Dragonfly: Technology Overview
Dragonfly aggregates and synthesizes data from a combination of mobile device identification techniques. For in-app advertising, it uses Apple’s Identifier for Advertisers (IDFA) and Android’s Advertiser ID. The process for mobile web advertising is more complicated. It uses third-party cookies when possible, in combination with the user’s mobile web browser cache.
Both of these techniques are useful, but not sufficient for many use cases. To overcome this challenge, Dragonfly additionally relies on the unique attributes of each HTTP request that comes in. Examples of data points include the user’s IP address, browser type, language settings, and much more. None of these elements are unique on their own, but the aggregation of everything taken together creates a unique device identifier. While cookies are 100% accurate, our testing reveals that Dragonfly’s unique device identifier is 94% accurate without relying on cookie data. This high level of accuracy in a cookie-less environment is a central benefit of using Dragonfly technology.
Simply place the Yieldmo conversion script tag onto any page, inside a container or into any tag management solution, and you’re ready to attribute actions back to Yieldmo ads. It’s as simple as typical integrations on desktop.
Core benefits of Dragonfly
Because you can measure the effectiveness of one ad over another, your team can now see where they are getting the most value for their dollars and adjust bids accordingly.
All the conversion data from Dragonfly feeds directly back into Yieldmo’s powerful optimization engine, allowing Yieldmo to further optimize your ads by ad format, publisher, and specific placement on the page.
Ad format flights.
Using device identification technology, Dragonfly allows you to serve ad format flights that bring your consumers progressively down the purchase funnel.
You can use Dragonfly to accurately segment users that have bought or almost bought your products. This is valuable information for both remarketing and upselling, as mobile consumers can now be grouped into segments based on past purchase behavior.