British Clothing Retailer Joules Christmas Strategy
Generic is out - customers today value personalisation in almost every aspect of their lives, from social media to online shopping.
75 percent of customers are more likely to buy from a company which knows their name and recommends products based on their purchase history. In fact, 78 percent of those customers say they will only engage with a brand which is able to offer personalised recommendations based on previous interactions. 63 percent of consumers find generic and spam communications irritating and would think more positively of companies if their messages were more personalised.
Perhaps most interestingly of all, 77 percent of customers have chosen, recommended, or even paid more for a brand which offers personalised recommendations or services.
It's with these facts in mind that British clothing retailer Joules wanted to supercharge its product personalisation capabilities.
Joules recently enjoyed one of its most profitable Christmas periods to date, with an 11.7 percent year-on-year boost to sales in all arms of the business - including ecommerce. Ecommerce accounts for 35 percent of Joules' revenue and is growing by 20-25 percent each year.
"I am pleased to update on a continued strong retail performance for Joules through the important festive trading period, which represents an improvement from the retail sales growth in the first half of the year," said Chief Executive Officer at Joules, Colin Porter. "This good growth was achieved despite the ongoing backdrop of challenging sector trading conditions. The group's performance was again underpinned by the strength of the Joules brand, our growing and loyal customer base, and the flexibility of our 'total retail' model which continues to enable Joules to adapt to changing customer shopping behaviours."
One of the key innovations which is allowing Joules to continually adapt to changing customer behaviour is its adoption of an intelligent recommendation engine.
Joules wanted a platform which could help it serve its customers with faster, more regular, and more relevant personalised recommendations than ever before - especially for its younger customers. Younger shoppers carry out much of their brand interaction via their smartphones, necessitating a personalisation platform which can meet them where they are and target them with up-to-the-moment recommendations.
"We want to be recognised by our consumers as giving them relevant experiences that are more personal," said Ecommerce Customer Experience and Analytics Manager at Joules, Jas Chana. "Everyone wants to get to 1-to-1 personalisation, and for us the most scalable way to do that is through recommendations. No matter the channel via our ecommerce site, via clienteling and styling, in-store experiences, and even through what we're sending out in our parcels - recommendations will be a cornerstone of how we provide personalised content to our consumers."
The intelligent recommendation engine implemented by Joules allows the company to deliver personalised content to its audience based on numerous factors.
Most importantly, the platform allows Joules to leverage the power of its vast database of customer data - age, location, shopping habits, previous purchases - and combine that knowledge with behavioural data regarding what customers are doing at that moment. One example of this would be regarding mobile interactions. Joules knows that when customers log on via mobile, they are looking for faster transaction-specific interactions, and so the platform allows Joules to target them with content which fills this need.
Automation plays a large part in this interaction, but not without the support of manual processes.
"Such intricate audience precision would be unthinkable without the help of automation," continues Chana. "We wouldn't be able to create curated looks for every product we have on the website, that would be an impossible undertaking. We would need to build endless product sets with the necessary breadth to cover gaps due to out-of-stock items, and manually upload a spreadsheet for each dataset. Therefore, a combination of automated recommendations and manual styling feels just right. We have implemented recommendations on the basket page, based on insights about the product the customer has in their basket and knowledge about the customer context."
Data is playing a big role in the automation of personalised recommendations, as well as and the increase in recommendations intelligence. It's great to see brands such as Joules finding ways to deliver ever more relevant content to its audience while also seeing results in its bottom line.
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