You need only take a look at Amazon’s homepage to understand the importance of product recommendations to ecommerce.
One report suggests that 70% of Amazon.com is devoted to recommendations, so it’s obvious that they play a vital role in exposing customers to new products and increasing sales.
In fact, according to an infographic from Monetate recommendations can increase revenue by up to 300%, improve conversions by 150% and help boost the average order value by 50%.
Obviously these figures will vary wildly depending on initial benchmarks and how extensively recommendations are used across the site, but the evidence is still too compelling to be ignored.
And in truth you’d be hard pushed to find a site that doesn’t upsell alternative products in shape or form – however there are a number of different methods that can be employed.
With this in mind. I thought it would be useful to take a look at several of the different ways in which ecommerce sites recommend products…
ASOS’s new ‘Complete the look’ button
We frequently praise ASOS as an online retailer that leads the way in terms of innovation and best practice, and it recently launched a new method of recommending item on it product pages.
As is frequently the case with ecommerce sites, ASOS displays its products using models who are styled with a range of other clothes available on the site.
This not only shows the customer how the clothes actually look on a real person, but is also a useful way of suggesting other items the customer might want to buy.
ASOS has always attempted to upsell the other clothes worn by its models with a section titled ‘Complete the look’ on the right of the screen, but it has now added a new ‘Buy the look’ call-to-action that enables the customer to purchase all the items from the same screen.
It’s a really effective way of recommending products as the shopper can already see that the items fit well together on the model, and can now easily add them to the shopping basket without having to navigate around the site to four different product pages.
Other customers also viewed…
John Lewis uses a product recommendation tool that provides customers with suggestions by analysing shopping behaviour alongside the relationships between products and product categories.
It was credited for helping the retailer achieve a 27.9% increase in sales during Christmas 2011.
John Lewis head of online delivery and customer experience Sean O’Connor told us that the tool, provided by RichRelevance, is tuned into “crowd shopping”.
This takes into account not only what the individual customer is doing on the site at that moment in time, but also what other shoppers who are similar in product views have done before.
We feel this is the very essence of social shopping: taking into account not just the individual customer’s experience but those of the wisdom of the crowds.
For more information about John Lewis’ success in ecommerce check out our blog posts on the reasons behind its recent 44% increase in online sales and a Q&A about the ingredients of its successful multichannel retail strategy.
While most product recommendation tools appear on product pages, some retailers take a more proactive approach by asking shoppers a questionnaire upfront and then recommending products based on their answers.
I recently blogged three examples of sites that adopt this method, including snowboard retailer Burton.
Burton uses a Board Finder tool to give product suggestions based on the customer’s vital statistics including height and weight, level of ability, and their preferences for speed, flex and board design.
The results are then presented with percentage rating based on how well the board matches your answers.
To further personalise the experience, Burton explains why it has made these recommendations and the difference between each style of board. There’s even a short video clip to further illustrate the attributes of each design
Personally I’m not a huge fan of this exact approach, as using a percentage rating and suggesting that the customer is 100% matched to a particular product risks undermining their trust in the tool if it turns out the clothes don’t fit.
Top sellers from a specific brand
It’s fairly common to see ‘Most popular items’ recommendations on ecommerce sites, but John Lewis gives it a slightly different twist by displaying top sellers from that particular brand.
So if you’re looking at a Ben Sherman shirt, then at the bottom of the screen you’ll see ‘Ben Sherman top sellers’.
Consumers are often loyal to a particular brand, so it’s a great idea to base recommendations around this shopping behaviour.
Amazon’s overwhelming options
Considering Amazon’s massive success in ecommerce it should come as no surprise that it does a great job of recommending products. But it’s worth pointing out a couple of the different ways it goes about it.
The product pages include categories for ‘What other items do customers buy after viewing this item?’ and ‘Frequently bought together’.
The latter option takes a similar approach to ASOS’s ‘Complete the look’ tool as it allows shoppers to add three products to their shopping basket in just one click.
This is a brilliant way of taking a more active approach to product recommendations, as it encourages shoppers to make an impulse purchase on the spot rather than requiring them to navigate around the site to view the other product suggestions.
And Amazon doesn’t relent even after you’ve made a purchase – on the order confirmation screen there are five different categories of recommended products.
This includes ‘Related to items you’ve viewed’, ‘New for you’, and ‘Recommendations based on your order’.
But personally I think the most interesting category is ‘What other customers are looking at right now’, as it’s essentially a different take on the more common ‘Most popular products’ but with an added sense of urgency.
It shows how a fairly simple change in copywriting can give a very different emphasis on product recommendations.
Naked Wines’ ‘What’s happening right now?’
This feature is similar to Amazon’s ‘What other customers are looking at right now’ tool; however it is more persuasive as it includes the name of the customer who has ‘liked’ or bought the product.
Naked Wines’ business model is based around a community of wine lovers who use the site as much as a discussion forum as they do for buying wine.
As everyone is logged in, often through Facebook, the product suggestions in this tool carry more weight as you can actually see who is making the recommendation.
This is a great example of adding a social element to product suggestions, which is is far more effective than displaying anonymous recommendations or reviews.