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Fill out the form and a member of the InfoSum team will get in touch to arrange a demo.
Unify insights across all your internal data sources and channels to create a unified understanding of your customers.
The only privacy-safe and compliant way to connect first-party data sources to create a single source of customer knowledge.
Put data at the core of all marketing decisions with insights and audiences developed from a trusted and unified customer view.
Connect insights from multiple channels and devices to build an omnichannel view of your customer profile and behaviour.
We don’t hold any data. We provide the identity infrastructure to power a decentralised ecosystem.
Federated technology keeps your data in its own unique Bunker, that only you can access.
You remain in control of who can analyse your data. This never grants access to the raw data.
Internal data silos are connected on existing identifiers, removing the need to share data with a third-party.
A multinational media company wishes to conduct analysis across their various online publications’ CRM systems to determine where there is a crossover in audiences and where there may be a potential for cross-promotion. There are a number of challenges preventing this initiative from moving forward:
Each publication uploads its data to their own isolated Bunker. The data is normalised and mapped to the global schema.
Each Bunker owner grants permission to a nominated user at the media company. An automated process matches identities using existing identifiers, removing the need for a universal ID (where a match can not be made, a third-party identity graph may be used to create a match, but doesn’t require data to be transferred to the identity graph owner).
This user is now able to conduct statistical analysis across the totality of all CRM databases - a true unified customer view - and determine where there is an intersection between audiences, where there may be opportunities for look-alike targeting and other revenue generation.
Aggregate level results and differential privacy features prevent any single individual being identified within a dataset.
Federated Architecture and Insights Engine overcomes trust barriers by removing the need to share and centralise data.
AI-powered normalisation and mapping removes the need for a complex and expensive ETL projects.
Each party retains complete control over their data through decentralisation and rich permission controls.
