The following article provides highlights of an interview between InfoSum CEO Brian Lesser and Marketecture Media founder and CEO Ari Paparo. Register for free Watch more discussions to learn how marketers are using cleanrooms to address consumer identity challenges.
Cleanrooms are helping marketers evaluate and understand their customer data
Cleanrooms allow marketers to develop more accurate customer-centric marketing strategies. These neutral environments support more effective CRM and ad impression data analysis. In addition, cleanrooms are helping brands integrate first-party consumer data and conduct in-depth analysis while protecting audience identities. However, many data collaboration solutions create siloed views due to provider-specific channel limitations. According to Lesser, brands are often forced to work with multiple partners to dissect this audience data. In this model, one partner provides the identity information, and one partner provides the onboarding solution — data is pooled, anonymized, and sent back for analysis. “The whole process is time-consuming, inefficient, and increasingly fraught with privacy and security challenges,” he said. Further complicating the identity resolution problem, traditional cleanrooms are often built using centralized databases. This requires each data owner to upload personal data to a third-party environment, which raises significant consumer privacy concerns. Lesser says marketers should address these challenges with a decentralized cleanroom solution that licenses the technology to parties using the data “bunker” technology. Advertisers upload CRM data into these siloed pieces and then sit back as the information is transformed from individual rows of customer data into descriptive mathematical models that can be prevented from being reverse engineered into customer files. Decentralized solutions such as these help protect consumer privacy and create a bridge between data sources and consumer identities. “This bridge can be anything,” Leather said. “These data collaboration systems will identify where there is overlap. If the two datasets have email addresses in common, the system will tell you that the biggest overlap between them is email. Can be an arbitrary descriptor of the data, can be online or Can go offline.”
To learn more about clean room and identity resolution technology, listen to this interview between Marketecture and Brian Lesser More conversation here .