How InfoSum's Decentralized Data Solution Can Solve Consumer Identity Challenges

As marketers and brands scramble to find new identity solutions as third-party cookies are deprecated, one set of technologies stands out: data cleanrooms. These digital environments, also known as data collaboration platforms, enable marketers to compare data sets without having to risk sharing consumer data. Brian Lesser, CEO of InfoSum, recently spoke with Ari Paparo, founder and CEO of Marketecture Media, about how more and more brands are looking to clean room technology to efficiently capture customer data. Interview highlights how InfoSum is helping companies move away from traditional centralized data blending processes and embrace technologies that disperse audience information for better analytics and privacy. “There is a proven, true approach to data normalization, which is mostly about finding a common identity and blending data in third-party databases,” Lesser said. “But now the industry has moved us into a data clean room.”

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.”

How Identity Resolution Technology Enhances Cleanrooms Capability

Over the past few years, brands have largely relied on identity resolution technology to match customers of various data sets, but as marketers continue to lean towards first-party data, many find these techniques work better with cleanrooms. When evaluating compatible identity solutions for use with cleanroom technology, savvy marketers will be mindful of their match rate capabilities—the percentage of consumer records that can be matched to another dataset. These metrics help to highlight the effectiveness of identity technologies in resolving identities in clean room environments. Marketers should also pay attention to characteristics such as the level of identity precision, accuracy of matching and reach of target users, Lesser said. At the same time, the new cleanroom framework is unlocking greater data transparency, flexibility and decentralized analysis to support more efficient data matching and measurement. Still, when data is too dissimilar, Lesser says it’s better to use an identity solution, especially if clean room technology allows for effective data collaboration. “Data collaboration works well when these datasets have something in common,” he said. “It doesn’t work when these datasets don’t have anything in common. That’s when we can bring in an identity provider to fill the gap.”
To learn more about clean room and identity resolution technology, listen to this interview between Marketecture and Brian Lesser More conversation here .

https://digiday.com/?p=474173