order for Teralytics to help cities, transportation operators and mobility service providers better understand human journeys, we apply leading edge technology, machine learning and data science to filter out the noise and provide highly valuable intelligence. With this information, we are building the infrastructure, mobility services and public safety capabilities of the future.

MTS: What’s the next frontier for IoT applications within the commercial mobility sector? In such a scenario, how do you see marketers expanding their creative vision to connect to consumers effectively?
Robin: Ride-sharing is taking over and self-driving cars are just around the corner. Connected and automated vehicle fleets will also be a reality soon. These new technologies will have to integrate with old infrastructure including roads, public transportation systems, cities and more.

These technological trends will pose significant challenges to everybody involved and are also an exciting opportunity to use data for social good. We believe that understanding how people move must be the first step in preparing for the future and designing the cities, roads, public transit networks and mobility services of tomorrow and providing the mobility services that people want and need.

MTS: Thanks for chatting with us, Robin.
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