Imagine you are walking through a crowded market, surrounded by hundreds of stalls selling all types of products. You’re shopping for a gift for your very picky partner. You start making your way through the shops, scanning the shelves one by one, trying to find something that they will love. 

You get overwhelmed and are just about to give up and get them a random present. 

But suddenly, a friendly vendor approaches you, carefully listens to what you’re looking for, and then points you toward a particular store. And there, you find an item that you know your partner will love.

This simple act of personalized recommendation has the power to transform your shopping experience from a tedious and overwhelming task into a delightful and efficient one. 

The same principle holds true for any business. A study from Epsilon found that “80% of consumers are more likely to make a purchase when brands offer personalized experiences”.

Why personalized recommendations are invaluable for any business 

Personalized recommendations have become an essential tool, especially for online businesses looking to increase customer engagement and boost sales. By using data on customer behavior, demographics, and preferences, businesses can create highly targeted recommendations that are more likely to be relevant and appealing to individual customers.

To understand why personalized recommendations are so effective, it is important to first consider the nature of the modern customer. 

In today's world, consumers are bombarded with an endless array of products and services, all vying for their attention and loyalty – the average person sees upto 10,000 ads every day!

As a result, customers have become increasingly savvy and discerning, seeking out options that are tailored to their specific needs and preferences.

This is where personalized recommendations come in. 

By using data and advanced algorithms to understand a customer's past purchases, browsing history, and other relevant factors, businesses can provide recommendations that are highly relevant and likely to be of interest to the customer. This not only helps to save customers time and effort but also demonstrates that the business values their individual needs and preferences.

Here’s what personalization can do for you

1. Decrease shopping cart abandonment rate

Cart abandonment is one of the most important eCommerce metrics. Providing customers with relevant recommendations, offers, and incentives that encourage them to complete their purchases.

2. Increase average order value (AOV)

Even a single personalized product recommendation can multiply your AOV by 369%. You can also use personalization tactics to cross-sell and upsell products. For example, Netflix recommends content to customers who have watched a certain type of content, increasing the time spent watching.

3. Increase session time

The longer a person stays in your store, the more they engage with your products. Retail stores have perfected the art of getting customers to linger; even window shopping is important! So why not try tactics that work for online stores?

By capturing their attention for a longer period, your customers will be more likely to make purchases.

Examples of personalization

Below are the three examples of personalization.

1. Product personalization

Product personalization refers to the process of tailoring product recommendations to the individual customer based on their browsing and purchase history, demographics, and preferences

Businesses can use data analytics and machine learning algorithms to analyze customer data and create personalized product recommendations. For example, collaborative filtering, content-based filtering, and hybrid models can be used to create personalized product recommendations.

For instance, Amazon's "Recommended for you" feature, which uses collaborative filtering to recommend products to customers based on their browsing and purchase history.

2. Landing page personalization

What it is: Landing page personalization refers to the process of tailoring the content and layout of a website's landing page to the individual customer based on their browsing history, demographics, and preferences.

You can use cookies to track customer browsing history and use that information to personalize the landing pages they see.

Netflix uses this strategy, and based on the users browsing history, it personalizes the homepage of their website, showing the contents they are most likely to be interested in.

3. Shopping cart personalization

Shopping cart personalization refers to the process of tailoring the products, offers, and promotions shown in a customer's shopping cart to their browsing and purchase history, demographics, and preferences.

Amazon displays related items that complement or enhance the items that customers are interested in, increasing the chances of an upsell or cross-sell. Or if you frequently purchase certain items together, if you add one of them to the cart, the Amazon cart will prompt you about the other.

Conclusion 

If you’re heading into 2023 without a fully formed personalization strategy for your customers – you might be in for a world of trouble. Personalized recommendations are a must-do, not a nice-to-have. The only question is how great your recommendations are.

That’s where we come in. Zevi is an AI-powered search engine that uses sophisticated machine learning algorithms to showcase highly targeted, relevant suggestions for your customers. Opt for a demo and see for yourself.