Get attribution data with SimulateIDFA – a new iOS 10 Mobile Ad Tracking Solution from Adxmi

With a recent introduction of IDFA (identifier for advertisers on iPhones) in iOS 10, consumers will see less relevant advertising, thus depriving brands of valuable attribution data. IDFA works as the Cookie but even better in iOS system. If it is limited in such closed system, advertisers just get blind of the official data. Many ad tech vendors attempt to find a new ID tracking methods for advertisers in applicable ways.

Adxmi SimulateIDFA

SimulateIDFA, New Way To Identify Devices

As mentioned above, if IDFA is limited, advertisers in iOS are searching for new methods. Hence, to realize goals of the advertisers, methods should equip with the above features.

That’s why Adxmi’s parent company — Youmi Ads is developing SimulateIDFA to help developers, advertisers and DSP platforms to identify devices in iOS and to optimize performance and efficiency of their ads.

Inspired by OpenIDFA, we developed a whole new solution which is more advanced and adaptable in iOS system for identifying devices. Most importantly, SimulateIDFA would be a new method abiding Apple developer’s policy and respecting user’s privacy.

Features of SimulateIDFA include:

  • Easy to operate

Data embedded with the algorithm in App or SDK of SimulateIDFA would be the same as IDFA.The principle of generating SimulateIDFA is similar to OpenIDFA. Consisting of 32bits value, MD5 value would be divided into two parts. The former part of the value only changes when system upgrades and it contains information of system, devices, storage, core services and files updates,etc.

The latter part consists of adaptable values which only change when device restarts. It contains information of system activation time, country, language and device’s name.

  • Low repetition rate, high efficiency & anti-fraud

For generation algorithm, repetition rate of SimulateIDFA is obviously lower than OpenIDFA’s. In certain conditions, the rate of repetition is relatively high because OpenIDFA algorithm involves the day time which leads to the change of MD5 value.

SimulateIDFA doesn’t have this problem, instead it has good performance in long-term tracking because value in SimulateIDFA divides into two parts. The first half part of the 16 bits value changes only when system upgrades. The second part of the value changes according to user’s activity, such as restarting the phone, modifying the device name as well as modifying the phone’s native language.

For anti-fraud, SimulateIDFA would equip with advanced value sources and algorithm, which makes cheating spend more time and money, failing to modify value on a large scale.

  • Recognized by the industry

Currently, many app advertisers are paying attention to SimulateIDFA. As a new solution for iOS advertisers, this technology is extracted and improved from our platform’s daily anti-fraud techniques. Owing to its premier testing and launching in Github granted by MIT, SimulateIDFA has refined its adaptability.

The development of SimulateIDFA enhances the credibility for the solutions, making the data more transparent. Also, we hope to create a more open mind among developers, building a new standard for China’s mobile advertising market.

“We are not assuming that SimulateIDFA would be accepted by the industry in the short term. What we do is to open a window for the rather closed industry in China, innovating and redefining technology for mobile advertising.” Says our technology team, “The open source project is  accepted by advertisers, giving a chance to solve the problem of user tracking and data standard.”

Apple may change its policy. The open source SimulateIDFA would also keep on track, making adjustment at the first time. From our point of view, data of devices from IDFA is the fundamental for mobile advertising. More emphasis should be laid on data analysis, mobile anti-fraud and ads optimization.

SimulateIDFA has been tested in some of our cases.

See more about SimulateIDFA