Commentary
Location Weekly: Using Location Data to Track Covid-19
In this episode of Location Weekly, the Location-Based Marketing Association covers Turkish firm Elektral developing vending machine for masks, wipes, and disinfectants; UNL raising $2M for smart address system; Wuhan bringing its famous Cherry Blossoms online; and Israeli startup Noveto bringing “smart audio bubbles” to digital signage. The episode also features a special discussion on using location data to track the virus.
Location Leaders Step Up to the Plate
During the Covid-19 outbreak, we’re seeing tech companies step up to the plate in a mixture of altruistic and opportunistic moves. That’s everything from Comcast removing data caps to Amazon removing its paywall for streaming kids shows. But what about local specifically? Again, that’s where businesses are getting hit most.
We’ve seen moves in the local space over the past week from Facebook, Yelp, and Foursquare. Though there are several others, we’ll drill down on this representative sample. We’ll also give a shoutout to Google for its work to free up human and compute resources for local listings updates, covered Monday by Damian Rollison.
Beyond the Data Label: The Next Phase of Data Assessment
This past summer, the IAB Tech Lab launched a much-needed transparency initiative in the form of its Data Transparency Standard, establishing baseline statistics on the objective attributes of a given data segment, such as refresh cadence, ID types, and segmentation criteria. The Data Label should be a big relief to data buyers, including agencies and advertisers, that are trying to wrap their heads around audiences, but it’s still only the starting point when it comes to assessing digital audiences.
For as much as the Data Label injects transparency into audience construction, it only addresses objective attributes, and not the qualitative aspects of the data segment. To get the most value out of their data investments, advertisers and agencies need to go further and develop their own standards for evaluating data, especially when it comes to quality.
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