What is data collaboration?
Data collaboration means analysing multiple independent datasets to gain the combined insight. It produces the same output as stitching the datasets together, without the data privacy, trust and implementation barriers.
Digital bridges are built between the datasets and only the query moves, meaning data is never at risk. The query matches identities and returns aggregated statistical answers, making it the most privacy-preserving way to connect customer data.
Data collaboration can be used internally to combine siloed datasets, and externally to work with other parties without sharing sensitive data. It enables users to co-operate with colleagues and partners in a trusted environment.
Generate new insights
The competitive edge gained through connected data can be seen through subscription services. These disruptive businesses are able to demonstrate a higher level of customer understanding, as they know exactly who their customers are, what products they like and how they can be up-sold.
For a long time, Gillette were the clear market leaders in the male grooming industry, but even they have been disrupted by Harry’s and Dollar Shave Club, with their less expensive products, innovative subscription services, convenient home delivery, and quirky ad campaigns.
In this instance, success has been achieved by providing a data-driven customer experience. For companies with different business models, that aren’t able to create a 360 degree customer view, data collaboration offers a solution to enrich and augment customer understanding and gain an advantage over competitors.
By collaborating over data with a colleague or strategic partner, you can access broader insights about your customer and audiences, without the commercial, privacy and security risks associated with data sharing. This creates the opportunity to achieve more with your data and translate this knowledge to provide personalised services and relevant product offerings.