Making Science Launches Gauss Cookie Deprecation Impact Tool: The Only Solution to Measure the Impact of Cookie Loss

Gauss CDIT is the first solution to enable companies to measure – with percentage data – the real-time impact of cookie deprecation on conversion rates

CHICAGO, ILLINOIS, USA, January 22, 2024 /EINPresswire.com/ -- Making Science, a technology company specializing in innovation and digital acceleration, today announced the launch of its Gauss Cookie Deprecation Impact Tool (CDIT), the first and only solution on the market designed to measure in real-time what impact the loss of third-party cookies will have on companies' conversion rate to sales.

This innovative tool comes at a key moment for the industry, following the announcement of Google's elimination of third-party cookies, scheduled for the second half of 2024. The Gauss Cookie Deprecation Impact Tool will provide Making Science customers with accurate percentage data to confirm how this loss of information will affect their business. In other words, for the first time, companies will have access to an unprecedented assessment that provides real data on the percentage of users who visit websites and applications without cookies, corroborating the effect on their marketing strategies.

The tool has already yielded significant data for a selection of Making Science clients; the results of measuring the absence of third-party cookies will lead to a 30% drop in conversion rates.

Real-time data, thanks to technological innovation

This new platform is essential for companies that want to be prepared for the cookieless transformation of the digital ecosystem. Thanks to technological innovation and high capabilities in data analysis, Making Science will enable organizations to effectively identify how to redesign their marketing strategies and optimize performance in the face of this changing landscape.

With this launch, Making Science reaffirms its pioneering position in developing innovative technological solutions. Jason Downie, the US CEO of Making Science, commented, "We are betting on continued innovation as we stay ahead of industry shifts. We developed the Gauss Cookie Deprecation Impact Tool to help us and our customers prepare for and navigate these changes.” He continued, “This technology enables companies to anticipate and implement effective first-party strategies to combat the impact of losing third-party cookies.”

Gauss, the origin of the cutting edge
This new tool from Making Science is part of Gauss, a suite of technology solutions based on first-party data and artificial intelligence for decision-making in key marketing and sales processes.

About Making Science

Making Science is a digital acceleration company with over 1200 employees and a presence and technological development in 14 markets: Spain, Portugal, Mexico, Colombia, France, Italy, the UK, Ireland, Sweden, Denmark, Norway, Germany, Georgia, and the USA. As a consulting partner of Local Planet, the world's largest network of independent media agencies, Making Science offers digital, technology, and performance marketing services to an international audience. The areas in which Making Science operates are digital marketing and MarTech, software and cloud, and artificial intelligence and SaaS, with a firm commitment to innovation.

As part of its commitment to innovation, Making Science offers its clients end-to-end capabilities required for consulting, developing, integrating, and maintaining advanced IT solutions that offer maximum scalability, cost-effectiveness, and efficiency. In addition, it has a global network of delivery hubs that drive job creation and the availability of highly qualified technological talent to develop projects that accelerate transformation and modernization.

Making Science participates in various ESG initiatives, including the Climate Pledge, the United Nations Global Compact, and the Pledge1% initiative, supporting non-profit organizations in its community with a strong commitment that will greatly impact the future.

Jen Crompton
WIT Strategy
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