Fashion brand, Princess Polly, is seeing a 66 per cent increase in online sales from petite size fashion shoppers – and a 61 per cent increase from tall size shoppers – when they click on a personalised home page category menu that targets an affinity for those clothing sizes. This category menu displays personalised menu bubbles that allow shoppers to click through to dedicated category pages for the company’s tall or petite collections.
This is just one of the ways in which Princess Polly is using Nosto, an intelligent commerce experience platform, to deliver personalised shopping experiences. Nosto allows the brand to automatically segment visitors based on their online browsing and shopping behaviour, including their size, colour and product affinities.
“The petite and tall category bubbles we deliver through Nosto are great for discoverability, since we’re always adding new sizes to our catalogue,” said Melanie Huang — UX eCommerce manager at Princess Polly. “And they’re only displayed to visitors who have shown an interest in those clothing sizes.”
Princess Polly was founded in Australia and now sells its fashion globally, including in the USA, UK and Europe, with a mission to make on-trend sustainable fashion available to everyone.
The brand is also benefiting from using a variety of Nosto’s personalised product recommendations that use AI-based machine learning algorithms. Shoppers who interact with the recommendations are 2x more likely to make a purchase, with a 21.6 per cent higher average order value and 2.5x higher average visit value (AVV).
On every product detail page, for example, Princess Polly is using Nosto to display a ‘similar styles’ product recommendations module that shows visitors other items that are similar to the item they are viewing. If they are looking at a blue mini dress, they are shown other blue mini dresses in a similar style.
Using Nosto’s AI machine learning based ‘cross-sell algorithm’, the recommendations take account of what else other customers who viewed the same product have also viewed or purchased, while filtering for product colour and style. Only items that are in-stock in the shopper’s preferred size are included (providing they have shown an interest in a particular size).
Claire Miller, Princess Polly’s eCommerce manager said: “We have thousands of products in our catalogue and when customers land on our site we want to make sure we serve the right products to them. We’re constantly trying to meet customers where they are to give them a familiar, easy shopping experience and Nosto plays a huge role in that.”
The similar styles product recommendations are also used whenever a shopper lands on a product detail page and finds that their size is out of stock. If they sign-up to be notified when that item becomes available, they are automatically shown a pop-out window of recommendations showing other products in their size with a similar colour and style. Since going live earlier this year, this campaign has helped to boost Princess Polly’s revenue from product recommendations on product detail pages by 2.8 per cent .
“Instead of bouncing off the site after signing up to be notified about an out-of-stock product, shoppers can continue shopping with items that are similar to what they were looking for, providing a more seamless shopping journey,” said Miller. “It’s a way of avoiding a disjointed shopping experience.”
To encourage purchases from first-time visitors specifically, Princess Polly is using Nosto to drive a campaign that triggers a personalised pop-up with a 10 per cent off discount code if it looks like a new visitor is about to exit without making a purchase. This contributed to a 2.5 per cent increase in sales in the month following its launch.
The pop-ups are personalised with images tailored to whether the visitor has shown an interest in either dresses or tops (otherwise a generic image is shown). And Nosto’s segmentation and personalisation tech ensures that the pop-ups are only shown to first-time visitors who have viewed at least 2 pages – which is a good indicator of purchase intent.
On its mini-cart, Princess Polly has previously focused on a product recommendation that shows a single accessory which can trigger a quick, easy purchase decision. The company has avoided recommending items that could disrupt the purchase process or lead to an abandoned cart by driving shoppers back to product detail pages to choose sizes and colours, for example.
However, with the help of A/B testing through Nosto, the company has been able to test and develop product recommendations that are effective at showing shoppers a pop-out summary of product detail pages which allow them to choose sizes and colours, without leaving the mini cart. These contain ‘recently viewed’ recommendations that seek to increase order value by providing a final reminder of products that shoppers might have browsed while on-site. The result is a very effective product recommendation feature that has a conversion rate that’s more than 2x higher than the site average.
Miller said: “We are always willing to try out new things and because Nosto offers us that data and A/B testing functionality – it’s very easy to do.”
Share