Data-driven insights in the era of PII

The European Union’s General Data Protection Regulation (commonly known as GDPR) came into effect on the 25th May 2018. It is important to any user or processor of personally identifiable information (PII) as this new law marks a seismic change in the way that organizations must protect consumers’ data.

The headline of GDPR is that it enforces much tougher non-compliance penalties than the Data Protection Act (DPA). Breaches can mandate a fine of 4% of annual global turnover or €20 million (almost $25 million) – whichever is greater. Previously, fines under the DPA were limited to £500,000.

Globally, personal data privacy is also to the fore. The US equivalent of the GDPR is the CCPA. The CCPA (or California Consumer Privacy Act) was inspired by the GDPR, and both laws were created to protect the personal data of online consumers.

Although the specter of privacy looms large over the Holy Grail of customer insight – information about the individual and household – there are many other data options open to organizations who want actionable insight on consumers without the risk or constraints of new and emerging regulation.

A geodemographic segmentation is one of these options. These data products classify, and label neighborhoods based on the socio-economic and behavioral characteristics of their populations, usually derived from anonymized, aggregated and fully compliant data, such as censuses and surveys.

Geodemographics assume that people who live in the same neighborhood are likely to have similar characteristics – in other words, “Birds of a feather flock together”. Areas are classified in terms of the characteristics of the population which they contain e.g., “Flourishing Modern Families”, “Inner City Roots”.

This classification of neighborhoods provides a rich understanding which can enable:

• Segmentation and insight
• Selection and targeting
• Campaign planning
• Customer analysis and modelling
• Trade area analysis and retail planning

Although at first glance geodemographic classifications appear simple, they solve a multi-dimensional problem – i.e., how do you provide accurate, powerful, understandable local area insight based on hundreds of data variables? Our brains cannot work in multiple data dimensions, so reducing these into one descriptive label provides an easily comprehensible and intuitive tool. The number crunching statistical routines used to build these systems cluster neighborhoods of similar types together, revealing a national social taxonomy.

Precisely has launched a new geodemographic data product for the US market, PSYTE^TM US. Each populated Block in the US is assigned one of 63 segments based on, and described by, multiple socio-economic and behavioral data dimensions.

The PSYTE^TM US geodemographic data product is created using proprietary techniques to ensure that all foundational data is kept up-to-date, reflecting the ever-changing nature of the US population. It is available in text and mappable formats, and is bundled with the PreciselyID, a unique and persistent identifier that allows tagged addresses to be linked to numerous Precisely data products without the requirement of spatial queries. PSYTE^TM US will also be made available in Precisely’s Data Integrity Suite.

To learn more about the PSYTE^TM US data product, visit our data catalog.