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Traditional platforms (DMPs, CDPs, etc.) require that data be centralised and anonymised for analysis. When the data becomes anonymous, it loses much of the detail that makes customer insights valuable. Through the InfoSum Insights Engine, detailed analysis can be conducted against all the original attribute level insight of the original data, without sharing, moving or centralising the data.
Combine data attributes across any number of first and second-party data sources to unlock rich customer insights that can drive analysis, segmentation, enrichment and activation.
During the analysis process, feedback is provided with every change to demonstrate the quality of the data being used in the analysis and how different filter selections affect the quality of the audience segment.
Analysis is conducted through the generation of mathematical representations of data. It is these representations that move from Bunker to Bunker to create analytical results.
Our proprietary Insight Engine generates a virtual database that enables multiple data sources to be analysed without moving, centralising or sharing data.Learn more
We utilise differential privacy concepts during both analysis and activation to safeguard personal data and ensure no individual can ever be identified within our UDP.Learn more
Our technology doesn’t rely on a single ID or identity graph. Instead it automatically determines the identifier, or combination of identifiers, within the dataset to create the optimal match.Learn more
Our rich permissions management ensures data owners remain in control of who can use their data in their analysis, and to what extent it can be analysed.Learn more
Our automated normalisation and mapping process ensures no changes are required to the original data to make it compatible across multiple data sources.Learn more
Our UDP is built on a federated architecture that ensures all datasets remain decentralised in their own isolated Bunker, but can be analysed ‘as one’.Learn more
InfoSum’s UDP has been built on six core technologies that empower trust by allowing data to remain decentralised, while enabling multiple first and second-party data sources to be connected for analysis and activation.