Test Third Party Data Sources for Uplift

Business Problem

In a 2017 Deloitte study on online data collection and consumer data quality, researchers found that over two-thirds of the participants in the study cited third-party data about them to be 50% accurate or less and half of those participants perceived the data as 25% accurate or less. This means that a significant portion of the third-party data out there is deemed unreliable by customers. In 2018, the U.S. businesses alone accounted for $19.2B in spending on third party data assets and solutions. With such large investments being made, validating the potential ROI of these assets is a high-value endeavor. Many marketers struggle to find relevant and accurate data assets that generate significant uplift for their brand and make poor investment decisions due to not being equipped with the right tools to evaluate and implement third-party data assets.

Intelligent Solution

AI will empower your marketing organization to make highly informed purchasing decisions on consumer data assets by predicting which data assets will lead to the greatest uplift in modeling accuracy. From evaluating the freshness and accuracy of disparate data sources to identifying at-risk attributes, understanding the health of a third-party data asset holistically is a great use case for AI, which can identify patterns in the data that may not be spotted through summary analysis or other more manual investigation. Data can get quite expensive and quality is often tenuous, so the ability to model key attributes of the data before deeming them valuable can protect your organization from a great deal of risk.