DataSapien offers Personal Marketing Technology to brands. Its edge architecture is focused on providing better customer outcomes. It is comprised of a bundle of components that are embedded inside existing customer apps, as a Software Development Kit, or SDK.
These components include 1) On-Edge Personal Data Storage and 2) On-Edge Personal Intelligence technology. The in-app SDK is controlled and managed by the 3) DataSapien Orchestrator which can be deployed by clients in their choice of cloud service provider (Azure, AWS, Oracle) or on their premises.
Together, these components enable customers to participate with brands, privately, using their own data, to get their jobs done. The result is far better outcomes for customers and for the brands that they choose to engage with.
Benefits of DataSapien Edge Architecture:
- Privacy is 100% Guaranteed with Zero-Shared Data
- Personal Experiences: Brands can offer more tailored experiences based on unique user insights due to the volume and variety of verified data now available to generate insights, signals and solutions
- Enhanced Data Security: Data remains on the user’s device, minimising the risk of breaches
- Low Latency as processing of data and insight generation happen as close as possible to the customer
- Offline access as processing can still happen locally if/when the device loses internet connection
- Reduced cost of centralised compute, as processing shifts to the customer devices
- Regulatory Compliance: Ensures adherence to data privacy laws such as GDPR and CCPA
- Scalable Solutions: Easily adaptable to various business sizes and industries
- Eco-Friendly: Reduced need for massive data centres lowers environmental impact
This post provides a high-level overview of the technical components of On-edge Personal Data Storage. A long form post covering all of the components of DataSapien edge architecture is also available here.
The Personal Data Storage Components
1. Personal Data Gathering and Storage Components
The secure, private and confidential storage of personal data is at the core of the DataSapien edge architecture. The DataSapien SDK contains
Data Vault
The core repository of the user’s MeData. By default, all data held in the DataSapien DataVault is private Zero-Shared Data unless explicitly shared as consented Zero-Party Data.
The MeData stored here may come from a number of sources:
- Customer Data: from the brand such as:
- purchase history
- purchase frequency
- customer service support interaction history
- loyalty history etc.
This is ideal seed data ‘given’ by the brand to serve as the initial population of the DataVault, creating value and solving the ‘cold start’ data problem.
- Life Data: Gather data utilising simple user journey’s driven by the customer’s Job To Be Done (JTBD) and desired Outcomes. Once again, this MeData may be gathered from a variety of sources:
- Device Native data such as location data, accelerometer data, app data, device details, screen usage etc.
- Explicit Questions and Answers. These enable the customer to self-populate their Data Vault with data such as preferences, beliefs, attitudes, desires etc. And generate psychometrics (see Personal Intelligence below).
- Data from third-party API’s: External data gathered into the app to unlock customer Jobs. There are thousands of potential data sources available, covering Social Media, Health, Bank, Car, Home data etc. These connections are managed by the DataSapien API Gateway and Orchestrator (more on this below).
- Browser Data: The SDK has an optional browser extension module that the customer can deploy into their browser to enable the gathering of web browser data. In addition to gathering data, the browser extension can be used as a private, omnichannel communication path, connecting directly from the app to enable, for example, real-time personal marketing messages based on browser domain.
- Verifiable Credentials: The Wallet (see below) holds 3rd party verifiable credentials as defined by related standards which may also be stored in the DataVault along with related meta-data. These then become available to the Personal Intelligence stack for multi-variate data processing.
- Insights and signals: The Personal Intelligence stack (see below) creates insights and signals which may be shared with the Brand as Zero-Party Data. Copies may also be stored in the customers DataVault to make them available for further processing. This data network effect is an important advantage of edge data processing.
The Data is multi-dimensional, recording the data item plus time and location [HH1] [SD2] where applicable. For example, the DataVault may privately store that the individual plays tennis at X location and Y time.
Data Wallet
The Data Wallet stores and exchanges Verifiable Credentials (VCs). These may come from formal providers of Verifiable Credentials (primarily government entities) and may then be shared with requestors of Verifiable Credentials, including as a Self-Sovereign exchange, i.e. providing proofs without revealing the sensitive underlying data.
The Data Wallet is designed using Open Wallet Foundation (OWF) standards. These are the same standards used by Google, Microsoft and Visa. It is capable of interacting with eIDAS and Mobile Driving License (mDL) providers of credentials, covering both European and USA standards.
A copy of verifiable credentials data is also stored in the DataVault to enable the processing (with Personal Intelligence) of extrapolation and inference data. For example, a verified date of birth (e.g. 15/01/2000) is processed to provide a verified age (24 years at the time of writing), verified age group (20-30 years at the time of writing) and verified age threshold (over 18/21). These may then be shared as Zero-Party Data without sharing the sensitive verified data. They are also stored in the data wallet as inferred verified credentials.
Personal Cloud
Private and secure data backup, plus multi-device data synchronisation, are provided by utilising the customers’ own iOS or Android Data personal cloud. Data is encrypted within the personal cloud. If a device is lost, the owner is able to connect a new device to their personal cloud to restore the data on their new device and synchronise. This approach maintains the integrity of the DataSapien edge architecture approach.
The long form post covering all of the components of DataSapien Edge Architecture is also available here.
For more technical information on DataSapiens Edge Architecture, checkout the DataSapien Developer Portal.
If you have any comments or questions, please do get in touch. We’d love to hear from you.