Ecommerce has evolved at a rapid pace. Shoppers no longer desire generic shopping experiences that remain the same regardless of their history with a company. Technological advancements allow merchants to personalize shopping experiences at scale—and it’s becoming table stakes in modern commerce.
Satisfaction, customer loyalty, and conversion rates are at stake with personalized experiences—in fact, 76% of shoppers get frustrated with companies that don’t offer personalized interactions.. This guide shares how to implement them at scale, with ecommerce personalization examples and best practices to follow.
Understanding the value of personalization
Modern personalization goes beyond adding a subscriber’s first name to your marketing emails: It tailors every part of the customer experience to the individual based on data you’ve already collected on them—including tailored product recommendations, customized website content, and targeted promotions.
Segment’s recent report found that 89% of leaders believe personalization is crucial to their business’s success in the next three years. That’s because a personalized customer experience offers benefits such as:
- Reduced customer acquisition costs (CAC): Cookie policy changes and growing competition are driving CAC through the roof across all industries. However, McKinsey found that personalization can reduce CAC by as much as 50%.
- Increased loyalty and customer retention:eMarketer reports that just 44% of consumers say that the brand offers they get are personally relevant. However, brands that incorporate first-party data into their loyalty programs can boost year-on-year loyalty member spend by 16.5%.
- Higher average order values: Some 57% of consumers say they’ll spend more on a brand that personalizes the shopping experience. When combined with the benefit of lower CAC, personalized experiences have the potential to significantly increase your bottom line.
Collecting first-party data to personalize shopping experiences
Despite their desires for a personalized experience, many consumers are concerned about the data that brands hold on them to make those tailored experiences possible. Per KMPG, 86% of consumers say data privacy is a growing concern. Two in five don’t trust companies to use their data ethically.
Leading technology companies are leaning into these concerns by offering consumers greater privacy protections. Apple launched its App Tracking Transparency feature that requires users to opt into data sharing, replacing the automatic opt-in and manual opt-out. Browsers like Firefox, Safari, and Brave have implemented similar features to maintain user privacy.
These changes make it more difficult than ever to uncover consumer behavior. You can only monitor onsite behavior, and use the collected data to personalize the shopping experience, when website visitors have opted in to cookie tracking.
First-party data fills this gap using data that has been willingly contributed by your audience. Despite privacy concerns, it’s something that people are willing to share: almost half of global consumers will share their personal data if it leads to better experiences.
The best part: You likely already have first-party data through sources such as:
- Direct customer interactions: Feedback mechanisms, such as surveys or direct communication channels, can help you learn individual customer preferences and pain points.
- User accounts: Customers can create accounts that allow you to track their preferences, previous purchases, and browsing habits.
- Loyalty programs: Loyalty programs not only retain customers, but provide a data-rich resource for understanding purchasing behavior and preferences.
Shopify is unique in that all of your customer data is unified from the get-go in our customer data model. You can view emails they’ve opened, loyalty points they’ve earned, sales channels they’ve used, responses they’ve submitted, and more. There’s no need for third-party plugins, apps, and integrations passed through middleware to construct a pieced-together view of your customer. It’s all right here, inside customer profiles in your Shopify admin.
Leveraging data for personalization
First-party data is the foundation on which personalized customer experiences are built. It surfaces your audience’s likes, dislikes, browsing history, buying preferences, past purchase history, and sales channel interactions—information you can use to fine-tune the content you deliver.
We can see this in action with an omnichannel retailer that wants to convert non-buyers on their email list. They can use Shopify Segmentation to group subscribers who haven’t made a purchase based on unified data in their Shopify customer profiles, then leverage the following data points to personalize their outreach:
- Referral channel they visited from: Subscribers who first discovered your website from TikTok could see embedded user-generated content on product pages from TikTok creators they know.
- Email form they signed up through: People who submitted their email address in exchange for a 10% discount on their first order get reminded of their offer—perhaps with a countdown timer to instill a sense of urgency.
- Collection pages they’ve visited: This data directs dynamic content on the website, such as personalized product recommendations and announcement bars that reflect bestsellers in the product categories customers have viewed.
- Pages they’ve viewed: Subscribers who’ve clicked your returns policy page might be concerned about their options if they don’t like a product they’re thinking of buying. Send a targeted email that reinforces your free returns policy that gives them 14 days to change their mind.
Integrating advanced technologies
It’s not just the data you’ve already collected on customers that helps offer tailored experiences. The best personalization strategies are proactive—not just reactive.
Modern technologies help to enhance personalized shopping experiences. Artificial intelligence (AI) and machine learning offer predictive data analytics to anticipate what customers need before they’ve expressed a need for it.
Shopify merchants don’t need a conjoined tech stack to benefit from this technology. Shopify’s an all-in-one commerce operating stack that manages your personalization efforts from end to end. It’s truly unified commerce, rather than commerce pieced together through middleware. With Shopify, you can:
- Acquire customers with Shopify Audiences, Shopify Collabs, and Shop Campaigns
- Drive buyers to your store using native features like Shopify Email or advanced marketing automation apps like Klaviyo
- Personalize the website experience depending on their location with Managed Markets, and enable dynamic content through integrations with personalization apps like Nosto
- Optimize checkout by prepopulating shipping and payment options to enable one-click checkout
- Increase customer loyalty with app integrations like Smile and Rebuy
Shopify unifies data from these app integrations to fix data-synchronization issues. Your data updates in real time, no matter where you originally sourced it from, to give you a 360-degree view of your customers to personalize their experience.
Innovative personalization ideas to try
Geotargeted promotions
Geotargeted promotions customize offers based on a customer’s location. Managed Markets lets you do this at scale. It detects a visitor’s IP address and customizes content on your storefront to localize the experience, such as:
- Using their home currency
- Translating content into their native language
- Incorporating duties or taxes into product prices to prevent surprises at checkout
An omnichannel retailer with a physical presence can also use location data to personalize online-to-offline (O2O) marketing campaigns.
For example, you could segment people within a 15-mile radius of your store, then run a Klaviyo email campaign to display inventory levels of products they’ve previously viewed on your online store. Offer an incentive, such as 10% off their first in-store purchase, as extra motivation to drive email subscribers to their closest retail store.
💡Pro tip: See real-time inventory data across multiple locations from your Shopify admin. This gives you the confidence to say exactly how many units you have available in a customer’s closest location from your online store.
Behavior-based triggers
Behavior-based personalization lets you design specific actions based on customer behavior. It’s one of the easier ways to personalize the shopping experience since your ecommerce platform and integrated apps already compile behavioral data.
Here’s what that might look like in practice:
- Customer views your men’s holiday gift guide → show bestselling men’s gifts in retargeted social media ads
- Visitor abandons their cart → send an automated email with a discount code 30 minutes after their exited session
- Loyal customer hasn’t made a purchase within 90 days → send an email that shows new products similar to products they’ve purchased in the past
Dynamic website content
Dynamic website content changes the appearance of your homepage or product pages based on a visitor’s past interactions. For example:
- Customers who participate in your loyalty program see a carousel that explains the value of their points (and what they can be redeemed for).
- Customers who previously redeemed a free shipping offer see an announcement bar that shares the minimum threshold to qualify for the same offer again.
- Customers who’ve bought a particular product see a product carousel of complementary items that people often buy in conjunction.
Personalized video content
Video is dominating social media in platforms like Instagram and TikTok. Ecommerce brands are leaning into the trend for good reason: 82% of people have been convinced to buy a product or service by watching a video.
Retailers use video marketing to address user preferences both onsite and through marketing channels like email and social media ads. If someone completed your skin care quiz and said their primary concern was acne, for example, you could share a UGC video of a happy customer who used your product bundle to clear their acne.
💡Pro tip: Shopify Collabs lets you recruit influencers, send free samples, and manage creator payouts—all without leaving your Shopify admin.
AI-driven product recommendations
Customers might need a helping hand to find the right product for them, especially if they’re a first-time shopper. Even if you don’t have a wealth of data about that customer already, AI tools can analyze customer data and provide highly relevant product suggestions based on information you’ve collected on other similar customers.
Say, for example, that you’re a home furnishings retailer. The limited data you have on a new customer shows that they clicked your Google Shopping ad and viewed the king-size variant of a particular duvet cover.
AI-powered customer insights show that people who view this duvet cover tend to buy a matching white bedsheet. You could use this insight to upsell the customer through customized product carousel widgets and targeted email campaigns. You could offer a complete new linen set for their king-size bed, simultaneously improving the shopping experience and increasing average order value.
If you also have an AI-driven chatbot, product recommendations can be seamlessly integrated into the feature. For example, if someone says they’re shopping for a holiday gift for their dad, point them towards your bestselling products that are popular among other customers who are shopping for their parents.
Personalization case studies and examples
Omy Laboratories
Omy Laboratories is a skincare brand built on personalized products. There are no one-size-fit-all serums or face creams—every formulation is tailor-made for each individual shopper.
Omy wanted to apply the same personalization to every part of the shopping experience. They upgraded their Shopify theme to Online Store 2.0, which allowed the brand to unlock dynamic page personalization, and enlisted the help of Shopify partner Novatize.
Omy worked closely with Novatize’s ecommerce agency to redesign their new DTC storefront, which features a product customizer to let customers order their own unique formulation. Shopify’s unified customer profiles also let Omy handle specific use cases—like when customers want to reorder their personalized products, review their tailor-made formulas, or opt in to a subscription.
The launch of Omy’s personalized storefront was a roaring success: The brand experienced a 60% session increase year-over-year, with a 35% boost in repeat purchases. The vast majority of all sales are now made through this ecommerce channel.
Little Words Project
Little Words Project sells bracelets with affirmative words and phrases, after founder Adriana Carrig was a victim of bullying in college. The entire brand is built around community and connection—their sprawling network of 14 brick-and-mortar stores helps the brand instill these values in their audience.
To strengthen the brand’s community and personalize the retail experience, Little Words Project turned to Shopify. They can now utilize point-of-sale (POS) features like email capture at checkout, which helps them build their email list. This became an avenue for the jewelry brand to build stronger, longer customer relationships with people after they’d exited the store.
Because POS is a native part of Shopify’s commerce operating stack, any customer data that Little Words Project collects in-store is unified in each customer profile. “This email data is flowing into our marketing programs and the larger Little Words Project ecosystem,” says Sam Sisca, VP of retail. “So customers are getting our promotional emails and announcements about new launches and events coming up at stores close to them.”
Since adopting email capture at checkout with Shopify POS, Little Words Project has increased in-store email capture rates by over 20% on average. They have experienced a 33% uplift in all POS orders with a customer email added and marketing opt-in across all stores.
Ruggable
Ruggable is a premium home furnishings retailer that sells durable and spill-proof rugs. These features mean their products tend to be much more expensive than the competition. With so much at stake when buying a high-consideration product, shoppers who are on the fence want to know that they’re choosing the right one. So the brand built a Rug Quiz.
The quiz is a great opportunity for Ruggable to collect first-party data on their shoppers. “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 Daniel Graupensperger, Ruggable’s director of product management.
Ruggable also uses augmented reality (AR) to show the customer what a rug would look like in their home. Shoppers can point their smartphone camera at an empty space in their room to see what the rug would look like there.
This combination of personalization tactics has helped Ruggable expand into new sales channels and greatly reduce new market launches—all without compromising on site speed, stability, or SEO.
Best practices to create a personalized shopping experience
Start small
Personalization must be correct to be effective. Using the wrong first name in a marketing email is the most obvious mistake, but there are plenty of other hazards you might trip up on when implementing personalized experiences for the first time—like not syncing data from retail stores when retargeting in-store shoppers online.
There’s also a fine line between personalization and being invasive. Per eMarketer, almost half of consumers think receiving personalized promotions within two minutes of visiting a retailer’s website or app is “creepy”.
A best practice is to start small with targeted campaigns based on larger segments, and gradually expand as you understand your audience better. That might mean cart recovery emails that show the items someone left, a special birthday offer, or tailored campaigns based on links they’ve clicked in marketing emails—before you dive deeper into advanced strategies.
Use A/B testing
A/B testing allows you to refine your personalization approach based on actual customer responses. It takes the guesswork out of what you think your customers would like by providing you with data that compares the personalization experiment against a control group.
For example, A/B testing can answer hypotheses like:
- Do email popup forms have a higher opt-in rate when you use a picture of a product the visitor recently viewed?
- Do emails have a higher open rate when the subject line reminds people of the incentive they signed up in exchange for?
- Does the conversion rate of a product page increase when reviews are from customers who share similar traits to the website visitor?
Continuously update data collection practices
The sheer volume of available data poses a challenge for online retailers. With so much data available, how do retailers not only ensure that the data they’re relying on is accurate, but also meaningful?
Establish data lifecycle management procedures to streamline the collection process. Create clear guidelines on the data sources you’ll use, which types of data you’ll pull, and where the centralized repository is for data storage. Most often, this is your Shopify admin, but as you scale, data might live in an enterprise resource planning (ERP) system that integrates with your commerce operating system.
Data collection and hygiene aside, maintain open lines of communication with your customers. What personalized offers do they want? How can you improve their shopping experience? Keeping your ear to the ground and iterating on feedback acts as a competitive advantage—considering just 9% of in-store and 14% of online shoppers are satisfied with their experience.
Scale personalization efforts with Shopify’s core customer model
Personalization is no longer nice to have—it’s the future of commerce.
Because your business’s data is unified through Shopify’s core customer data model, it’s never been easier to invest in the right strategies and tools to deliver superior experiences. You already have the data at your disposal—now it’s time to use it to give shoppers what they want.
