(Left) Rob Aksman
Chief Strategy Officer at BrightLine
(Right) Lawrence Chan
SVP of Innovation & Strategic Partnerships at Cuebiq

Over a course of the last eighteen months, the location data technology has evolved significantly. Marketers have a keen eye on how the world uses location data to amplify Mobile Marketing reach and real-time analytics. We spoke to Brightline’s Rob Aksman and Cuebiq’s Lawrence Chan to understand how Location Data could be used to improve the customer journeys.

Tell us about your roles at BrightLine and Cuebiq respectively and the teams and technologies that you handle.

Aksman: I am the Chief Strategy Officer, guiding the product and platform strategy for BrightLine’s OTT ad offerings.

Chan: I lead the Strategic and Innovation Partnerships team at Cuebiq, focused on working with partner platforms, specifically digital, mobile, OOH, and TV, to leverage location intelligence to drive business and enhance their sales arsenal.

What is the state of Location Data in 2018?

Chan: As the industry moves beyond AdTech into MarTech, the old emphasis on proximity marketing is being replaced by more accurate and precise historical insights. Legacy industries such as OOH, TV, real estate, and finance are integrating location intelligence into their marketing stack. There is also heavy scrutiny on data collection, methodology, and privacy, which is pushing marketers to consider their partnerships more carefully.

What are the core tenets of your partnership?

Chan: With the growing spend in OTT advertising, being able to measure the impact of advertising on offline behavior is essential. Measuring campaigns using real-world performance, rather than just view or click-through metrics, helps prove the efficacy of the format.

Integrating our data and insights into BrightLine enables their clients to see all of their campaign metrics, including footfall insights, on a single platform to measure multiple OTT partners using one unified and proven methodology.

How should businesses unlock the value of their Location Data?

Chan: Through location intelligence, marketers can map, target, and measure offline consumer behaviors. They can understand consumer and competitor mobility patterns through location analytics, conduct real-time campaign optimization and footfall attribution, and identify geo-behavioral audiences for targeting. This will enable them to truly unlock the value of their location data and gain an unprecedented vision into the offline consumer journey.

How is the Data Management ecosystem evolving around OTT and cross-screen advertising technologies?

Aksman: As TV viewing migrates toward connected TV streaming, the capabilities around targeting and ad formats are taking a massive leap forward. Digital delivery to connected TVs means accelerated evolution in how data can be used to plan and buy audiences. The increased sophistication means a buyer can identify, find, and buy on a one-to-one basis the specific audience segmentations in their target set, be it auto intenders, yogurt purchasers, etc.

How does your technology enable companies to analyze and manage consumer experiences with the addition of location data?

Aksman: Our partnership with Cuebiq brings accurate footfall attribution capabilities to TV. Advertisers can now measure the true impact an OTT TV ad has on a viewer’s actions, in this case visiting a particular store, dealership, or QSR. Advertisers can now better quantify ROI, and more importantly, optimize their creative and ad buys based on this extra level of attribution.

What made Cuebiq a go-to partner for your system?

Aksman: Cuebiq is a leader in footfall attribution and location services, and we were particularly impressed by their significant mobile footprint of device level, opt-in, location data.

How can Location Data be used to improve the customer journey?

Chan: Location data helps brands better understand the behavioral patterns and real-world visitation, so they can tailor their marketing strategies to better serve consumers at each touchpoint in their journey. For example, brands can use location intelligence to identify customers throughout their shopping journey based on their offline behaviors, visitation patterns, and brand preferences to deliver timely, creative and efficient messaging that resonates with them.

How do you see trends in Data Management influencing the development and adoption of ad platforms further?

Aksman: Any time an advertiser can optimize buys based on accurate attribution data, it’s a good thing for the platform, provided the platform delivers on its promise of superior ad effectiveness. True attribution data will help weed out the ineffective from effective, so agencies know where to place their bets.

Chan: Data Management through both first and second-party data will create more tailored opportunities for brands and agencies to engage. On one hand, the adoption of programmatic has allowed for scaled ad buys with many levers to pull. On the other hand, brands are also being smarter with data. Data Management is key in tailoring that data for effective activation and platforms will need to build turnkey solutions to deliver that.

Tell us more about location data and how these could improve customer-brand interactions at an omnichannel level.

Chan: Location data enables brands to understand consumer behaviors in the offline world, providing the insights to create a better experience for consumers across all channels. Specifically, location analytics can provide detailed information about the broader visitation habits of a brand’s own consumers, such as where else they like to shop, which the brand can use to create more refined messaging. Brands can use these insights to customize the experience across different channels by understanding attribution insights as well as visitation patterns like dwell time and frequency, which can also be used to improve the in-store experience.

What are your predictions on Data-as-a-Service for 2018-2020?

Chan: I think there will be lots of consolidation in the space. Second-party services will augment first-party data. I predict there will be more refined metrics around conversions, AI-driven optimization around unique data sets, and front-end UIs to manage DaaS. Finally, I think walled gardens will open up to data services, similar to how they opened up to third-party targeting.

Thanks for chatting with us, Rob and Lawrence!

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