Source: cision | Published on: Tuesday, 05 September 2023
Partnership to accelerate the delivery of data-infused pricing at scale to leading global brands and retailers
BENGALURU, India and TEL AVIV, Israel, Sept. 5, 2023 -- UST, a leading digital transformation solutions company, has partnered with leading price optimization platform Quicklizard to provide AI-guided data-infused pricing at scale to prominent global brands and retailers. The integration of the Quicklizard platform into UST's solutions portfolio provides clients with improved operations, experiences, and profitability across their retail value chains by optimizing pricing capabilities.
This collaboration harnesses Quicklizard's leading price optimization platform as a core part of UST's comprehensive retail solutions, delivering best-in-class technology solutions as part of a comprehensive, scientific approach to pricing at scale that is unequivocally aimed at client business success. The partnership seeks to aid clients in maintaining profitability while sharpening their competitive edge within their markets by offering strategic discipline, accurate market intelligence, and stringent implementation procedures.
Even in today's advanced retail market, pricing managers must still engage in the time-consuming task of manually analyzing a wide range of data sources to inform their pricing choices. This limits managers' ability to optimize prices to just 5%–15% of their product catalog. However, Quicklizard's AI-powered dynamic pricing platform enables pricing managers to optimize decisions for 100% of their catalog.
Leveraging the power of machine learning and artificial intelligence, Quicklizard and UST have developed an innovative platform that adeptly covers all aspects of pricing for retailers, increases efficiency, and accelerates digital transformation. Utilizing an omni-channel approach, Quicklizard's platform ensures retailers can design bespoke pricing strategies across a wide range of business models. In addition, the platform features a robust pricing engine with pre-defined rules and conditions, automation and management tools, AI capabilities, analytics, and an open interface that allows clients to develop complex pricing strategies without the need to integrate with additional tools. This is in stark contrast to standard price monitoring tools which are predominantly focused on tracking competitors' prices and making pricing decisions based on this data alone, whereas the joint solution provides the ability to adjust prices in real time based on several critical factors.
These advanced solutions are complemented and enhanced by UST's AI-powered 'VERA' engine, designed by UST Evolve, which supports the mapping and matching of own-brand products across multiple categories. UST Evolve is a global digital business transformation group of strategists, designers, technologists, and domain experts dedicated to solving complex challenges through pragmatic approaches that deliver bold outcomes.
Through the collaboration, UST and Quicklizard are positioned to provide consulting capabilities and wrap-around services to our joint clients, including dynamic pricing solutions, project management, delivery management, and business analysis.
"By integrating our advanced platform as part of a comprehensive UST solution portfolio, we are able to offer the coordination, discipline, market intelligence, and rigor needed to maintain profitability and a competitive edge," said Pini Mandel, Co-Founder and CEO, Quicklizard.
"The Quicklizard team and solution are a great fit for the UST culture, our emphasis on client-intimacy and our retail solutions portfolio. They are ideal partners in our quest to assist clients seeking to improve operations, experiences, and profitability across the retail value chain by specifically optimizing their pricing capability," said John Taylor, UK Retail Lead, UST.
This is the latest in a series of high-profile collaborations for UST. Over the past two decades, the company has established itself as a key business transformation partner across a range of industries. For more information on UST and its work driving digital innovation, please visit the UST Newsroom.
About Quicklizard
Quicklizard (TASE: QLRD) transforms pricing into a strategic asset for retailers.
Quicklizard is the leading pricing optimization platform for retailers and brands. Offering retailers, the ability to fully manage their pricing strategies on a single platform that provides the tools, insights and analytics required to achieve pricing excellence.
We provide an advanced pricing infrastructure that makes your business truly thrive across all retail industries from consumer electronics and pet supplies to groceries and point to point airlines. Our Platform is deployed across over 50 markets in both online and offline channels producing millions of price recommendations each month.
To find out more, visit Quicklizard.com
Media Contacts, Quicklizard:
Anat Oransky Lev
VP of Marketing, Quicklizard
anat.oransky@quicklizard.com
About UST
For more than 24 years, UST has worked side by side with the world's best companies to make a real impact through transformation. Powered by technology, inspired by people, and led by our purpose, we partner with our clients from design to operation. Through our nimble approach, we identify their core challenges, and craft disruptive solutions that bring their vision to life. With deep domain expertise and a future-proof philosophy, we embed innovation and agility into our clients' organizations—delivering measurable value and lasting change across industries, and around the world. Together, with over 30,000 employees in 30+ countries, we build for boundless impact—touching billions of lives in the process. Visit us at www.UST.com
Media Contacts, UST:
Tinu Cherian Abraham
+1 (949) 415-9857
Merrick Laravea
+1 (949) 416-6212
Neha Misri
+91-9284726602
Roshni Das K
+91 7736795557
media.relations@ust.com
Media Contacts, U.S.:
S&C PR
+1-646.941.9139
media@scprgroup.com
Makovsky
ust@makovsky.com
Media Contacts, U.K.:
FTI Consulting
UST@fticonsulting.com
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