Shopping basket abandonment refers to users abandoning their journey on a site after having placed items in the shopping basket without purchasing them. Reasons for users to abandon vary widely, from a simple natural interruption, to hesitation or decision fatigue. Sometimes there is nothing that could have been done to prevent this, but more often than not, a few counteractive techniques can be used.
Especially when caused by hesitation or decision fatigue, there are some well-tried methods to minimise shopping basket abandonment.
The most successful one is using urgency messaging to highlight reasons why the user should buy from your website. For example, remind users about free delivery (and if the threshold for it is not met, display a £ countdown message to encourage them to hit it), offer free samples with every order, promote a time-limited discount code (maybe via an exit intent overlay that appears when intent to abandon is detected).
When users are on your basket page, the ideal scenario is to avoid distractions at all cost. For that reason, web designers often make it easy to proceed to the next funnel page, whilst making it a lot more difficult for users to return to the main site (Amazon’s checkout page is a good example of this). Although it seems like a good idea, users can get annoyed with this, so don’t forget to AB test this thoroughly if you elect to go down the hard distraction-free route.
Keep the basket page as clean and functional as possible to encourage users to proceed with their order immediately; summarise all relevant basket contents information neatly, be clear about delivery costs and clarify what the next steps are with a progression bar.
Webtrends Optimize can help you minimise the impact of shopping basket abandonment using tools like urgency messaging (“You have 10 minutes to check out”), social proof (“10 people recently bought this hotel”), exit intent (“Leaving so soon? Enjoy a 5% discount on your order today only”) or simply by testing the format of your funnels pages via AB or split testing.
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