Mountain Warehouse is the UK’s leading retailer for outdoor clothing and equipment. It has 400 stores across the world, from Europe and North America to New Zealand. In 2019, the company created a new retail-focused agile team to reduce manual processes in stores and empower staff to better serve customers.

The team designed a number of apps to help with everyday tasks like stock counts, returns and click and collect. Next, they turned their attention to customer pain points — products missing labels and queuing at the till to ask a question.

Essentially, the goal was to make shopping painless for everyone and maximize any opportunities to add value for customers. But store fronts come with specific challenges that the team needed to address.

Much as we’d love to have great Wi-Fi signal everywhere, we can’t rely on it. As David Jarrett, team lead for retail development at Mountain Warehouse explains: “Wi-Fi can be patchy in stores. When we started designing our first application, we had to pivot our whole approach around that consideration. Data syncing is really important, changes need to be reflected immediately. We can’t have a situation where stock levels are inaccurate or team members can see different values on their apps.”

In fact, this was one of the deciding factors that led to MongoDB. “We decided to take an offline first approach, which isn’t easy. MongoDB Atlas is compatible with that approach and has great documentation around how to do it. We also liked that it has good support for Android and the React Native framework,” reveals Jarrett.

The first app the team developed is still one of the most popular. It’s called Product Checker, and helps staff respond to queries by giving them information on stock, prices, special offers and missing labels, for example. Data from the company’s SQL data warehouse is pushed into MongoDB Atlas and displayed in the app.

“It doesn’t matter if there’s no Wi-Fi when someone uses Product Checker, any changes are reflected as soon as the device connects thanks to Atlas Device Sync,” explains Natalia Jagiełło, IT developer at Mountain Warehouse. “If a price changes when the app is open, the user can see that right away.”

Following on from Product Checker’s success, the team developed more apps such as Stock Count. Staff use it to scan barcodes as they count stock, and MongoDB Atlas routes that data to the area or store manager to verify it.

Apps are also used to scan parcels for Click and Collect or deliveries. Atlas Device Sync pushes barcode data into MongoDB Atlas and the product is marked as in stock at the till. With stores across the world, Mountain Warehouse also needs to partition data, so prices in UK currency aren’t synced to products in New Zealand, for example.

“All you have to do is define the field you want to update in MongoDB Atlas, enable sync in app services and connect a partition. It updates those segments of data quickly and efficiently, so it’s available for staff and customers,” says Jagiełło.

Today, Mountain Warehouse has 25 microservices and applications running on MongoDB, and they were all created to improve the in store experience. “Tills should only be used for payments. With MongoDB we can provide tools to help staff work smarter and deliver outstanding customer service on the shop floor,” concludes Jagiełło. “We’ll keep building new apps to improve the retail experience for everyone.”