Retail Giant MAP Deploys Intelligence Node to Transform Its Retail Analytics Vista

Press enter to search
Close search
Open Menu

Retail Giant MAP Deploys Intelligence Node to Transform Its Retail Analytics Vista

08/31/2016
Mitra Adiperska (MAP), one of the largest retail lifestyle groups in the world, is using Intelligence Node's powerful retail analytics platform to apply pricing intelligence and merchandizing analytics to its eMall e-commerce site to gain detailed, real-time insight into its competition to ensure its competitive edge.

MAP, headquartered in Indonesia, has an enormous brand portfolio that includes department stores, fashion brands, sports equipment, food and beverage names, supermarkets, and lifestyle products. The company employs 23,000 people and is the local franchise holder of well-known global brands including Zara, Mango, M&S, TopShop, Starbucks, New Balance and Converse.

Through Intelligence Node's flagship platform Incompetitor™, MAP will gain pricing intelligence and real-time competitive insights into 1 billion unique products across 130,000 plus brands in 1,100 plus categories which are all tracked each day, making it one of the most exhaustive and dynamic databases on the market today.

“Incompetitor will give us full visibility and optimize for demand, trends, products, price architecture and regional behavioural differences across all the products and brands we run across MAP eMall,” Amit Keswani Manghnani, vice president e-commerce & customer loyalty at MAP, explained. "This allows us to deliver to meet our customers' needs while remaining super agile about product lines, stocks and pricing to maintain our leading edge.

MAP initially piloted Intelligence Node's multilingual features to explore how to run global channels efficiently by converting language and currency in real-time analysis modes. MAP finally chose Incompetitor because the end-to-end solution provides a benchmarking on pricing, as well as fixing prices in real time and a very large database – all of which were key requirements for the retail giant.

Intelligence Node's multilingual pricing and analytics platform being used by Manghnani and his team uses 20 third-party dictionaries and a comprehensive set of image archives to provide the system with a "smart" way of translating and contextualising listings in Indonesian Bahasa to English. This intelligence has now been augmented by a new Natural Language Processing (NLP) layer to ensure contextual meaning is always accurately preserved.

The platform is helping MAP to gain real-time, accurate pricing and merchandising intelligence regardless of the geography – which is a major boon to a global e-retailer.