Mountain Warehouse's Sam Biddlecombe on AI and E-Commerce

Global retailers are bearing the brunt of sky high customer expectations as they innovate to deliver faster, smarter and more personalised digital shopping experiences.

As AI becomes a major part of e-commerce along with with real-time data and seamless omnichannel journeys, many brands are replacing ageing legacy platforms with more flexible, API-first architectures that support rapid innovation.

For businesses with large store networks and world-wide operations, the challenge is balancing performance, scalability and customer experience without adding unnecessary operational complexity.

Here, Sam Biddlecombe, Senior Delivery Manager – Technology at Mountain Warehouse, discusses the retailer's e-commerce transformation, its approach to personalisation and how AI is shaping the future of its digital strategy.

Mountain Warehouse relied on a custom-built system for 10 years. What made you realise building it yourselves was no longer the right path?

The expectations on e-commerce systems has increased exponentially over the last decade. Customers want faster digital experiences, advanced search and discovery, seamless checkout journeys and a more consistent experience across both online and physical stores.

Our previous e-commerce platform was becoming increasingly difficult to scale and was also absorbing a lot of resources just to maintain its ageing infrastructure.

We needed a platform capable of adapting much more quickly to changing customer behaviour and emerging trends such as GEO and AI-driven optimisation.

It also needed to support the scale and complexity of our business which now stretches across over 400 stores worldwide.

With BigCommerce we can innovate faster, integrate best-of-breed technologies and focus our engineering efforts on delivering better customer experiences rather than maintaining core infrastructure.

With so many retail tech tools on the market, what is your personal test for a new vendor? Is it ease of integration, cost or something more specific to the outdoor industry?

For me, the real test of a vendor is whether they can provide the right balance between flexibility and control.

We wanted a platform that allowed us to customise the parts of the experience that genuinely matter to Mountain Warehouse customers and accelerate innovation across our global e-commerce operations, without adding unnecessary operational complexity.

By partnering with BigCommerce we're able to take this flexible approach across payments, search, content and marketing automation. This helps us implement new features and initiatives faster while still improving security, reliability and compliance.

Beyond site speed and security, what is the one internal metric you’re watching most closely to prove this new platform was the right investment?

One of the key internal metrics for us is the time it takes to implement new features.

We’re focusing on delivering new features 50% quicker than what we achieved historically, which means we are delivering more value to our customers as well.

We also want to ensure our data is accessible for all our technology uses such as complex order handling, custom checkout experiences and multi-location inventory management.

How does Mountain Warehouse define personalisation?

Personalisation is about making every shopper feel understood and valued. This starts with moving away from treating interactions as isolated transactions to seeing the whole customer journey.

By understanding what a customer is actually shopping for, whether that’s hiking, skiing, camping or another outdoor activity, and helping to effectively guide them through that process, we create an experience that feels more connected and responsive.

The new platform gives us a much stronger foundation to build on this concept, particularly through better integration between different systems, improved search and discovery capabilities and an altogether more flexible e-commerce experience.

Over time, that will allow us to deliver journeys that feel increasingly tailored to individual customers rather than relying on generic e-commerce capabilities.

Your new system uses Algolia to respond to user signals in real time. Can you give an example of a customer signal that your old system would have missed, but your new system catches and acts upon?

Algolia provides us with a better understanding of customer intent in real-time, creating a more responsive and tailored shopping journey.

For example, if a customer searches for “waterproof jacket”, previously, that may have returned a static set of results based on the search term itself.

With Algolia, if that customer then filters by kids’ sizes, checks stock availability near a local store and starts interacting with insulated products, the platform can recognise that they are likely shopping for a warm, waterproof children’s jacket with local availability.

That means the experience can become much more relevant in the moment, surfacing products that better match a variety of different preferences, rather than relying on a one-size-fits-all result set.

Mountain Warehouse has more than 400 physical stores. How does the new digital personalisation strategy bridge the gap between the online cart and the in-store experience?

We want the online experience to feel as personalised and helpful as interacting with one of our store colleagues.

The rollout with BigCommerce included several capabilities designed to support that approach, including click-and-collect functionality, more flexible checkout experiences with multiple payment methods and gift cards, and more advanced order handling.

Combined with better use of data around what customers buy and how they interact with the brand, this will enable us to build the personalised experience customers look for no matter where they are shopping.

Now that you have a flexible API-first foundation, how are you looking at Gen AI? Is it for customer service, automated product descriptions, or something more radical in the supply chain?

The opportunity for us is about using AI practically and as part of the wider goal of building a more flexible e-commerce operation, rather than adopting it as a standalone technology project for its own sake.

Customer service, product discovery and AI-assisted content are all areas of interest, and especially useful in outdoor retail where clearer and more tailored guidance around factors like size, fit, colour and activity can add real value to the customer experience.

For a business like Mountain Warehouse, one of the most exciting opportunities is using AI to help customers make better choices - whether that is finding the right kit for a trip, understanding technical product features or choosing the best fulfilment option.

The API-first foundation is important because it gives us flexibility to connect AI tools into the right parts of the business without locking into one fixed approach, meaning we test new capabilities and scale efficiently as demand grows.