How Privacy Computing Enables Cross‑Domain Ad Tracking and Asset Analysis

The 2023 Big Data “Galaxy” case competition highlighted Alibaba Mama and Jiahe Tech’s privacy‑computing based cross‑domain advertising tracking and whole‑domain asset analysis as an outstanding example, detailing the Secure Data Hub platform, its use of multi‑party secure computation, federated learning, differential privacy, and the resulting improvements in data flow, compliance, and marketing efficiency.

Alimama Tech
Alimama Tech
Alimama Tech
How Privacy Computing Enables Cross‑Domain Ad Tracking and Asset Analysis

Background : On December 6, the China Academy of Information and Communications Technology and the CCSA TC601 Big Data “Galaxy” case collection announced its winners. The project “Privacy‑Computing Based Cross‑Domain Advertising Tracking and Whole‑Domain Asset Analysis” by Alibaba Mama in partnership with Jiahe Technology was selected as an outstanding case in the Data Element Circulation direction.

Problem Statement : In the advertising ecosystem, data security and user privacy permeate the entire ad delivery chain, creating a critical need for safe, compliant data usage while preserving the core operations of online advertising business models.

Solution Platform : The Alibaba Mama Marketing Privacy Computing Platform SDH (Secure Data Hub) is a Data Clean Room product that serves ad engines, advertisers, third‑party DSP/DMPs, and other partners. It enables data fusion, privacy‑preserving computation, and joint modeling using multi‑party secure computation, federated learning, and differential privacy techniques.

Implementation Details : Leveraging SDH, the collaboration combined Jiahe Technology’s ad placement data, brand private‑domain data, Alibaba Mama’s e‑commerce conversion data, platform marketing data, and audience tag data. This integration achieved data element circulation and value extraction, solving practical challenges such as cross‑domain user identification, multi‑party data flow computation, joint modeling, and ad effect attribution.

Results and Impact : The solution created an innovative “placement → traffic → growth → placement” loop, markedly improving marketing analysis efficiency for benchmark brands in cosmetics, food, beverage, and daily‑chemical sectors. It also pioneered a “usable but invisible” data element circulation paradigm, offering a reference model for the broader advertising industry.

Significance : This case demonstrates how privacy‑computing technology can be applied to advertising to ensure compliance, protect user privacy, and unlock the value of data assets, providing a concrete example for industry adoption.

Reference link: http://mp.weixin.qq.com/s?__biz=Mzg5NTk4MDMwMA==∣=2247490415&idx=1&sn=2e4ce343d0c95fa44f5bc6d76dd6987e

advertising analyticsData SecurityPrivacy Computingindustry case studycross-domain trackingdata asset analysis
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