Recommendations To The Rescue

With more than 2 billion online shoppers, brands have to be sure to keep their digital platforms up to date and anticipate any inconveniences that may arise from virtual shopping.

A vital aspect that differs between online and in-store experiences is access to inventory. When physically roaming the stores, you have the freedom to check every rack and shelve for items, as all options are plainly laid out for you to see. Whereas, online, your exposure is somewhat limited to the number of items that fit on your screen. For retail shoppers in specific, scrolling and browsing through what seems like a never-ending number of pages is a big NO.

For this reason, it’s important to give shoppers options to selectively view items they are interested in, leading us to the accommodating service known as Recommendations. This futuristic trend is becoming more and more popular with online stores, often helping boost sales and drive traffic to digital platforms. To illustrate how this solution can come in handy, we’ve paved a hypothetical user journey for you to experience the magic firsthand.

Recommendations by Category

Starting with the most generic, this solution is the base to all others. It detects the general category you have searched for and displays all the items available in store that fall under the same category. For example, if you are looking to spice up your winter wardrobe with a new coat, the solution will recognise “coat” as a keyword and display all available coats in the catalogue to choose from with no specific filters applied. Although this is a recommendation solution, it already exist among almost all platforms (we hope), and doesn’t specifically contribute any unique advantage.

Recommendations based on Buyer/User behavior

When this solution arises in the shopping journey, an algorithm uses previous user behaviour to anticipate what your next move is. Popular examples exist within companies like Amazon or Netflix, where data patterns reveal the most popular items based on common trend. This can be done with fashion, but your representative style and taste is subjective and shouldn’t be crunched up in a pool of data – but we’ll get to that later.

Recommendation based on Previous Purchases

Let’s assume you are at the end of your shopping journey, a coat in your basket, along with a couple of more items, and you are ready to check out. Before doing so, the system dives into your file and picks up a buying pattern of prior hat purchases. With this information, it generates a final recommendation based on what it already knows about your preferences. This can often come in handy, but can be seen as annoying in alternate circumstances. For example, assume you recently attended a baby shower and gifted the mother-to-be a little suit for her unborn son. With this history in mind, the algorithm may start generating children’s options before you check out, which may throw you off your shopping game.

Similar Recommendations

Now, welcome to the future. This solution is the most innovative of all, with a scarce added ingredient of Visual Artificial Intelligence. To steer clear of confusing technical terminology, let’s paint a picture: Say you discover a stylish leopard coat on Instagram that you must have. But once you enter the product page, your size is out of stock. Don’t panic! Our technology will read the leopard attribute and generate options with similar colours, cuts, patterns and prints based on your size and filtered preferences where applicable. The twist? You will know you are not wasting your time because the generated results appear in real time and reflect all similar items in stock in the moment of shopping! (Ps. This solution is one of our specialties here at Wide Eyes… Tell your friends)

And, check out! Don’t you feel confident in your purchase, having scanned a precise list of all possible customized alternatives? Yep, we know..

Basically, Recommendations exist on almost all online platforms. It is up to retailers to choose which solutions best represent their brand’s digital store. Our job at Wide Eyes is to provide your favourite brands with this magic, making sure they make use of all collected data to create the best possible experience for YOU! Similar Recommendations can solely guarantee that, and it’s just ONE of our solutions. If additional Virtual AI solutions were added to the mix, can you imagine the shopping power you would have at your fingertips?

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