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by Phil Birss
3 min read
5 personalisation techniques we can learn from ASOS
Author: Phil Birss
Posted in Performance Marketing on 23rd May 2019 12:00 am
“By 2020, personalisation technology that recognises customer intent will enable digital businesses to increase profits by up to 15%” (Gartner)
Stats like this make it difficult to ignore the power of personalisation. Ecommerce sites in particular are really starting to harness their customer data to provide completely unique user experiences and help boost sales.
One that stands out in particular is ecommerce giant ASOS. They use some incredibly clever (and sometimes subtle) personalisation techniques that any online store could benefit from.
We’ve looked into some of the most common personalisation techniques being used today, and how you can take advantage of this ever growing trend.
We learn a lot about a user the first time they browse your site. From then on, we can make assumptions about their behaviour for subsequent visits.
As you can see above, first time browsers are presented with a gender neutral page directing people to either ‘shop women’ or ‘shop men’. As soon as we browse women’s, from then on we’re presented with a homepage completely focussed on womenswear.
A more recent addition to ASOS is its ‘Fit Assistant’. From a user’s purchase / return history, this machine learning algorithm will recommend which size they should choose for future purchases.
It can even go one further, and if you’re happy to share more insight into your height, weight, shape and fit preference, it can provide a more exact recommendation every time.
ASOS sells hundreds of different clothing brands all with varying size guides, so this ‘digital assistant’ is a welcome addition to the ecommerce giant. Personalised size recommendations are really helping to minimise the risk of disappointment after waiting days for that parcel to arrive, only for the product not to fit. Conversion rates are higher, and return rates are lower…
A common feature of ecommerce site, and one that ASOS does particularly well is constantly reminding you of your ‘recently viewed’ products. A user might visit a site multiple times and go back and forth when making their decision, so a recently viewed section acts as personalised selection of clothes that we know the customer is considering. It can really help to seal the deal and lock in that sale that’s been bubbling for weeks.
ASOS also makes use of the vast amount of customer data it holds by providing each user with their own personalised ‘edit’. By analysing past behaviour such as purchase history, saved items and added to cart, you’re presented with a tailored suggestions of products which ASOS calls ‘your very own personal stylist’. It aims to save you browsing through the thousands of products it holds on site, and displays products you’re highly likely to be interested in.
While the above feature uses machine learning to display more personalised product to users, this feature allows the user to provide their preferences in person.
We’re taken through a short questionnaire asking us to choose our favourite products / brands from a small selection. From then on, ASOS uses this data to once again display products we’re more likely to purchase.
ASOS are certainly the king of ecommerce, but implementing even just a couple of these features can drastically improve your bottom line.
As the personalisation trend grows and grows, and machine learning becomes smarter, now is a good time to get on board. If you’d like to discuss our ecommerce services or any of the above, just give us a call.
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