Quantzig, a leading analytics advisory firm, has announced the addition of new services to its merchandising analytics solutions portfolio. With troves of structured and unstructured datasets now available at every interaction-point, there is a dire need to change retail strategies and leverage merchandising analytics-driven insights. Quantzig’s merchandising analytics solutions help retailers to eliminate data silos by offering actionable insights that empower them to make smarter business decisions.
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Leveraging analytics to make crucial merchandising decisions has never been easy. Request a free brochure of our analytics solutions to learn how we can help you transform your approach to retail decision making.
A competitive market scenario, the emergence of new retail channels, and an increasingly demanding customer base – are factors that have challenged retailers across segments to find new and efficient ways to remain relevant and competitive. However, in the real world, retailers are inundated with data from various sources and are pressurized to make smart, data-driven decisions to gain a competitive edge. Quantzig’s merchandising analytics solutions are designed to help retailers overcome the burden of managing vast datasets by helping them break data silos and analyze data to unearth valuable insights.
The overabundance of data sets and inefficient in-house data analytics tools have plagued the data management capability of retailers across the globe. As such, most retailers struggle when it comes to maintaining and analyzing data sets. We at Quantzig understand the value that data holds from a business viewpoint, which is why we’ve designed a comprehensive portfolio of retail merchandising solutions to help companies gain in-depth insights into the market scenario by replacing the inefficient data management tools and in-house analytics approaches with more agile, receptive, and cohesive data management systems.
Our merchandising analytics solutions leverage pre-built models and advanced methodologies that facilitate profit and loss budgeting, cannibalization analysis, and storefront layout optimization. Talk to our analytics experts for detailed insights.
Quantzig’s Merchandising Analytics Capabilities
With dynamic changes in business models and the ongoing shift in the retail scenario, it has become necessary for businesses to adopt a comprehensive approach to retail category analysis – one that focuses both on the customer and the categories required to meet the growing demands of the customers. Our retail category analysis solutions can help retailers tackle challenges arising due to the dynamism in market trends through advanced analytics-based solutions.
Our merchandising analytics solutions are designed based on the industry’s best practices to help retailers make merchandising crucial decisions. Gain limited-time complimentary access to our analytics platform to learn how we can help you.
2: Store Front Layout Analytics
In today’s dynamic retail scenario, business success calls for a store layout plan that successfully leverages storefront layout analytics to drive satisfaction and create unique customer experiences. Through our storefront layout analytics solutions, we leverage machine learning algorithms and proven methodologies to help generate the kind of value that keeps retailers competitive and profitable in the long run.
We can help you transform the evolving retail challenges into fruitful opportunities. Learn more about our offerings here!
Take a look at our portfolio of merchandising analytics solutions: http://bit.ly/2pfRDXA
About Quantzig
Quantzig is a global analytics and advisory firm with offices in the US, UK, Canada, China, and India. For more than 15 years, we have assisted our clients across the globe with end-to-end data modeling capabilities to leverage analytics for prudent decision making. Today, our firm consists of 120+ clients, including 45 Fortune 500 companies. For more information on our engagement policies and pricing plans, visit: https://www.quantzig.com/request-for-proposal
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