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blog|Customer Experience

Content Personalization: How it Works & Strategies for Ecommerce (2026)

Learn how ecommerce content personalization works, why it matters, and get tactics to tailor shopping experiences and drive sales.

by Chris Payne
/ Elise Dopson
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On this page
On this page
  • What is content personalization?
  • Why content personalization matters for ecommerce
  • How content personalization works
  • Ecommerce content personalization tactics
  • How to build a content personalization strategy
  • Examples of brands using content personalization
  • Content personalization FAQ

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Content personalization tailors the shopping experience to individual customer preferences. It uses behavioral data to deliver targeted content, like promotions and product recommendations, to individual segments and customers. 

Amperity’s 2026 report found 83% of customers want retailers to remember them, and three-quarters are more likely to purchase when they receive a truly personalized offer or recommendation. Attentive’s study corroborates this from the retailer’s point of view: It found brands that personalize are 3.5-times as likely to see improved messaging performance year over year..

This guide shares how ecommerce content personalization works and why it matters, with practical tips on how to personalize the content your customers and prospects see.

What is content personalization?

Content personalization uses customer data to deliver relevant content, offers, and experiences to individual shoppers and segments. 

It’s much more than a customer’s name appearing atop a landing page or marketing email subject line. For example, you could welcome customers with new product recommendations based on items they’ve shown interest in before. As they shop, present them with items corresponding to what they’ve placed in their carts. And at the checkout page, have their preferred payment methods ready and waiting.

Personalization strategies unpacked: What retailers need to know for 2026

Hear from experts at Shopify and our guest Forrester as they uncover why personalization strategies are a complicated undertaking for retailers, and what technology leaders need to do to help their business thrive while maintaining customer trust.

Watch now

Why content personalization matters for ecommerce

Content personalization matters because 70% of shoppers say they feel overwhelmed or uncertain, or that it takes too long to find an option they like when shopping online. Some 21% of them give up completely when they feel this way.

Brands able to help customers wade through the overwhelming options have a competitive advantage. Amperity’s 2026 study found 83% of Americans want brands to deliver personalized experiences, yet 57% think current experiences still feel generic.

“Shopify’s segmentation capabilities can improve a variety of marketing KPIs, due in large part to the fact that segmentation is the foundation of personalized marketing,” says Egan Cheung, director of product at Shopify. “And personalization is going to drive more sales, and drive up every result you’re looking for.”

How content personalization works 

With content personalization, retailers use customer data to segment their audience and tailor their customers’ shopping experience across each touchpoint. Here’s how it works:

The data that powers personalization

Third-party data-collection, powered by cookies that track customer browsing behavior, has lost much of its relevance since Google announced in 2020 that they would begin phasing out cookies on Chrome. And even though Google officially reversed its decision in July 2024, they did not change customers’ minds: 61% of consumers think limiting access to their personal data is very important.

First- and zero-party data fill that gap, and they do so in a way that does not scare customers. That’s because customers willingly share these forms of data on your owned channels. PwC reports that 9 in 10 customers are willing to share this type of personal data for a more personalized service. 

Data type Zero-party data First-party data
What it is Information shared intentionally with your brand Collected directly from your customers through your own channels
Sources
  • Quizzes
  • Polls or surveys
  • Support tickets
  • Email signup forms
  • Website interactions
  • Purchase history (in-store and online)
  • Loyalty program participation
  • Mobile app usage


Shopify’s unified customer data platform brings together every piece of data you’ve collected on customers—either through a native Shopify feature or integrated app—into a unified customer profile. 

“More and more, we are seeing organizations win in the market when they take a unified approach to their channels,” says Warren Tomlin, EY-Shopify global alliance leader. “Customers expect a deep, personal experience no matter where or when they start or end their purchasing journey. Only a natively integrated solution can deliver this.”

Customer segmentation

Data from unified profiles feeds into customer segmentation. This divides your customers into groups based on qualities they share, such as:

  • Demographic segmentation: Age, gender, income, or job title
  • Geographic segmentation: Region, country, language, or currency
  • Customer behavior segmentation: Purchase history, pages they’ve viewed, emails they’ve opened, or loyalty rewards they’ve redeemed
  • Value-based segmentation: VIP buyers, loyalty program members, or first-time customers
  • Psychographic segmentation: Lifestyle, purchase motivations, or pain points
  • Lifecycle segmentation: Where shoppers are located in the buying journey

Ask Sidekick, the AI assistant built into Shopify, to build dynamic segments. It pulls data from customer’s unified profiles to assign them into groups based on the criteria you define. Customers move when they no longer meet a segment’s criteria and enter new ones when they do. 

Privacy, consent, and customer trust

Customers are increasingly protective of their personal data. Attentive found 71% of shoppers take action to protect their privacy by opting out of cookies, shopping in incognito mode, and using separate email addresses for marketing. 

Despite those concerns, some 69% of privacy-conscious shoppers still want brands to learn from their shopping habits over time. Attentive’s report shows strong security practices (51%) and clarity on what data you’re collecting (45%) have the biggest impact on customers’ comfort with AI personalization. 

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Ecommerce content personalization tactics

Personalized content appears across the entire ecommerce customer journey, from product recommendations to tailored search results:

Personalized product recommendations

Personalized product recommendations display items customers are most likely to be interested in. Retailers use first-party data, such as customers’ browsing history or past purchases, to anticipate what each customer is most likely to buy. 

Attentive found 73% of shoppers are more likely to purchase when they receive recommendations that are relevant to their needs and preferences. Integrate them throughout the shopping journey, whether that’s:

  • “People also bought” carousels on product pages 
  • Complimentary items at checkout 
  • Back-in-stock alerts for items added to a wishlist 

Jones Road Beauty also uses shade match quizzes to gather zero-party data. It suggests a shade and a short description of “why this works”, referencing each shoppers’ quiz answer alongside the personalized recommendation. 

Shade matching quiz results for a beauty balm matched to the individual user’s skin type, tone, undertone, and main use.
Jones Road Beauty offers personalized recommendations through their Shade Matching quiz.

Following similar logic, unified commerce allows for more relevant recommendations when in-store sales associates can recommend based on customers’ past purchases and online engagements.

Personalized email and lifecycle messaging

Use Sidekick to describe the criteria of shoppers you want to include and have the AI assistant build segments for you. Automate outreach by adding those segments as the recipient in a Shopify Flow-powered marketing email. 

For instance, you could use first-party data to send special offers to customers who haven’t purchased in a while, or to entice customers who abandoned their carts to complete their purchases.

Attentive found emails with the most influence on user behavior are:

  • Sales or price drops 
  • Back-in-stock notifications
  • Customer loyalty point reminders
  • Product recommendations 
  • Refill reminders for items they buy regularly

Encourage customers to create an account and add items to a virtual wishlist to open the door to this type of personalized email. Gymshark takes this approach; it gives the brand zero-party data they can use to tailor future content. 

Pop-up box on Gymshark’s product page that encourages customers to save the item to their wishlist.
Gymshark’s wishlist tool collects data for future personalization.

Dynamic website content

Dynamic content displays different banners, offers, or content, based on customer segments, location, or browsing history. For example, a clothing brand might want to greet existing customers with this season’s version of an item they purchased last year, or a garment that pairs well with one they bought last month.

Shopify brands can do this through website personalization apps like Nosto. The app pulls data from unified customer profiles inside Shopify to adjust what each website visitor sees on your storefront. 

Health tech brand Healf is going one step further. They aim to help customers digest their product catalog, which contains curated wellness products from over 400 brands, by launching Healf Zone. The AI-powered membership gives expert guidance, delivers personalized product recommendations, and at-home blood-testing.

“Data is a huge part of our business,” says Healf’s cofounder Max Clarke. “Shopify makes it easy to get all the data we need in any format and visualize it so that we can make the right decisions for the wellbeing of our customers.”

Personalized search and merchandising

Website visitors who use a brand’s search feature account for 44% of the site’s total revenue, despite forming just 24% of their customer base, per Constructor. They also have 2.5 times higher conversion rates compared to non-searchers. 

Personalized search results prioritize products based on individual preferences and past interactions. 

Take Decked, who implemented the Shopify Search & Discovery app to handle complex search queries. Custom filters, product boosts, and synonym groups help customers navigate their extensive catalog of truck bed accessories. This feature alone drove a 4% revenue lift.

Four product recommendations for a website search: “I’m looking for a drawer system for my truck bed with a load floor.”
Conversational queries pull recommended products on Decked’s site using the Search & Discovery app.

Personalized promotions and loyalty offers

Some 81% of brands have changed their discounting strategy from last year, per Attentive. Around 43% are discounting more selectively. Personalized offers fall into this category when retailers use first-party data to adjust the promotion a customer receives—or who receives a promotion—as opposed to a blanket discount code. 

Build segments that group customers based on their shopping behavior or preferences. Here’s what that might look like in practice:

Customer segment Personalized promotion
Shipping address within a five-mile radius of your retail store Free in-store pickup
Loyal customers with <100 loyalty points Double points on their next purchase
One previous order containing a single product Discounted bundle of your most popular items from the same collection
First-time customer who made one purchase using a discount code Subscription offer with a three-month discount
Shoppers who haven’t yet bought Free gift with their first order
Shoppers who’ve bought through a social media platform Exclusive TikTok Shop product bundle
Website visitors browsing on a mobile device Mobile pop-up with an offer to remind them by SMS when a product is back in stock


How to build a content personalization strategy

Build a content personalization engine by starting with high-intent use cases, a solid unified customer database, and goals. Then test and refine your approach as you gather data.

Start with one or two high-intent use cases

Personalization can feel creepy if you go overboard. Start with one or two high-intent cases using data you’ve already got permission to use. 

Attentive’s 2026 study found shoppers find it neutral or acceptable when brands:

  • Send back-in-stock alerts for items they’ve viewed on their website (94%)
  • Recommend products based on past purchases (94%)
  • Personalize based on preferences they’ve explicitly shared (92%)

Customer feedback can uncover opportunities outside of these use cases. In the case of a fashion ecommerce brand: “incorrect size” might be the leading reason for returns. Consider personalized content like a “view on a model like me” widget which lets customers view clothing on a model that most looks like them. 

Unify customer data across channels

Amperity’s 2026 study found 69% of shoppers are more likely to buy when retailers adjust offers instantly while they browse. And of the 79% who report retailers frequently get personalization wrong, many cite irrelevant or mistimed messages.

Delayed data syncing between two integrated platforms makes this more likely. Customers in your “no purchases” segment might receive a first order discount a few minutes after they bought in-store if your POS and ecommerce data isn’t unified.

Shopify solves this problem because POS and ecommerce are unified on the same infrastructure by default. No middleware or integrations means you have one always-updated source of truth for consumer data. 

A leading independent research firm found these benefits compound. Retailers using Shopify POS experience, on average:

  • 34% lower data-migration and transition costs
  • 89% lower annual third-party support costs
  • 20% faster implementation time

It’s not just digital content you can personalize using this data; Footwear brand OluKai uses Shopify’s unified customer profiles to personalize the retail experience. 

“We know exactly what that person's purchased online, so our associates can recommend something in their size, or can better recommend how certain products relate to their interests using our first-party data,” says Nick Daniels, senior ecommerce manager.

Set goals and KPIs before launching

Tie your content personalization strategy to a handful of core key performance indicators (KPIs). Sidekick Pulse can give personalized advice here. It proactively scans your store to find opportunities and actionable tasks to improve your store. 

Jessica Robertson, cofounder and chief content officer at media and commerce company Togethxr, advises a north star vision to anchor your team. “In the end, through all of that chaos, if you can point back to that vision and that North Star, it tends to allow people to drop their shoulders and the weight of things and reset and refocus,” Jessica says in a Shopify Masters interview.

“For anything that feels chaotic or questions or priorities or non priorities, you can go back to that vision in that North Star and say, does this align? If it doesn’t, then it's deprioritized.”

Test, measure, and refine

Consult analytics to determine whether your content personalization strategy is meeting its goals. A/B testing can show the impact before an official rollout. 

“Before we launched, we had multiple landing pages that we were testing,” says Gyve Safavi, cofounder of Suri in a Shopify Masters interview. “We were doing fake ads to emails to just see what worked and how to refine the concept further.” 

Shopify Rollouts lets you manage these tests without third-party tooling. For example, you could test a localized homepage for your Canadian customers and replicate winning personalization elements for other localized storefronts.

Examples of content personalization in ecommerce

Using these tactics, and Shopify’s personalization tools, let’s get some inspiration from three online businesses who have built innovative customer experiences: 

Polywood

Polywood has a product catalog with more than 150,000 product variations. Personalization is how the brand helps customers navigate those items and locate the outdoor furniture they’re looking for. 

The brand reports a 12% increase in average order value (AOV) through personalization and recommendation features. This is on top of a six-figure reduction in total cost of ownership (TCO) and 22% higher conversion rate after migrating to Shopify.

“Everything is working out of the box and we can get all the features the business requires, but we can also still customize it to the level that matches our business,” says chief digital officer Benjamin Spiegel. “The other competitors, customizing it becomes a million-dollar project. Here, customization is easy.”

As a result, Polywood plans to launch even more personalization features over the coming months, including:

  • Interactive product-visualization tools using augmented reality and 3D modeling
  • AI-powered catalog discovery that lets customers describe their lifestyle and receive personalized furniture suggestions 
  • AI-powered self-service support after customers make a purchase 

Ruggable

Online rug boutique Ruggable uses a Rug Quiz to tailor content on their website. The quiz helps potential customers select designs that match their style and preferences. 

“We found that if we can get someone to take our Rug Quiz and answer all the questions, our conversion rate will be four times higher because the tool helps to select the right product to fit their style,” says Ruggable’s director of product management Daniel Graupensperger.

Ruggable also uses AI to help customers with product discovery. Online shoppers can upload images to let AI analyze their room’s style, instead of having to describe it themselves. The tool then retrieves a list of matching rugs that suit their home.

Béis

Luggage brand Béis used Shopify data to learn which products customers started their journey with, and which items they later browsed. They fed this into Nosto, an AI customer experience app that uses Shopify data to personalize what each individual shopper sees, as part of their holiday retail strategy. 

CEO Adeela Hussain Johnson says: “[Black Friday and Cyber Monday (BFCM)] is such a critical time period for us, our four busiest days of the year. Being a DTC brand, of course, 90 percent of our effort is making sure those four days go off seamlessly.”

The approach paid off: Béis recorded a 200% growth in organic traffic during the BFCM weekend; and 40% of consumers shopped with the brand multiple times during Black Friday. 

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Website content personalization FAQ

What is an example of personalized content recommendations?

Content personalization methods can offer customers special product recommendations that compliment items they already purchased from your website. For instance, a pet supply company could use first-party data to find customers who recently purchased a certain kind of pet food and offer first-time discounts on a dietary supplement that compliments that particular pet food.

How to make personalized content?

Make personalized content by using the first-party data you collect from customers to send personalized discounts, product recommendations, search results, or website banners. Shopify unifies this data inside a 360-degree customer view which powers native segmentation features and personalization apps like Nosto.

What’s the difference between segmentation and personalization?

Segmentation is a method ecommerce brands use to personalize their content. For example, you might build a segment of loyalty program members with over $10 in points value and send a personalized email that encourages them to redeem rewards at their nearest store.

What data do you need for content personalization?

The data you’ll need to personalize content depends on what you’re tailoring. That might include:

  • First-party data: Browsing history, pages viewed, time on site, and search queries
  • Zero-party data: Quiz answers, wishlists, and email opt-in fields
  • Contextual data: Location, device, referral source, and time of visit
  • Transactional data: Previous purchases, order frequency, average order value, and customer lifetime value

How do you personalize content without third-party cookies?

First- and zero-party data let you personalize content without relying on cookies. Quizzes are an example: Jones Road Beauty runs a shade quiz that asks for a customer’s skin tone and planned usage. They use these insights to adjust the quiz results page that includes a tailored product recommendation and “how to use” advice. 

by Chris Payne
/ Elise Dopson
Published on 25 Feb 2025
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by Chris Payne
/ Elise Dopson
Published on 25 Feb 2025
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