I was looking at a sports jacket the other day. This was at a clothing store that had the words ‘Sale’ plastered across it, which caught my eye as I walked past. I decided to step in for a bit and see if there was anything interesting, more out of curiosity than anything else.

The jacket was dirt cheap after all the price cuts, so I threw it on to give it a test drive. As I was looking at myself in the mirror, a sales rep sidled up to me and told me it looked great on me. I knew he was paid to say that, but I still smiled. It did look great on me.

“You know what would go better with that jacket,” he said. “Dark jeans.”

The jacket was dark, and I was wearing light jeans. I looked in the mirror again. Maybe he was right. Wouldn’t hurt to try out some dark jeans and see if it looked better.

When I came back out wearing the jacket and dark jeans, the sales rep had a light blue shirt in his hand. “This would complete the look better than the yellow t-shirt you’re wearing,” he said.

I had walked in there out of curiosity, but I was walking out with an entirely new look. With a few well placed product recommendations, the sales rep had converted an uncertain $40 purchase into a certain $100+ sale.

That’s the power of product recommendations, and it works online as well. In this post, we’ll look at how you can use product recommendations on your eCommerce store to up-sell and cross-sell customers. Let’s start with some hard numbers.

Why Use Product Recommendations?

When you visit the Amazon homepage, most of it is just product recommendations. Amazon collects data about your past shopping habits, combines that with data points from other similar shoppers and products, runs it through a magical algorithm, and serves you product recommendations you’re most likely to purchase.

We’ll look Amazon later in this article, but they aren’t the only ones using product recommendations. In fact, each of the top 10 websites in the Internet Retailer 500 use product recommendations. Why? Because it’s so effective!

Research shows that, on average, 2% to 5% of a store’s revenue can be attributes to product recommendations. In some cases, it’s as high as 20%. More importantly, retailers report that product recommendations have increased key performance indicators like revenue, conversion rates, and Average Order Value (AOV).

[Tweet “15% of online shoppers have purchased a recommended product”]

Convinced yet? Let’s look at how some online retailers use product recommendations, and what results they’re getting from it.

Case Study 1: Amazon

No two Amazon home-pages are the same. It’s different for every shopper, and it changes each time you visit the store. Amazon’s algorithm quietly runs in the background, always collecting data and trying to anticipate what products you want before you know you want them.

It’s not just the homepage. Head to any product page and you’ll see multiple rows of recommendations, each based on a different algorithm – ‘Frequently bought together’, ‘Customers who bought this item also bought’, ‘Customers who viewed this item also viewed’ and ‘Your recently viewed items’.

It doesn’t even stop there. Amazon has recommendations for your cart – ‘Frequently bought with the item you added’, ‘Customers who bought the item you added also bought’, ‘Customers who shopped for the item you added also shopped for’, and ‘Customers also bought these highly rated items’.

Amazon product recommendations growth hack

Hang, on. We’re still not done. Amazon has even more recommendations on the confirmation page after you purchase a product! It’s unclear what percentage of their revenue comes from product recommendations, but it’s obvious that they put a lot of effort into helping customers discover the right products.

Related posts:  eCommerce Heatmaps for Better Customer Interaction and Conversions

Case Study 2: ASOS

ASOS is an online fashion retailer that recently started using product recommendations on their store. They don’t have access to the mountain of data that Amazon does, so they went about it differently.

Because ASOS sells a number of different clothing items, they know what goes well with what. Just like with the sales rep at the store I shopped at, ASOS has an online ‘Shop the look’ feature that recommends which clothes go well with the one you’re looking at.

For example, if you’re looking at a jacket, ASOS has a matching shirt, jeans, and shoes to go with it. This is a great cross-sell feature that’s not too hard to implement because it doesn’t require you to track shopping behaviour.

ASOS product recommendation growth hack

Simultaneously, ASOS also has a ‘You might also like’ list where they recommend similar products to the one you’re viewing. Again, this is pretty simple to implement because it’s category based rather than behaviour based. It’s also a great opportunity to up-sell customers and show them higher priced and better-quality items as an alternative.

Implement The Growth Hack

You don’t have the resources that Amazon does, but that’s not a problem. Like ASOS, you really don’t need to track every single move your shoppers make and create complicated algorithms. Something as simple as manually creating a list of related products for your customer to browse is good enough. In fact, if you don’t sell too many products, this is actually the best way to go about it.

The best part is, there are pre-built solutions out there that you can integrate with your eCommerce store. Some eCommerce platforms, like LemonStand, already have a built-in feature for this, which means your work becomes a lot easier. Here’s what you need to do in LemonStand to get those ASOS-like features.

Step 1

So in the ASOS example, we’re looking at a sports jacket product page, and the complete the look section has three other items. In your LemonStand backend, head to the sports jacket product in edit mode and scroll down to the ‘Related’ section. Here, you’ll need to pick out the other items that complete the look, in this case a pair of shoes, jeans, and a shirt.

LemonStand product recommendations growth hack

Step 2

Now you’ll want the related products to manifest in the product page. Head to the theme code and drop in this piece of code where you want the section to go –

{% if product.related.count %}
<h1>Complete The Look</h1>
<ul class="row">
{% for relatedProduct in product.related %}
<li class="four columns mobile-two">
{% if relatedProduct.image %}
<img src="{{ relatedProduct.image.thumbnail(120, ‘auto’) }}" alt="{{ relatedProduct.image.title }}" />
{% endif %}
<a href="{{ site_url(‘/product’) }}/{{ relatedProduct.url_name }}">{{ relatedProduct.name }}</a>
{% endfor %}
{% endif %}


You’ll notice here it says ‘Complete the look’, but you can make it ‘Shop the look’ or anything else you want. It’s also four columns but you can change that to three if you need to. In fact, you can customize the whole section any way you like.

And that’s it! For more information, have a look at the documentation.

Time To Growth Hack

By recommending products to shoppers on your site, you’re hitting two birds with one stone. First, like Amazon, you’re creating a more delightful shopping experience for your customers. Second, like that retailer store I visited, you’re increasing your Average Order Value and revenues.

If you could increase your average order value by just 10%, how much extra in yearly revenues would your store earn? Let us know in the comments!

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