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PROGRAMMATIC ADVERTISINGSTREAMING & CTV
We cross check 100% of Adoppler’s device traffic, allowing them to do what they do best.
2017
Founded
1B
Requests p/w
100%
Traffic cross-checked by DeviceAtlas
Background
Adoppler is a full stack advertising technology platform offering OTT and Video monetization solutions. Adoppler’s technology platform incorporates a built-in SSP, Video Ad Exchange and DSP for programmatic and direct advertising campaigns.
Adoppler’s programmatic advertising platform enables its clients to establish transparent advertising and digital media buying with ad inventory suppliers in a single solution.
Adoppler’s partners include streaming media service providers, video publishers, vMVPDs, media agencies, OTT and advertising technology vendors and brands.
Founded in 2017 in Minsk, Adoppler now has a presence in the United States, Belarus, and Ukraine.
Since its founding, Adoppler relied on open source libraries to deliver in-house device detection. And in 2021, with the aim of providing additional value to their partners, Adoppler sought to overcome their device intelligence challenges.
Industry:
Marketing and Advertising
Specialties:
OTT monetization,
video ad exchange,
programmatic
demand mediation
The Challenge
The OTT ecosystem is relatively new and is developing rapidly. This, combined with the continued growth in OTT consumption and the increasingly fragmented CTV device landscape, has led to many challenges.
These challenges are caused, to a large extent, by User-Agent string issues. Common issues include the absence of identifiers, encoding issues, model collisions and the inclusion of irrelevant information / tokens in User-Agent strings.
These issues, and more, can negatively impact targeting, triggering and rendering ad creative, analytics and reporting. Ultimately, they can lead to reduced buyer and publisher confidence and have a negative impact on monetization.
Like many operators in the OTT ecosystem, Adoppler faced these challenges. Their in-house solution, built on open source libraries, did not deliver sufficient accuracy or device insights. Adoppler noted that in many cases these libraries determined devices incorrectly or did not provide any information on CTV devices at all.
To deliver additional value to their partners, by taking their device intelligence to the next level, Adoppler sought an alternative solution.
"Adoppler and our partners have experienced significant improvements since implementing DeviceAtlas."
Anton Tkachuk, Product Manager, Adoppler
The Solution
After exploring several device detection and intelligence vendors, Adoppler chose to partner with DeviceAtlas.
DeviceAtlas supports every step in the chain, from publishers (Netflix, CBS Interactive), through monetization (Xandr, SpotX, The Trade Desk) to analytics (Adobe, Conviva). DeviceAtlas help a range of top players in the OTT ecosystem overcome challenges and leverage the opportunities enabled by real-time device intelligence.
DeviceAtlas delivered a locally deployed device intelligence solution that enables lightning-fast lookups with minimal server footprint. Through its quick and easy to implement, high-performance API, Adoppler now has a market leading, accurate, futureproofed device intelligence solution.
Results
“DeviceAtlas has helped us deliver even more value to our partners.” Anton Tkachuk, Product Manager, Adoppler.
Adoppler’s key goal was to provide additional value to their partners. With DeviceAtlas, Adoppler has significantly improved their device targeting capabilities and now delivers enhanced monetization opportunities.
Adoppler has the peace of mind that they offer market leading device intelligence that their partners can leverage.
Since implementing DeviceAtlas, Adoppler has achieved stellar performance improvements. Using DeviceAtlas, Adoppler immediately realized a 110% improvement in the CTV device make (vendor) and model identification, and a massive 480% improvement in identifying operating systems.
Additionally, Adoppler can now focus more on their core business as maintenance of their in-house solution is not required.
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