Product Recommendations
Build brand loyalty using personalisation.
We’ve all experienced companies recommending new products due to items we have previously purchased on their website. But with so many companies vying for our custom, it is vitally important that what they are suggesting is accurate to encourage repeat purchases.
According to a study by Smarter HQ, 70% of millennials are frustrated with brands sending irrelevant emails.
It’s never too late to re-engage with a potential customer and let them know the products that will entice them back to your site. Every customer is unique and it’s vitally important to celebrate that to help increase brand loyalty, in turn amplifying your revenue and boosting your conversion rate.
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How it works
By making your customers feel valued, accurate product recommendations come with major benefits.
Boost your orders
Significant uplift in Average Order Value (AOV) and increase in click rate.
Improve your UX
A smoother and more personalised customer experience.
Repeat business
Increase brand loyalty through personalisation.
About Product Recommendations
What Are Product Recommendations?
SaleCycle’s recommendation engine is a machine learning solution that suggests relevant products by learning the behaviour of visitors that have purchased items on your website. Our solution leverages the vast volumes of data we collect to provide more insightful and intelligent recommendations to your customers.
The results of a study by Accenture indicated 91% of consumers say they are more likely to shop with brands that provide offers and recommendations that are relevant to them.
Initial testing of cart abandonment campaigns using this solution against our previous recommendations engine indicated an Average Order Value (AOV) increase of 18%.
SaleCycle’s new engine uses “collaborative filtering”. This technique utilises data from user purchases to generate item recommendations based on users who have purchased the same items. The engine then utilises the algorithm to understand correlation between items being purchased together.
SaleCycle are continually improving and evolving our recommendations engine, ensuring our clients can personalise their customer’s experience as accurately as possible.
