Among the Fortune 500 and Global 500, MongoDB customers include 8 of the top retailers.
Twenty-first century retailers are facing an increasingly challenging and competitive environment. Now that customer bases are becoming global, retailers need to have scalable systems that can accommodate massive spikes in traffic. They need one system for all time zones and cannot afford downtime. They need real-time analytics and reactivity, both from a customer-facing and supply-side standpoint. Given the rise of ecommerce and pressure on margins, retailers are looking for innovative services as well as ways to improve customer service, loyalty and engagement. Leading organizations in retail are choosing MongoDB because of its ability to help them compete, providing superior customer experience and accelerated time to market.
Example Retail Solutions
Rich Product Catalogs. Product catalogs are becoming more and more complex, encompassing a range of products with different characteristics. Retailers need simple, flexible platforms that can store various product types in a single database and that make it easy to add new products to adapt to market demands. They need to ensure that product catalogs are easily searchable and consistent across their various channels, like brick-and-mortar stores, web and telesales. MongoDB provides a scalable and highly-available database, enabling retailers to serve millions of customers globally. MongoDB’s document data model not only provides retailers an agile and consistent platform for storing product catalogs but also a wealth of associated metadata, from photos to clickthrough behavior to customer purchase history. This helps retailers provide more up-to-date and relevant product catalogs and ultimately, a better experience for their customers.
Customer Data Management. Retailers have myriad sources of customer information, from online and in-store billing history, social network data, user-generated content and others. It can be complex to manage and integrate all this data into one single repository. It is even more challenging to aggregate this data and derive useful insights from it. MongoDB’s document data model provides dynamic schemas, making it easy to create universal repositories in which data can be stored, processed and served to other applications. MongoDB’s native analytics capabilities also enable retailers to conduct analyses in place. This enables new avenues for improving customer experience and upselling by providing actionable information for customer service reps, ecommerce applications and more.
New Services. Retailers are looking for innovative services they can offer in order to increase revenue and differentiate in a highly competitive market. Some are creating mobile apps to make it easier for customers to purchase on their device of choice or to navigate store aisles. Others are integrating social components into their websites. These new products and services call for an equally modern database that can accommodate evolving data models and constant iteration, and that is compatible with mobile and social apps. Further, they require a scalable backbone that can handle massive spikes in usage due to seasonality or an app that goes viral. MongoDB is helping leading retailers differentiate and decrease the friction required to generate purchases, increasing developer productivity and helping them bring new apps to market faster.
Other use cases for MongoDB in retail include:
- Customer Sentiment Analysis
- Digital Coupons
- Inventory Management and Optimization
- In-Store Customer Navigation Analysis
- Demand Chain Optimization
- Real-Time Price Optimization