Industry Solutions

Retail

Drive new revenue through Alternative Data and Retail Media Networks.

Today's challenges

Understanding consumer behavior

With a plethora of transactional data, retailers often face challenges in discerning critical consumer insights, leaving potential revenue on the table.

Consumer privacy concerns

The balance between gathering insights and ensuring consumer data confidentiality is crucial, with growing concerns over privacy in the digital era.

Revenue diversification

Beyond traditional sales, the rise of Retail Media Networks provides retailers with a fresh avenue for revenue generation by monetizing consumer data for advertizers.

Holistic customer profiles

A comprehensive view is essential to cater to customer needs. Retailers who lack this often miss out on tailoring the ideal shopping experience.

 

Our solution

Omnisient equips retailers with cutting-edge data collaboration tools to deeply understand consumer behavior while ensuring utmost data privacy, allowing them to unlock new revenue streams, such as Retail Media Networks, and tailor superior shopping experiences. By choosing Omnisient, retailers gain a competitive edge, seamlessly monetizing their vast consumer data and fostering enhanced trust through a privacy-first approach.

From enhancing shopping experiences to leveraging data for new revenue avenues like Retail Media Networks, we’re here to revolutionize retail with state-of-the-art data collaboration and insights.

Privacy-preserved data collaboration

Collaborate with partners outside of your industry to gain a more holistic view of your customers’ shopping behavior, demographics, and preferences.

Retail media network enablement

Foster meaningful partnerships with insurers and wellness brands to improve patient offerings and holistic care.

Unlocking new revenue streams

By offering insights directly to sectors like banking and insurance, retailers can further diversify their revenue streams and establish collaborative data ecosystems.

Featured case study

How Banks use Shopping Data to determine Credit Risk

The objective was to use a retail grocer’s loyalty shopper data as an alternative data source for predicting credit risk among credit invisible applicants, aiming to grow financial inclusion, especially within the lower-income demographic.

Book a product demo

Book a demo and discover how we help your business unlock the power of 1st party data collaboration without the risks.