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Google recently announced the launch of their Privacy Sandbox intending to improve data protection for advertising on smartphones. Many advertisers see this as a major threat, fearing a loss of addressable audiences on Android smartphones. We briefly summarise Google's announcement and explain what we think it means for the industry.

What You Need to Know About Google’s Privacy Sandbox

7 March 2022, Monday | By: Tom Laband
5 min read

About Tom Laband

Tom Laband is Co-Founder and CEO at Adsquare with over 15 years of industry experience. Tom is a mobile specialist with a fierce interest in data.

Google recently announced the launch of their Privacy Sandbox intending to improve data protection for advertising on smartphones. Many advertisers see this as a major threat, fearing a loss of addressable audiences on Android smartphones. We briefly summarise Google’s announcement and explain what we think it means for the industry. 

What is Google’s Privacy Sandbox?

With the so-called “Privacy Sandbox for Android”, Google says it wants to develop its own advertising systems that are both effective and privacy-friendly. What does that really mean? Google wants to develop advertising solutions that do not require the current Android Advertising ID (AAID) for data collection across different apps and is currently looking at technologies that can reduce the likelihood of unnoticed data collection. First-party data will continue to be collected and used for targeted advertising in the future. The developments are more about ending the opaque practices like device fingerprinting outside Google’s services. The new system should do without cross-party identifiers and the exchange of user data is said to be limited. We’re looking at a multi-year initiative that just kicked off. Google intends to continue to promote the existing functions for advertisers for at least two more years.

Tailwinds for Universal Identifiers

Google’s announcement is a boost to the various initiatives for Universal IDs, first and foremost the Unified ID 2.0 launched by The Trade Desk or – in cooperation with Liveramp – the EUID. These types of Next Generation IDs are a new, more effective way to connect across digital media on the open internet to receive the media’s free content in exchange for relevant advertising. Adsquare is pleased to support initiatives like these and officially joined Unified ID 2.0 in September 2021. After all, our technology allows us to enrich every identifier passed from the bidding site as part of a bid request with meaningful data to achieve the best campaign results. These initiatives are currently being tested and might take some time before a new standard is established. However, there are already alternatives to audience targeting with contextual targeting products.

Sharpening contextual signalling

It’s a reality that audience targeting based on cross-party identifiers such as cookies and MAIDs is going to play less of a role in the future. In contrast, contextual advertising will become more important as it solves both privacy and identity challenges. Adsquare offers a contextual targeting product that works without cross-party identifiers. But instead of relying on the context of the publisher content, advertisers are relying on the context of the location where users are at the time of ad delivery. In its simplest form, this could be selecting a radius around certain Points Of Interests (POI). For example, a burger chain could run a drive-to-store campaign by advertising on billboards near their restaurants.

Proximity targeting in the world of programmatic advertising is a little more complex. A number of publishers collect data about users’ latitudes and longitudes as part of their function; weather, mapping and dating apps, for example, all require location data. Likewise the owners of out-of-home inventory know the exact locations of their digital screens. The geo-coordinates are passed from Supply Side Platforms (SSP) to Demand Side Platforms (DSP) as part of a bid request. Third-party data specialists such as Adsquare can enrich this location data in real time with data about the context of the surrounding space.

From the advertiser’s point of view, this type of geo-contextual targeting could not be easier to activate. Before bidding, the advertiser can choose from thousands of spatial data sets in the Adsquare platform and activate them in the desired DSP before the campaign starts. The spatial data that can be used for proximity targeting campaigns include the following: places data, household data or purchase data.  

What’s more, data can be gathered in a dynamic way to provide intelligence on the context of a location over time. For instance, weather data can provide an hour by hour snapshot of what weather conditions will be like over the course of a day, allowing advertisers to choose frames and latitudes/longitudes on a granular basis. Where the latest iteration of geo-contextual advertising really gets exciting is when first-party data is mapped to predictive contextual models. Hereby, telcos will play a big role in the future as they are able to connect their first-party data to country specific geometries (or OOH locations) and estimate movement patterns of a desired audience. Mind you, aggregated, anonymised, and therefore fully privacy-compliant. 

Modelling footfall attribution

If you’re running a campaign you need to know exactly what impact your advertising is having by attributing conversion data such as store visits to your campaign. Today’s store-visit attribution solutions calculate uplifts by comparing the exposed user group against a control group of users that hasn’t seen the corresponding ad. Even though the calculations are based on a smaller movement data panel with statistical relevance, the underlying movement data is connected to Mobile Advertising IDs. With potentially fewer IDs available for the free internet, independent measurement partners have to adapt and find new ways in attributing store visitations to ad campaigns. In the future, companies will model attribution logics where anonymous and aggregated data helps identify the key factors that drive foot traffic. Such systems can learn from more meaningful and privacy-compliant data, e.g. from telcos – leading to better estimates and equally meaningful results.

Conclusion

Adsquare is committed to champion an open, neutral and healthy ecosystem. The Privacy Sandbox for Android is a step towards improving data protection, while ensuring that developers and businesses can continue to thrive on mobile platforms. Data-driven advertising on Android will continue to exist, even though we will most likely have to familiarise ourselves with new technologies. We look forward to accompanying you through this time of change – as we did the past 10 years. 

About Tom Laband

Tom Laband is Co-Founder and CEO at Adsquare with over 15 years of industry experience. Tom is a mobile specialist with a fierce interest in data.

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