How To Build a Personalization Engine for a Shopify Store [2025]

You may notice or not — personalization is everywhere in commerce.

It’s a powerful strategy that enhances your sales, marketing, and customer loyalty.

Imagine going to a brick-and-mortar clothing store to buy a T-shirt:

Based on your preference, the salesperson would bring the most suitable T-shirts for you, from hundreds of items. While showing those T-shirts, they may also present you some jackets or jeans that would pair nicely with them. Well, that’s just one of many forms of personalization.

Now, as an eCommerce business owner, you could deliver such a personalized shopping experience to your online customers with a robust personalization engine.

So, in this blog post, we’ll share a detailed guide on the personalization engine, how it works, why you should use it, and a step-by-step guide on how to build a personalization engine for your Shopify store.

Let’s get started!

What is a Personalization Engine in eCommerce?

A personalization engine is a software that uses historical and real-time data, with advanced technologies like Artificial Intelligence (AI) and Machine Learning (ML), to create a personalized shopping experience for customers.

The goal of a personalization engine may differ from business to business. But in general, the idea is to enhance the customer experience by displaying personalized product recommendations, content, ads, or other offerings. Ultimately, it helps increase the revenue and profits of your business.

Example of a Personalization Engine

Now, let’s understand this with a simple example. Talking about personalization in eCommerce, how could we ignore the best in the business — Amazon — the eCommerce giant! 

Amazon is a great example of an eCommerce platform that’s leveraging a personalization engine. As soon as you visit the Amazon homepage, you may find the section — “Pick up where you left off” if you have previously browsed products on Amazon.

So basically, that’s a personalization engine at work. It shows you those items as you might still be interested in purchasing them. Even upon scrolling down a product page, it displays the items based on your shopping trends and other (similar) customers’ browsing history.

The Rise of Hyper-Personalization

Now, you may wonder — what’s the difference between traditional personalization and hyper-personalization?

It’s simple. The core idea in both these terms is the same — to deliver a personalized experience to customers by using insights from data analysis. But the main difference is the degree to which personalization is implemented, at an advanced level.

The traditional personalization approach considers delivering personalized recommendations based on historical data and observations of customer behavior. Whereas hyper-personalization is more advanced and uses real-time data (along with historical data) and AI/ML technologies to deliver a highly personalized experience.

How Does a Personalization Engine Work?

Now, let’s take another example of a brick-and-mortar store.

Has it ever happened to you that you go to a local store, where you frequently purchase the same item, and the shopkeeper gives you the item even before you ask for it? That’s again a form of personalization that is widely used in eCommerce as well.

However, as we just discussed earlier, different brands may leverage a personalization engine in different ways—based on their requirements and business goals. For example, the way Netflix uses a personalization engine for its streaming platform is different than how Amazon uses it on its eCommerce marketplace.

But again, it’s the core concept of personalization that’s being used with different use cases or business types. Here’s a brief overview of how a personalization engine works for eCommerce brands in most common use cases:

Gathering data and insights:

First, the personalization engine learns from your existing or historical customer data to understand customer behavior and patterns. For example, “frequently bought together” product recommendations are created based on the historical buying patterns of customers.

Similarly, the personalization engine could also study the real-time data and customer behavior from your website or mobile app. For example, let’s say a customer searches for specific diet items on a food store, the entire shopping experience can be personalized with related product recommendations.

Analyzing the customer preferences:

The way customers interact with your website, a personalization engine can identify their preferences and purchase intent. Here’s where AI & ML technologies play a crucial role in studying large datasets and converting them into meaningful insights.

Then, the personalization engine leverages those insights for better product recommendations or content delivery.

Segmenting customer groups or individual profiles

Customers can be divided into various groups or segments to create a personalized experience for them. For example, one of the most common use cases in eCommerce is to segment buyers based on gender to offer them suitable product recommendations.

Also, such a segmentation strategy works great in your email marketing campaigns. You can segment your email subscribers into different categories and send personalized email content based on the segmentation.

Pro tip: During the lead generation activity, you can collect some details from your potential leads about their profile or preferences. Also, a quiz is a great way to collect details about customers that can be immensely helpful in segmentation and personalization.

Learn more: Shopify Quiz Funnel — Guide, Examples, and Apps

Delivering a personalized shopping experience & content:

Even within a niche, customers may have different preferences based on criteria such as age, gender, location, etc. For example, let’s say your store offers various types of products for all genders. You can choose to prioritize different types of products on your homepage depending on the visitor’s gender.

How To Build a Personalization Engine for a Shopify Store

Okay! Now, it’s time to get into the real deal. We’re going to go through the step-by-step process of building a personalization engine for a Shopify store.

Step 1: Define Your Goals & Strategy

First off, the idea of personalization has a huge and broad scope in eCommerce. 

You must define how and where you’d like to implement the personalization engine — 

• Product recommendations 

• The search function on your store

• Content (e.g., personalized email marketing)

• Ads and promotions

Depending on business goals and personalization strategy, you could choose your tech stack for building the personalization engine. One of the most widely used applications of personalization is in product recommendations on the website or app.

Also, the scope of personalization may depend on how and where you’re selling your products. For example, when selling globally, personalization would have a different scope than selling in the domestic market.

In a nutshell, your goals and strategy for personalized shopping experience should be aligned with your business goals and long-term vision.

Step 2: Choose Your Tech Stack for Personalization Engine

Shopify App Store offers many great apps to help you build a robust personalization engine.

Based on the goals and strategy you defined in the first step, research and finalize which app(s) you would like to install on your Shopify store.

You can directly type “Personalization Engine” in the search bar on the Shopify App Store, and you’ll find multiple apps that can help you create personalized product recommendations for your store.

Review the apps and finalize the one that best fits your use case, budget, and requirements.

Side note: You may choose more than one app to implement personalization across your store for various functions. For example, apart from personalized product recommendations, dynamic pricing strategy can also be an important strategy for personalization.

Learn more: Dynamic Pricing in eCommerce — Guide and Examples

Step 3: Install & Set Up the Personalization Engine App

For this tutorial, we’ll go with the Rebuy Personalization Engine app. Click on the Install button to proceed with the installation. Review access permissions and complete the installation.

Then, you’ll be redirected to Rebuy’s sign-up page where you can create an account with your first and last name and work email. Alternatively, you can go with your Google account if you want to associate it with your Rebuy account.

As soon as you create the account, you’ll land on Rebuy’s dashboard. Right at the top, you’ll see a pop-up with a button — “Enable Rebuy Connector”. Click on that button to configure Rebuy in your current theme.

Once you click on the button, the Rebuy toggle will automatically be enabled — you just need to hit the Save button on the top right corner to confirm it.

Now, go back to the Rebuy dashboard, and now you’ll see a new pop-up with the button — “Start Feature Onboarding”.

The app has a nice and easy onboarding flow. Just personalize your configurations as per your goals and needs.

Step 4: Implement Your Personalization Engine

Now, you’re all set to start implementing different strategies available in the Rebuy app. When you click on the “Set up Rebuy Features” tab in the sidebar, you’ll see the different features including:

• Product Recommendations

• Reorder Landing Page

• Smart Cart

• Post-purchase

For example, if you go to the first option (Product Recommendations), you’ll see all the different options such as AI Recommendations, Recently Viewed, Add to Cart Upsell, and so on.

Choose the relevant option based on what type of product recommendations you’d like to display on your Shopify store, and complete the configuration logic.

Step 5: Analyze the Performance and Optimize as Needed

To gauge the effectiveness of your personalization engine and the whole strategy, you must measure and analyze the before and after performance.

You can do this comparison in two ways:

• Quantitative data: Comparing the sales and conversion figures, average order value, impact on your revenue and profits, and so on. You can use Shopify analytics tools to measure these data points.

• Qualitative data: Apart from data, customer feedback is also important. How happy or satisfied are customers with their shopping experience? Conduct pre-purchase and post-purchase surveys to collect customer feedback.

Based on the performance results and customer feedback, keep improving your personalization strategy. And when talking about improvements — your goals shouldn’t be limited to revenue optimization but they must also cover customer experience (CX).

Why Use a Personalization Engine?

A personalization engine isn’t just a business requirement for you only — your customers require personalization too. Epsilon research has found that 80% of consumers are more likely to buy from brands that offer personalized experiences. 

And that’s the reason it helps enhance your conversions. According to a Netcore report, 71% of retailers who worked on personalizing customer experience (CX) witnessed at least 4 times higher ROI.

Here are some of the key benefits of using a personalization engine:

• Conversion Rate Optimization (CRO):

A personalization engine leverages the data and analytics to offer personalized product recommendations. Customers love to see a tailored shopping experience, and it increases the chances of getting converted.

• Increase the Average Order Value (AOV):

Personalization recommendations can also be used to display product upsell and cross-sell offers more effectively. When done properly, upselling and cross-selling increase the AOV as customers are enticed to shop more from your brand.

• Build Customer Loyalty:

Every time a customer visits and interacts with your store, the personalization engine aims to deliver a seamless buying journey. On top of that, it can analyze customer behavior for future opportunities too. This way, you can make your customers keep coming back to your store.

• Solidify Customer Lifetime Value (CLV):

The focus of personalization is not just about closing a one-time deal. The personalization strategy should be optimized to build a long-term brand. When you receive repeat orders from your loyal customers, it increases the CLV and helps you build a sustainable business.

Best Shopify Apps for Personalization Engine

Now, let’s take a look at some of the best apps on the Shopify App Store that could help you build your personalization engine:

1. Rebuy Personalization Engine

So, we’ve already seen this app in the above tutorial. Rebuy Personalization Engine is one of the popular AI-powered product recommendation apps.

Rating & Reviews: 4.8 Out of 5 Stars (788 Reviews)

Key Features:

• Personalization Engine: Leverage AI/ML technology to create end-to-end personalization and advanced search experience.

• Smart Cart: Build and customize your AI-powered smart cart that's fully integrated with your Shopify store.

• Upselling & Cross-Selling: Display data-based product recommendations on the checkout page and accelerated checkout.

•  Re-Order Landing Pages: Increase your repeat sales using re-order landing pages.

Pricing:

2. Wiser Product Recommendations

Wiser is a product recommendations app that can help you increase your store's conversions and revenue. The app also offers API access and supports the multi-currency function.

Rating & Reviews: 4.9 Out of 5 Stars (712 Reviews)

Key Features:

• Frequently Bought Together: Display AI-powered product recommendations for "frequently bought together" items along with discounts.

• Upselling Features: Display upselling offers on your product pages, collection pages, and blog posts. Also, offer checkout, thank you page, and post-purchase upsells to increase your revenue.

• Advanced Cart Drawer: Optimize your cart drawer with a progress bar and display upselling offers.

• Recommendations Quiz: Create a recommendations quiz to gamify the shopping experience.

Pricing:

3. Vandra: Site Personalization

Vandra: Site Personalization is a relatively new app but looks quite promising. Vandra’s personalization engine creates a shopping experience based on the traffic source and customer behavior on your site.

Rating & Reviews: 5.0 Out of 5 Stars (8 Reviews)

Key Features:

• AI-Powered Session Analysis: Gather insights on purchase intent with analysis of session data.

• Behavioral Targeting: Personalize the shopping experience for customers based on their interactions with your site.

• Pre-Built Personalization "Recipes": Optimize your personalization game with pre-built systems.

• Performance Metrics: Measure and analyze the impact of personalization on key metrics such as sales, conversion rate, and AOV.

Pricing:

Vandra’s pricing structure is different from other apps that have fixed monthly fees. This app charges a 5% commission on the gross transactions’ value. 

4. AfterShip Personalization

AfterShip Personalization helps you create and offer smart product recommendations using advanced AI-powered algorithms and merchandising rules.

Rating & Reviews: 4.9 Out of 5 Stars (148 Reviews)

Key Features:

• Smart Cart: Optimize your cart with features like a progress bar and upselling.

• Customizable Checkout: Enhance your checkout experience with customizations and optimize the thank you page as well.

• Templates: Use pre-built AI algorithms and merchandising rules that you can customize as needed.

• Personalized Collection Pages: Display the collection pages tailored to specific segments and traffic sources.

• Analytics: Review the dashboard for important metrics such as revenue, orders, and product affinity.

Pricing:

That’s it about the personalization engine apps. Feel free to check out more apps on the Shopify App Store if you wish to do so.

Pro tip: Most personalization engine apps are built for curating the shopping experience with personalized product recommendations and increasing upsell opportunities. However, keep in mind that personalization goes beyond the buying journey. Make sure to implement personalization in other areas of your business too. For example, even after a customer has completed a purchase from your brand, you can implement personalization in email marketing. Send them relevant emails based on their purchase history and build a long-term relationship with personalized emails.

Final Thoughts on Building a Personalization Engine

Every eCommerce brand wants to excel at conversion rate optimization (CRO). After all, it helps your business grow at a faster pace. Personalization plays a key role in the effectiveness of CRO efforts.

As an eCommerce entrepreneur, you must leverage every opportunity to optimize personalization on your store. It will not only help you increase the conversion rate in the short run but also build your brand for the long run with higher customer satisfaction.

If needed, you may consult CRO experts to get help on how you can incorporate a personalization engine in your CRO strategies.

To learn more about eCommerce marketing strategies, trends, and best practices — check out more resources on the GemPages Blog. Also, join the GemPages Facebook community to network and learn from like-minded entrepreneurs and experts.

FAQs About the Personalization Engine