Data company Numerator expands its consumer panel reach
Data and tech company Numerator, Chicago, has added consumer data capabilities with the acquisition of Information Machine, opening the company up to even larger volumes of purchase data and consumer panelist profiles to strengthen its overall consumer panel data.
Headquartered in Brooklyn, N.Y., Information Machine's proprietary API sources from mobile apps, loyalty card programs and food-based delivery services, as well as media viewing data on supported media platforms. It currently processes 2.5 million consumer connections daily across more than 100 retailers and captures 10 million viewing minutes daily on supported media platforms. Information Machine's APIs will be integrated into Numerator's mobile app, Receipt Hog.
Information Machine's SaaS based platform will continue to be available for commercial application under the new name Numerator Link. The continued investment will enhance and expand the services available to Numerator Link clients.
"Numerator has always been about more, better data. Our investment in Information Machine accelerates the volume and type of detailed data we can add to specific consumer profiles. It further distances Numerator from the increasingly archaic practice of scanning individual UPC codes," said Eric Belcher, CEO, Numerator.
"Less friction for consumers means higher adoption, continuity and data quality, so we architected a low-friction collection system for transaction and service usage data. We recognized the tremendous value generated by integrating this data into a seamless view of consumer behavior. Numerator shares this vision and provides a unique opportunity to realize the full potential of our platform," said Matt Stanfield, Founder and CEO, Information Machine.
The integration of Information Machine proprietary APIs will be done using Numerator's rigorous transparency and privacy standards, including full transparency into all data collected and how that data is used. It also ensures consumers have the right to share in the value of the data they choose to share.