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Your Nightmare Before Christmas - Shopping Basket Abandonment

9th Dec 2015
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It has to be one of the most frustrating sights for an e-commerce retailer to see - a shopping cart full of items, carefully chosen and ‘clicked on’ by the shopper, and then left abandoned in their shopping basket before they reach the checkout.

Christmas is the busiest time of year for retailers. In fact, many retailers make more than half of their sales and profits between the months of October and December. In the United States, it has been calculated that a quarter of all personal spending takes place during the Christmas holiday shopping season and so called ‘Cyber Monday’ – the first Monday after the Thanksgiving Holiday  – is now recognised as the busiest online shopping day of the year. It is looking as if total sales over the four-day shopping event has surpassed £3 billion in the UK, according to The Guardian. In the US, sales has topped off at $2.98 billion according to USA Today.

So it may come as a surprise that a recent Forrester report, Channel Management: Core To Your Customer Service Strategy, has revealed that 55% of US online shoppers are likely to abandon their online purchase if they cannot find a quick answer to their question. This shows that retailers could be missing out on even higher revenue and profits during the holiday season.

It’s true that abandonment tends to be somewhat lower at Christmas (when there is a greater urgency to buy gifts by a set deadline) and, of course, it may not be possible to persuade all shopping cart abandoners to go through to the final checkout – but it’s still worth looking at why this happens and what can be done to stop it happening quite so often.

A significant percentage of these ‘abandoners’ are persuadable and with a little bit of help would probably continue their ‘customer journey’ all the way along to the checkout (Some of the abandonments are accidental of course, for example, because the website crashed or when the page timed out due to lack of activity).

The most successful shopping experiences are those that are positively guided, and clearly encourage visitors to add a product to their cart with the minimum of time and effort.


Some of the reasons given for abandonment are things like ‘being presented with unexpected delivery costs’, ‘having to create an account’, ‘payment security concerns’ or ‘finding the website navigation too slow or complicated’; but whatever the reason, both the customer and the retailer end up suffering as a result.

The customer spends time and effort on a process, at the end of which, they fail to accomplish anything, while the retailer ends up with no sale and ultimately reduced profits.

Many of the problems which online shoppers report are relatively simple to resolve and, in real life, could probably be solved by having a sales assistant on hand to smooth the process.

How to create an account or questions about payment could be quickly and reassuringly answered if there was someone standing by, looking over your shoulder, metaphorically speaking, and intervening at the appropriate moment without being too pushy or trying to sell you things.

Live Chat

Increasingly, organisations are turning to live chat and virtual agents to provide customers with an ‘invisible sales assistant’ who can help them out and make them feel valued while they’re browsing from the comfort of their sofa or even on the train on the way home from work.

Both chat and virtual agents help to close the gap in customer experience between online and offline channels, offering online customers with the same level of assistance that they might expect to find in a real life, bricks and mortar shop.

Of course live chat is pretty good most of the time: for customers in a hurry, it means a quick answer to a query. A 2010 Forrester report ‘Making Proactive Chat Work’ found that ‘44% of online consumers say that having questions answered by a live person while in the middle of an online purchase is one of the most important features a Web site can offer’.

But live chat is rarely integrated with information about the product being browsed or with the stored history or any context about the customer’s past buying or browsing history. Not only that, but there is often no linked up communication across the various sales channels. Busy customers do not want to have to keep repeating information about who they are and what their query is every time they contact a supplier.

Chaining customers to silos of information and customer touchpoints is time-consuming and annoying and, ultimately, counterproductive as many potential sales will go unfulfilled. Retailers should aim for a truly seamless online experience, which in turn drives customer satisfaction and boosts savings.

Predictive Analytics

More sophisticated technology that uses predictive analytics - Predictive Sales Chat – identifies customers who could benefit from additional help to make a buying decision and then intervenes with an offer to ‘live chat’, if that’s what it takes to get to the checkout.

Predictive analytics has been used across business platforms to find patterns and figure out trends. It can help recognise the patterns of behaviour generated by individual customers - for example, regular cart abandonment or cart abandonment at a particular stage of the buying process - based on the data gathered and then segment it.


The other key point here is that only those customers who look like they may need help are approached. This is a different approach to traditional CRM solutions which don’t make use of customers’ past buying and browsing histories and so are more indiscriminate in which customers they ask to ‘live chat’.

Identifying only those customers who could benefit from additional help to make a buying decision – ‘serious’ shoppers you might call them, not recreational browsers who are not likely to complete an online sale - is the key here.

Proactive assistance must always be selective, so that resources aren’t wasted. If the shopper is successfully navigating their journey on their own, then there’s probably no need to interrupt them with distracting offers to chat or contact customer service as the aim is to limit the ‘cannibalisation’ of self-serve as much as possible. 

The problem with an unwanted pop up ‘do you want to chat?’ message is that customers will just ignore it and the goal here, we mustn’t forget, is a high chat ‘acceptance’ rate amongst ‘hot prospects’. People who are comfortable with several buying channels and who look around, doing some product research before buying, are top of that list of hot prospects and that is where predictive analytics will score best.

Predictive analytics can help predict which customers are likely to abandon their carts – maybe because they’ve done it before, they’ve had problems setting up an account or they struggle with the checkout process - and then provide corrective action, leading to a successful outcome for everyone involved.

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