How to use your data to win big in the Christmas rush

In late September 2017, Apple released details of its latest iPhone 8 and iPhone X. Breathless reporters converged in Silicon Valley to cover the unveiling.

The media coverage suggested a smash hit, with the public clamouring to get a taste of the latest Apple offering.

But in the weeks building up to the release, the most searched term on John Lewis (one of the UK’s largest retailers) wasn’t ‘Apple’, ‘iPhone’ or ‘iPhone X’. Instead, it was ‘Christmas’.

Consumer data suggests that shoppers are already doing their research – and in the lead up to the Christmas rush (including events like Black Friday and Cyber Monday), retailers around the world are using more and more sophisticated data tools to maximise sales and revenue.

Personalise the experience for your customers

Savvy retailers are using machine learning to create highly personalised experiences for their customers. Outdoor clothing company, The North Face, uses an online shopping experience powered by IBM’s Watson. Customers can now use natural phrasing and conversation as they shop via a recommendation engine powered by Fluid XPS.

For example, you could be asked, “where do you plan on using this jacket?” and “what activities do you plan on carrying out?” It even asks you to type in the colour you prefer – which feels more personal than clicking on a colour swatch.

Converse with the system and customers receive outerwear recommendations that are tailored to their needs.

Curious, we tried out the XPS system for ourselves. We were on the hunt for a light, rainproof jacket suitable for cycling in Dublin. Instead of having to trawl through the more than 400 jackets on offer, we were presented with the three best-suited products.

Indeed, one commentator says that a refined system with personalised suggestions benefits the retailer because it eliminates the Paradox of Choice – where customers opt to make no purchase at all when they are given too many options. Because of the baffling array of choices available, customers often resort to impulse buying – a study by Deloitte shows that 20 percent of all money spent during the holiday season is on impulse purchases.

According to Venturebeat, users who provided feedback rated the experience as 2.5 out of 3, and 75 percent said they’d use it again. The technology generated a 60 percent click-through rate of customers buying the recommended product.

While The North Face might have millions to invest in machine learning, smaller businesses can also benefit from applying similar technology to its sales techniques. Click here to read how Big Data can benefit small businesses.

Focus on customers – not where they do their shopping

Increasingly, retailers are focusing more and more on ‘omni-channel customers’ – customers who shop with a retailer both in-store and online.

Google published a study two years ago which showed that omni-channel shoppers have a 30 percent higher lifetime value than those who do their shopping in physical stores or online-only.

Already, retailers are seeing the benefit of a 360-degree approach. Many experts thought that Best Buy would struggle to cope on the back of Amazon’s influence, but the brand has been so successful that the Wall Street Journal is writing articles with headlines like ‘How to Fight Amazon.com, Best Buy style.’

Best Buy used to have a retail system in place which told customers that an item was out of stock if it wasn’t available in a Best Buy warehouse – even if its bricks-and-mortar stores stocked the item.

Best Buy was kneecapped by poor communication: its online stores had no way of talking to the in-store inventory system. To remedy the problem, Best Buy brought in an integrated system based on eliminating data silos – and now Forbes says that Best Buy stores, “do double duty as ecommerce warehouses with half of online orders picked up or shipped from a store.”

Be brave – if you dare

Black Friday and Cyber Monday are a huge part of the Christmas shopping ecosystem. Every year, news reports detail shoppers getting into fights and desperate night-long queues to score a TV for $100.

American outdoor clothing company, REI, had a novel approach to the queues and huge sales. It looked at its customer data and realised that while they liked a bargain, the true incentive was being in the great outdoors.

So, REI decided to opt out of Black Friday and shut its stores, giving its 12,000 employees the chance to spend the day outside instead. The plan, called #OptOutside, was downright brave – but it paid off, big time.

The hashtag #OptOutside was recorded more than 37,000 times on social media and the campaign was covered on most of the morning TV shows in the US. Perhaps most surprisingly of all, 150 additional retailers and the US National Parks department followed suit and joined #OptOutside too.

We’re not saying that every retailer should shut down to connect with customers. But REI looked at its data to see what its customers liked – and the return was more than worth it. Shouldn’t you do the same?

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