Helping shoppers find products that they want to buy is an essential part of turning them into customers. In the world of retail, both online and offline, a lot of effort goes into organizing stores, signposting items and helping people find their way towards the things they want. But not every purchase is planned, consumers spend a lot of money on impromptu purchases, the items that they perhaps didn’t realize or remember they wanted or needed until they saw them.
This is one area where personal recommendations can have a significant impact on a person’s buying habits. In a brick and mortar store, a savvy assistant can recognize a customer’s tastes and take on board their description of what they’re hoping to find, then lead them towards a selection of goods that they might buy.
But for online stores, an ecommerce recommendation engine performs the work of your best salesperson – and then some. Using algorithms and machine learning, identifying relevant products to recommend is a much quicker process – and often much more accurate – than relying on a human brain. It can also search the entire store catalog, pulling out appealing products even from inventories containing thousands or even hundreds of thousands of items.
Recommendations are getting smarter. Sentient Aware is an AI-powered ecommerce recommendation engine that understands products at a level beyond the traditional use of tags or algorithms based simply on other shoppers’ behavior. It learns more about a customer’s tastes with every interaction, allowing stores to make increasingly personalized recommendations, picking out items based on each individual’s habits and tastes.
Intelligent recommendations are one of the most effective ways to optimize your site, boost your conversion rates, promote your inventory and secure more sales, increasing the value each customer offers to your business. When used well, product recommendations can also keep your most valuable customers coming back to your site again and again. You know what they want, and you’re making it as easy as possible for them to find it and buy it.
What is an ecommerce recommendation engine?
An effective ecommerce recommendation engine allows you to laser target the right products to customers at multiple touch-points, through different pages on your site as well as across a variety of pre and post-sale marketing channels. It learns about a customer’s preferences, their level of buyer intent and shopping habits, using that knowledge, as well as data collected from other buyers displaying similar traits, to make personalized recommendations for products or add-on services that are particularly relevant.
Intelligent recommendation engines improve with every interaction, learning more about what is important to each individual visitor, allowing it to make increasingly more accurate suggestions that are more likely to appeal.
Personalized recommendations act as a filter to help shoppers quickly get to the stuff they want to see. Shoppers appreciate an experience that is tailored to them, while store owners like it too, as it makes their visitors more likely to find what they need and convert.
Taking online shopping behemoth Amazon as an example, you can see multiple instances of product recommendations in action. Amazon uses deep learning-generated recommendations at almost every step of the on-site journey – on category pages, product pages and even on the checkout page. On some pages, it’s estimated that over 70% of Amazon screen real estate is given over to recommendations. But it’s a tactic that pays off, as product recommendations drive 33% of the retailer’s revenue. And a third of Amazon’s revenue is a pretty big deal.
So where do you see these recommendations? Different stores take a different approach, but the technology behind recommendations is flexible enough to be adapted to various uses. Product collections, homepages and category pages can all be personalized to each shopper by using the space to display products most suited to them. When viewing a product page, it is common to see Amazon-style ‘Customers Who Bought This Also Bought’, or ‘Frequently Bought Together’ collections of items. Shopping carts also often serve up another chance to recommend related items, while follow-up marketing efforts can display items embedded in an email, powered by your ecommerce recommendation engine, encouraging customers to return and buy from you again.
Algorithms powering recommendation engines have often relied on previous purchases, previously viewed items or related products based on what other customers have bought. But Sentient Aware allows for in-the-moment recommendations, using artificial intelligence to analyze interactions and find visually relevant items that will appeal to each individual customer. This allows for fast and accurate recommendations that are personalized to each shopper.
It also provides an improved way of searching online, serving up recommendations based on a customer’s visual preferences, rather than relying on them to accurately describe what they want. For example, Sunglass Hut uses Sentient Aware to power ‘My Frame Finder’, a mobile-friendly visual search function that interprets a customer’s taps and swipes to present them with the sunglasses that most suit their individual style.
The benefit of recommendations to customers
Speed, ease and relevance are crucial traits that the modern consumer demands. With so much choice out there for where to shop online, shoppers lose patience if they don’t find what they want quickly on one store, as they know that there is an abundance of alternative stores available at their fingertips.
Personalized recommendations help to entice shoppers to stick with your store because they satisfy a lot of their demands. The content is relevant because it has intelligently identified what an individual wants. It is fast and easy because they see items they want to buy without having to spend time and effort searching for them. Personalized recommendations also add that extra bit of sparkle to the shopping experience, making customers feel ‘special’. These advantages for the consumer are part of the reason why more than 70% of internet users prefer content that is personalized to them and why nearly half of shoppers spend more with a personalized ecommerce experience.
How ecommerce recommendations can boost your online store’s profits
When done well, relevant product recommendations can provide a boost across multiple levels of your marketing efforts, even across different channels, on and off-site. It helps you make the most of the traffic you have, optimizing the content for each user to increase your chances of securing a sale, while off-site communications can also be personalized, increasing the opportunities you have to bring customers back to your site to buy from you again.
Investing in an effective ecommerce recommendation engine can make all your marketing efforts more efficient. It is taking the traffic you already have and recommending relevant products to them at a time when they are often already in a position to buy.
Now let’s explore some of the ways you can use an ecommerce recommendation engine to grow your ecommerce business.
Increasing conversions through personalized merchandising
We’ve looked at some the ways that ecommerce recommendations can be used to shape your site’s content. Using data from current and previous shopping sessions, you can ensure each customer sees their own unique version of your store, from the homepage through to the shopping cart. Intelligent recommendations deliver the right products at the right time, and the business benefits of this are clear – it will help you sell more.
No one customer is the same, something that can lead to frustration for people shopping online, leading them to bounce off your site and look elsewhere if they don’t quickly see something that seems relevant or appealing. But by showing them items they want to buy, you are clearly increasing the chances that they will convert.
It also means you are able to showcase more of your inventory, without having to focus your merchandising efforts just on the top-selling items. Recommendation engines will scan your entire product catalog so that the right people will see the items that will appeal to them the most.
This can help you shift those slow-moving goods and maximize your entire inventory, delivering an improved ROI for your stock.
Saving a sale
For a shopper, there can be few things as frustrating as finding an item you love, only for it to be out of stock or not available in your size. It’s a situation that should be equally frustrating for a retailer too, as it means you’ve missed out on a sale.
But it doesn’t have to end up like that. Going back to the store assistant comparison, a real life helper may select some alternative items for you, showing you other similar styles on the shelves that match what you were looking for and are available in your size. And this tactic can be deployed with even more efficiency and speed with an ecommerce store.
The intelligent product recommendations powered by Sentient Aware can fill in for that store assistant, presenting carefully matched alternative items. Aware instantly scans the entire inventory for visually similar products, ensuring they are available in the right size, so a customer knows they are being presented with a viable and attractive option. This increases the chances that they will still buy from you rather than leave in search of the out of stock item on another stop.
Growing basket size
Many people focus on conversion rate as the key metric of conversion rate optimization (CRO). And of course, increasing the percentage of people who purchase from you can be a great metric on which to focus. But it’s only one facet of truly optimizing and growing a business. It’s best to think of CRO more as business optimization, as the focus should always be on how to grow your revenues and profit margins, not just raising the number of people who visit your site and purchase from you.
In fact, to put it into context, you could optimize your site in a way that actually sees your conversion rate drop but your profit levels grow. Say 10 visitors out of 100 buy a $5 item from you – that’s a 10% conversion rate bringing in $50 in sales. But then your ecommerce recommendation engine helps you to focus on the most valuable customers and helps them to discover more higher-value items. The design changes mean only 8 out of 100 visitors convert to customers, but this time they buy a $15 item, then discover another $25 item that they also buy at the same time. That’s $40 per customer, rather than $5. So despite your conversion rate dropping to 8%, you’ve grown your revenue from $50 to $320.
Of course, what would be even better would be growing the number of people who convert and growing the amount that each customer spends.
When done well, personalised ecommerce recommendations can help you do both. Customers see the most relevant products and they see more of them, more often. This helps you to improve your baseline conversion rate
Not only are you increasing the chances that a site visitor will convert into a customer, but you are also increasing the chances that they will buy more and spend more. They may have come looking for one product, but they’ve already got the credit card out and are ready to use it. So if they see something else that is relevant to them or related to what they are already buying, then there’s a high chance they will buy that too.
A customer buying one item is great. A customer buying two items is even better. An effective product recommendation engine can help to increase the average basket size by encouraging customers to add more items to their basket, spending more money with you. You haven’t spent any more money to acquire a new customer, but you have increased your profits, helping your traffic acquisition efforts deliver an even more effective return on investment.
Personalization is one of the most effective ways to develop customer loyalty. Tailoring the ecommerce experience to each individual ensures they find what they want quicker and they can complete their purchase quickly and efficiently. It also makes the experience more pleasurable and means they are more likely to return to your store in the future.
Every interaction makes the personalization even more accurate too, while processes such as checkout become quicker. If a customer perceives your store as relevant to them and knows they can quickly find items that match their tastes, then they are incentivized to come back.
So as well as encouraging customers to spend more in their initial visit, by recommending genuinely appealing add-on or related products, an intelligent ecommerce recommendation engine also creates a positive customer experience that means your customers are more likely to return to buy from you again and again. It can also turn your customers into brand advocates, as shoppers who’ve had a positive experience are nearly three times more likely to recommend you to friends.
Intelligent recommendations can also continue to power your marketing efforts even after a customer has completed a purchase or left your site. We’ve already seen how they are commonly used on checkout or cart pages. But you’re also very likely to have had follow-up emails from stores where you’ve purchased before. The content of these emails and post-sale messages will be even more relevant and persuasive if they include items that are likely to be of interest to you.
The same tactic can be used across display advertisements as well. Retargeting ads that follow you around the web with items that you left in your basket are a common sight for web users these days. But the data that can be pulled together about each user can also power ever-more persuasive and relevant new items to retarget consumers with, enticing them back to your site with personalized ad content.
The technology behind recommendation engines can be put to effective use in identifying related products that will appeal to your customers and encourage them to return to your store again and again.
Why ecommerce recommendations should be an essential ingredient in your marketing mix
The ‘four Ps’ is a popular model often used for looking at the traditional marketing mix, covering product, price, promotion and place. It works on the idea that effective marketing must focus on promoting the right products at the right price and in the right place. While advancements in the digital world have turned many marketing efforts on their head, a lot of the traditional principles still apply.
With an ecommerce recommendation engine, you are equipping yourself with an effective tool to really tackle 3 of these 4 key strategic principles. Essentially, it is giving you the ability to promote the right products to the right people at every step of the conversion journey.
By laser targeting recommendations to individuals, you can promote more of your inventory than ever before. It showcases the most relevant items to the people most likely to buy them – a far cry from throwing up billboards alongside a freeway in the hope that someone interested will just happen to drive past. It allows you to promote these items at just the right time, when you know a potential customer is already showing strong buyer intent. You can focus your recommendations on just the right places where they will have the biggest impact, whether that be in a follow-up email to re-engage a previous visitor, or on a checkout page when the shopper already has their credit card out and are ready to order.
Ecommerce product recommendations are becoming more accurate than ever before. That’s good news for customers, who can find what they want when they want it, and great news for retailers too, as they know that they can show the right products to the people who are most likely to buy.