How to Use Personalization to Boost eCommerce Conversions

Thomas wasn’t always an expert in eCommerce personalization and conversion optimization. His journey started with a passion for technology and problem-solving, which led him to study computer engineering. But something wasn’t clicking.

He didn’t just want to write code all day—he wanted to work with people, build businesses, and help brands scale. That realization pushed him to start Scoutside, an eCommerce-focused agency that helped brands grow through data-backed optimization. After 12 years of scaling Scoutside, he merged with Bear Group, where he now leads strategy, UX, and growth initiatives for direct-to-consumer (DTC) and B2B brands.

Through years of working with eCommerce businesses, Thomas has cracked the code on personalization—how to use customer data to create experiences that feel tailored, relevant, and engaging while increasing conversion rates.

In this post, i’m breaking down his step-by-step approach to personalization, from beginner-friendly tactics to advanced AI-driven strategies.

Step 1: Start with the Basics – Email & Product Recommendations

Most brands think personalization is complicated, but you don’t need advanced AI to get started. The easiest way to begin is by personalizing two key areas: email marketing and product recommendations.

1. Segment Your Email List (Stop Sending One-Size-Fits-All Newsletters)

✅ Analyze past purchase behavior – What product categories does each customer engage with?

✅ Use browsing history – Even if they didn’t buy, what did they look at?

✅ Personalize subject lines – Emails with a customer’s first name or relevant product category get higher open rates.

✅ Create targeted email flows – Example: If a customer bought running shoes, follow up with performance socks or workout gear.

🚀 Pro Tip: If you use Klaviyo, leverage its segmentation and dynamic content tools to send hyper-relevant emails.

2. Intelligent Product Recommendations (Your “Related Products” Section is Broken)

Most Shopify themes come with a “related products” section, but they’re static and generic. The key to better personalization is using real-time data to recommend products.

✅ Use AI-driven recommendation engines like Rebuy to suggest products based on purchase patterns.

✅ Bundle products together – If a customer buys high heels, recommend matching accessories, not sneakers.

✅ Use “Frequently Bought Together” data to increase average order value (AOV).

🚀 Pro Tip: Personalized product recommendations can increase revenue by 10-30% without additional ad spend.

Step 2: Personalizing the Shopping Experience

Once you’ve nailed email and product recommendations, the next step is on-site personalization—adjusting the website experience based on user behavior.

Geo-Personalization (Show Customers What’s Relevant to Them)

A great example? The North Face. If you visit their site from Seattle, you’ll see rain jackets. If you visit from Miami, you’ll see swimwear.

✅ Detect location & adjust homepage content (weather-based, region-based, or even city-based offers).

✅ Use language and currency localization – If you’re an international brand, don’t show USD prices to UK visitors.

✅ Geo-targeted promotions – Offer discounts or free shipping based on location.

🚀 Pro Tip: Use tools like GeoIP Redirects to personalize the experience based on the customer’s region.

Dynamic Content Based on Browsing Behavior

Every visitor’s behavior tells a story. If they browse high-end luxury watches, don’t show them budget-friendly deals.

✅ Customize homepage banners – Highlight the product categories they showed interest in.

✅ Pre-fill search suggestions – If a visitor searched for “running shoes” last time, show them latest arrivals in running gear.

✅ Offer smart exit-intent pop-ups – If they’re about to leave, trigger a customized discount based on their cart value.

🚀 Pro Tip: Use Ninetailed or Intellimize to dynamically adjust website content based on user actions.

Step 3: Intermediate Personalization – Quizzes & Zero-Party Data Collection

With third-party cookies disappearing, brands need to collect data directly from customers. One of the best ways? Quizzes and guided shopping experiences.

Example: Clearly Filtered’s Water Quality Quiz

A brand called Clearly Filtered collects data through a simple zip-code-based water quality quiz.

Customers enter their zip code.
The site pulls real-time data on contaminants in their local water supply.
It recommends the best filtration system based on their needs.

✅ Why This Works: Customers feel like they’re getting a personalized recommendation rather than a generic sales pitch.

✅ Bonus: The brand collects first-party data that can be used for future retargeting and follow-up campaigns.

🚀 Pro Tip: Use tools like Octane AI to build quizzes that personalize product recommendations.

Step 4: Advanced Personalization – AI & Headless Commerce

For brands that want to go all-in on personalization, advanced strategies involve AI-powered content delivery and headless commerce setups.

AI-Powered Personalization (The Future of eCommerce)

✅ Predictive product recommendations – AI can analyze browsing and purchase history to suggest the next best product.

✅ Dynamic site experiences – Show different homepage layouts based on customer behavior.

✅ Personalized search results – If a customer frequently buys organic products, prioritize organic items in search.

🚀 Pro Tip: Shopify Plus brands can integrate Ninetailed AI for deep personalization.

Final Takeaways: Personalization is the Key to Scaling

eCommerce isn’t just about driving traffic anymore—it’s about maximizing every visitor’s experience.

If you want higher conversions, lower ad costs, and better customer loyalty, personalization isn’t optional—it’s essential.

Now over to you—how are you using personalization in your eCommerce business? Drop a comment below!

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