Marketers face a data dilemma. They understand the value of first-party data in creating a 360-degree view of the customer to use for relevant, personalised campaigns, but are also aware of the risks involved in the processing and management of personally identifiable information (PII). With poor management of customer data hitting the bottom line of businesses, marketers are seeking ways to maximise the commercial value of their first-party data without falling foul of stricter data regulations and relying on unreliable third-party data.
When using data to create a fully integrated and omni-channel customer view, the current approach is to take available datasets from across multiple sources and place them into one central location, creating data warehouses or data lakes. But while this tactic might deliver a single view of the customer, it has numerous drawbacks relating to security and control. Obtaining a true picture of customer behaviour while protecting privacy and maintaining control is only possible through a decentralised infrastructure.
Paying the price for poor data management
A centralised approach to data management limits the control marketers have over their data and can ultimately reduce its value. Data lakes combine multiple types of information from a wide variety of sources with different quality standards, diluting the usefulness of insights drawn from centralised data. Using external providers to enrich centralised data is problematic as allowing access to the central repository risks data leaks and regulator breaches.
Centralising, storing and maintaining data in a single location such as a server or mainframe computer – the standard industry approach to data management – also increases the risk of a security breach as the central repository becomes a key target for hackers. If that central location is attacked the impact is immense due to the vast volumes of data stored.
Sharing insight without sharing data
Decentralisation, on the other hand, gives marketers increased control over their data. Raw data is never shared and remains safely stored in its original location, so there is no central repository to act as a PII honeypot. Instead marketers can combine insights from separate data sources, providing them with a complete customer view across their own organisation, as well as an opportunity to share this knowledge with external partners to gain commercial value without compromising data integrity.
So how does decentralisation allow marketers to combine data insights and create the single customer view without sharing raw data? The answer lies in an approach that focuses on connecting rather than sharing.
Decentralisation involves isolating data within a dedicated virtual server so only the controller retains access to the original information – not even the platform being deployed has access. Information is then mapped to a global schema and converted into a mathematical representation of the data, at which point all PII is deleted. After this process takes place, only queries are passed between companies, and aggregate statistical analysis returned. The result is a level of consumer insight equal to centralised data-stitching, only with security, control, and trust obstacles removed from the equation.
Building these virtual bridges between datasets means marketers can, for the first time, drive relevant, personalised campaigns without any data exchange. For the three-quarters (76%) of CMOs who believe they are missing out on opportunities due to poor data management, this approach is an alarm call that will make them rethink current methods.
Many marketers feel secure and compliant data management is at odds with targeted, personalised campaigns, but this view is based on existing centralised business models. By reimagining data management practices, and switching to a decentralised approach, marketers can gain maximum commercial benefit from their first-party data while still maintaining security, control and trust.