Retail

The retail industry is currently experiencing a rapid transformation, driven by changing consumer habits, technological advancements, and the rise of e-commerce. This evolution is reshaping how retailers operate, interact with customers, and compete in the marketplace.

Reports suggest that e-commerce is undeniably on the rise as a retail channel, with estimates indicating that 21% of retail sales will be conducted online by 2024. This has compelled even traditional brick-and-mortar retailers to adapt and innovate. Many retailers are now embracing omnichannel strategies that integrate their online and offline channels. This allows customers to seamlessly shop across multiple channels, whether it be online, in-store, or on mobile devices.

In this ecosystem, digital maps play a vital role by empowering consumers to easily search, compare, find, and reach retail locations to purchase the products they need. At Wipro, we specialize in organizing large volumes of real-world data in a manner that empowers consumers to make informed choices while shopping. We are dedicated to seamlessly connecting consumers with businesses in various sectors, including food and beverages, utilities, gas stations, fashion and apparel, books and stationery, electronics, and furnishings.

Through consistent investments in understanding evolving consumer needs, we have delivered sophisticated solutions for our partners in key areas, including:

• Mapping detailed store location data, including floor levels, to ensure accurate address and marker locations for over 27 million establishments. We achieve this through training and enhancing advanced machine learning systems.
• Adding category metadata for over 500,000 businesses to enable better search results.
• Organizing food and beverage menus for over 55,000 restaurants on maps.

With a team of over 200 full-time employees, Wipro is committed to meeting the expectations of retail consumers. Operationally, we have demonstrated our capability as an innovative partner for our clients through various value additions, including:

• Increasing the verification rate of store information by at least 9% by adding smarter resources to the workflow.
• Implementing tool refinement projects that result in efficiency gains of more than 15%.
• Enhancing existing machine learning algorithms by at least 15% through the supply of rich training data and providing analytical insights.