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If you want to understand the importance of using recommendation engines, know that according to research, around "35% of what consumers purchase on Amazon and 75% of what they watch on Netflix come from product recommendations." Furthermore, research from Accenture suggests that "91% of consumers are more likely to shop with brands who recognize, remember, and provide them with relevant offers and recommendations."

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In simpler words, recommendation engines *deliver results.* They can be used to get customers hooked to your platform through a hyper-personalized shopping experience. We will deep-dive to understand how recommendation engines can improve product discovery by looking at real-world examples and applications. Let's get the ball rolling.

## **How Recommendation Engines are Boosting Ecommerce Product Discovery: 4 Real-World Examples**

Product discovery is an important factor for eCommerce websites to boost sales and enable a seamless customer experience. Here are four interesting strategies eCommerce brands can use to make their product easily 'visible:'

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**1. Similar products and shop-the-look carousels**

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Imagine if your customer has logged onto your eCommerce website and has to go through an inventory of 20,000+ styles of clothing. The chances of them leaving the website without making a purchase shoot up drastically, right?

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One of the primary *responsibilities* of eCommerce brands today is to make the customer's browsing experience easier and as convenient as possible. This is where using an AI-powered recommendation engine comes into play. You can leverage a variety of functionalities to boost product awareness and discovery such as:

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* **'Related to items you've viewed' and 'Similar products' category:** This functionality allows brands to showcase similar products that the customers might like and boost sales in the process:

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 \n  ![Source: https://cxl.com/blog/product-recommendations/](https://cdn.hackernoon.com//images/sWPIKQpSfnWW7RwzkBLP2BSzZHm1-2022-03-28T03:04:22.425Z-cl1a4ml5l017h0as65x6vgqgx)

* **Shop-the-look carousels:** This feature is perfect for eCommerce brands looking to cross-sell or up-sell to boost the average order value and showcase complementary products:

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 ![Source: https://shopthelookapp.com/](https://cdn.hackernoon.com//images/sWPIKQpSfnWW7RwzkBLP2BSzZHm1-2022-03-28T03:04:22.425Z-cl1a4ml5l017i0as6gz9iem6y)

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:::tip
All in all, recommendation engines double up as a tool to showcase your brand's offerings and boost product discovery in a personalized and holistic manner.

:::

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**2. Context-aware cart recommendations and personalized recommendations**

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Recommending products on the cart/checkout page related to the items that the customer has added to the cart can significantly boost the order value:

 \n  ![Source: https://shopthelookapp.com/](https://cdn.hackernoon.com//images/sWPIKQpSfnWW7RwzkBLP2BSzZHm1-2022-03-28T03:04:22.426Z-cl1a4ml5m017j0as69iv51ehe)

Another way of recommending contextual items is by showcasing 'Frequently bought together' items as Amazon demonstrates below:

 \n  ![https://shopthelookapp.com/](https://cdn.hackernoon.com//images/sWPIKQpSfnWW7RwzkBLP2BSzZHm1-2022-03-28T03:04:22.426Z-cl1a4ml5m017k0as6ckpx0pe2)

The idea is to leverage real-time data--a specialty of recommendation engines--to understand what customers are buying so that you can recommend related, context-aware items that are accurate and genuinely useful for boosting order value.

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**3. Personalized search by product attributes and customer behavior**

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Recommendation engines can be used to analyze your customer's behavior on the website to drive personalized recommendations and more importantly, personalized search results that are based on product attributes as well as real-time user behavior.

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Think of the search icon on your website as an intelligent albeit virtual sales agent--continually suggesting relevant products to customers based on historical browsing, past purchases, and product attributes. Recommendation engines can analyze and record user activity--from understanding product views and previous purchases to adding items to the cart and clicking on bestsellers. The engine recognizes trends across said attributes to deliver a hyper-personalized search experience for the user.

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Take a look at Amazon's search feature which 'recommends' relevant items as the user starts typing into the search bar--much like how Google does--making it a crowd-favorite among customers:

 \n  ![Source: https://www.moengage.com/blog/lessons-from-5-ecommerce-companies-acing-personalization/](https://cdn.hackernoon.com//images/sWPIKQpSfnWW7RwzkBLP2BSzZHm1-2022-03-28T03:04:22.430Z-cl1a4ml5r017m0as65hxahhzi)


:::tip
The personalized search functionality boosts user engagement, saves your customer's valuable time, improves user satisfaction, and boosts brand loyalty.

:::

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**4. Personalized push notifications for boosting product awareness**

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Another tried-and-tested strategy to boost product awareness is by rolling out personalized push notifications that encourage users to take the desired course of action:

eCommerce brands can get innovative by highlighting images and enabling a single-click checkout process to create a sense of urgency within the user using a well-conceived push notification campaign.

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This strategy also works wonders if you have a customer who abandoned a cart and you wish to nudge them to complete the sale as the brand, Bajaao demonstrates below:

 \n  ![Source: https://www.izooto.com/blog/abandoned-cart-push-notification-templates](https://cdn.hackernoon.com//images/sWPIKQpSfnWW7RwzkBLP2BSzZHm1-2022-03-28T03:04:22.430Z-cl1a4ml5q017l0as62cf3c3ft)

**The Takeaway**

There's a sharp boost in the number of eCommerce buyers, with research estimating the numbers to reach a whopping [2.14 billion by 2021](https://customerthink.com/explained-working-and-advantages-of-a-recommendation-engine/). If eCommerce brands wish to capitalize on this growing segment, they'll need to improve their product visibility and make the brand easily visible.

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Improving eCommerce Product Discovery with Recommendation Engines

Improving eCommerce Product Discovery with Recommendation Engines

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