Home » Personalisation for eCommerce – how does it work?

Personalisation for eCommerce – how does it work?

Personalisation is a key trend within merchandising in eCommerce at the moment, but what does it actually mean? And how does it work?

When shopping online it is extremely likely that you have experienced some form of eCommerce personalisation, whether that was being directed to the correct department (Mens / Womens) based on your previous visit to that site or product recommendations based on your previous purchases. There are varying levels of personalisation being implemented currently by eCommerce businesses, but we are only going to see it increase.

So how does it work?

Any form of personalisation you’ll experience on an eCommerce website will be being driven by a personalisation engine or a product recommendation engine, like The Filter. It is a piece of software which integrates with the website itself and applies “machine learning” in order to personalise the experience for each individual user.

What is machine learning?

Machine learning is when software intelligently learns from data and then applies certain logic to its out. So in the case of eCommerce sites, when a user lands on the site, a cookie is registered and certain information like browsing behaviour and previous purchases are stored and monitored by the machine learning software via the cookie from which to “learn.” The software can then begin to deliver an experience for the customer, based on their behaviour.

Why do businesses use eCommerce personalisation?

Personalising the experience for a user on an eCommerce site through things like personalised product recommendations is more than likely to help increase both the user experience for the customer and therefore the conversion rate for the businesses.

If done well, personalisation should enrich the user experience and as a result increase the customer’s likelihood to convert, purchase more often and return to the site, all of which will contribute to a greater Customer Lifetime Value of that user for the business.

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