eCommerce PersonalizationHere’s Why a Personalized User Experience is a “Must-Have” for the Modern Market

The Value — and the Necessity — of eCommerce Personalization in Contemporary Commerce

Online shopping has come a long way since Jeff Bezos first got the idea to open a book store online.

Global eCommerce revenue is expected to hit $4.32 trillion in value in 2025. And, it could continue to grow at an annualized rate of more than 8% until the end of the decade. By 2030, the eCommerce market as a whole may be worth $73.5 trillion.

This growth is in large part thanks to how easy it is to access digital experiences through internet-connected devices like smartphones and desktops.

But, that’s not the whole story. While the internet is helping customers access your site, what’s keeping them there — and enticing them to buy — is a compelling, personalized experience that uses data-driven approaches to recommend tailored products and customized promotions.

In this article, we’ll take a closer look at personalization to explore how it drives performance, decreases churn, and exceeds user expectations. We’ll also explore some real-world examples to draw from, and outline a few pitfalls you need to avoid.

What is eCommerce Personalization?

eCommerce personalization is the practice of providing tailored experiences, recommendations, and discounts to customers based on their location, past purchase behavior, frequently viewed items, and average order value (AOV), and behavioral patterns.

Customers who encounter personalized experiences benefit from more enjoyable and relevant shopping journeys. Merchants who manage to offer good experiences see decreased bounce and churn rates, along with improved conversion rates and higher average order values (AOVs).

In practice, a buyer who visits a personalized eCommerce store should not feel that they are visiting a nameless, faceless website. They should feel that the merchant knows them and their preferences. It’s like walking into your local coffee shop where the barista greets you by name and knows your usual order.

This is totally possible with modern technology. You can use your customer’s first and last name provided during signup to greet them every time they login or checkout. That’s just one example; as we’ll explore in the following sections, there are dozens of other personalization tactics you can explore.

eCommerce Personalization: By the Numbers

Shoppers no longer see personalization as a “nice-to-have” shopping experience. For many, personalization (or the lack of it) is a dealbreaker, and merchants are taking notice.

Merchants are embracing personalization because it’s proven to attract customers and drive revenue. A 2024 Boston Consulting Group (BCG) study found that personalized offers are more than three times as profitable as mass promotions. Simply making on-site product recommendations can drive incremental revenue for retailers by as much as 20%.

There’s a good reason for this correlation between profitability and customer satisfaction. Simply put, customers are more likely to buy when the content, products, and services they’re recommended are tailored, relevant, and specific to their wants and needs.

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How AI Technology is Impacting eCommerce Personalization

The landscape in regards to AI is so flexible, you could still have a first-mover advantage, even if you act now. According to the BCG data cited above, “retailers on average are investing less than 5% of promotional spending in personalized offers, and many large retailers invest 1% or less, in part because category-focused merchant teams are reluctant to give up control over trade dollars.”

You don’t even need to completely overhaul your current approach to benefit from personalization. Incremental approaches, like upgrading from traditional segmentation techniques to data-informed, generative AI-enabled approaches that allow for hyper-personalized 1-on-1 experiences at scale, and can help you unlock topline growth.

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What you do need to do, however, ask yourself:

• Is your content reaching customers where they are?
• Does your content make suggestions based on individual preferences?
• Does your content offer promotions based on browser preferences?

• Is your system able to check in with frequent site visitors and regular customers?

If you can’t answer each of these questions in the affirmative, then exploring how to augment your eCommerce personalization strategy with AI and machine learning should become your new priority... stat.

How Merchants Benefit from Personalization for eCommerce

So, what do you stand to gain from taking this approach? eCommerce personalization offers a number of benefits, including:

These are just a few benefits. eCommerce personalization can help with anything from streamlining your data insights to reducing your chargeback issuances.

eCommerce Personalization Techniques

Okay. So, we’ve covered the importance of eCommerce personalization. How do you actually provide that personalized experience, though?

A successful eCommerce personalization strategy, like a robust chargeback management strategy, should be a multi-pronged approach that makes use of several complementary tactics simultaneously. Tactics include:

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Product Recommendations

This is the bread-and-butter of personalization. Here, you provide product recommendations at the add-to-cart and checkout stages of the buying journey based on first-party data like a customer’s browsing behavior and past purchase history.

The core idea is that a buyer who has previously purchased an item is more likely to purchase it again, and bringing it up at the right time can nudge them to do so.

Dynamic Content

Ever sorted through your mail and felt yourself more drawn to the solicitations that appear to be handwritten? The same principle applies to eCommerce shoppers. They’re more likely to open an email and less likely to click away from a landing page if they felt like it was custom-made for them.

Simple tactics, like greeting a customer by their first name in an email, or funneling them into a dynamic landing page that changes based on their browsing history, can help customers feel more welcome, valued, and understood.

Behavioral Targeting

Browsing history isn’t random. Customers spend more time researching the products they’re likely to buy, and less time bothering with items that aren’t relevant to their needs. You can use these behavioral cues to target customers, both on your site and beyond.

For example, you can suggest products similar to ones that a buyer appears most interested in, or recommend complementary items that they’ve never viewed before. You can also launch retargeting campaigns so that a customer is reminded of your product and store, even if they’re on a third-party social media site. The latter approach helps draw customers who have left your website without making a purchase back to your site, and can also help you drive repeat orders.

Geolocation Targeting

Customers in different places have different budgets and buying criteria. Providing tailored recommendations to buyers based on where they’re browsing from can make them more likely to make a purchase.

For example, you can try customizing the language and currency based on a buyer’s location, or rearranging the order of items based on what’s popular in a region.

Personalized Pricing and Offers

Promotions and discounts can be personalized so that they’re more likely to compel shoppers to buy. For example, issuing specialized promos to prospective customers who abandon their carts and leave your site before making purchases may convince them to return to complete their orders.

Similarly, providing “flash sales” for complementary products based on what a buyer has already selected can convince them to add additional items to their cart.

AI-Powered Adaptation

AI algorithms, which ingest data in real time and continuously improve based on new information, can help you deliver more personalized recommendations.

A good personalization engine will need to continuously adapt based on new customer information in order to suggest products and promotions that remain relevant to buyers over time. After all, personalization is not static; customer needs and wants change over time.

Data Sources for Effective Personalization

So far, we’ve talked about how you can personalize shopping experiences for buyers. But where does the data that informs those recommendations come from?

Browsing Behavior

The way your customers interact with your website is a goldmine for relevant data. Data points like the pages they visit, the products and landing pages they click on, the amount of time they spend on specific pages, and their overall browsing paths can help reveal what they’re interested in and what they’re looking to buy.

This implicit data provides valuable insights into what a customer is looking for during their current browsing session, which allows you to dynamically adjust content and recommendations so that it is relevant during each particular shopping trip.

Purchase History

Analyzing past purchase patterns — such as the categories they favor, the price ranges they consider, and the frequency of their purchases — can give you strong insight into customers’ current preferences and potential future needs. Using this explicit data can help you deliver targeted product recommendations, loyalty offers, and tailored communication that encourages repeat orders and increases customer lifetime value.

Demographic & Geographic Data

Demographic information, such as a buyer’s age range, gender, and language preferences, helps with initial personalization efforts. Layering on geographic data, such as a customer’s city, region, or country, can help you further tailor recommendations based on local currencies, trends, and cultural nuances.

Email & SMS Interactions

How customers engage with your email marketing efforts and SMS campaigns offers another valuable data stream. Tracking opens and click-through rates can help you understand the kind of messaging that best resonates with individual subscribers. You can use this information to personalize future messaging, offer tailored promotions, or provide more relevant on-site shopping experiences.

CRM & Loyalty Program Data

Although you’ll likely have little insight as to how your buyers interact with other loyalty programs, your own survey and loyalty program data can provide an array of valuable touchpoints, including how your customers interact with support staff, what kind of feedback they’re leaving, and how often they redeem rewards.

You can use this data to design highly-personalized shopping experiences that make use of bespoke promotional offers and exclusive content. This, in turn, can result in more loyal, satisfied, and “stickier” customers.

5 Real-World Examples of eCommerce Personalization

So, now that we understand why personalization is so important, let’s take a look at several companies that are leading the way in showing how to deploy this strategy. 

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Are There Any Drawbacks of Personalization?

We’ve been singing the praises of personalization for a while now. However, there are a few points of concern that you need to consider once you decide to invest in more personalized content. These include:

All that said, the only serious “con” you’re likely to run into regarding increased personalization is the lack of it.

Most major retailers now offer personalized product recommendations, personalized emails with individualized promotional content, and advanced profiling systems. These let customers define their means of interacting with the business.

When these elements aren’t present, customers may buy things that weren’t exactly what they hoped for, weren’t specifically targeted toward them, or generally weren’t what they were looking for in the first place. Buyer’s remorse is one of the leading causes of chargebacks and friendly fraud, for instance. You can drastically reduce this problem by increasing personalization at the consumer level.

How to Get Started

eCommerce personalization offers compelling and obvious benefits with few drawbacks. So, how can you implement it in your eCommerce business?

Here, tools and integrations can do much of the heavy lifting. But it’s not a “set-it-and-forget-it” approach. Instead, you should:

#1 | Collect The Right Data

Holistic datasets that accurately inform you about who your customers are and what tastes they have are foundational to a successful personalization strategy.

That’s because all of your tailored suggestions will be based on what you know about your customers. If your knowledge about your buyers is disjointed or incomplete, you risk providing poorly personalized or irrelevant recommendations… which is arguably worse than no personalization at all.

In practice, this means you’ll need to collect both explicit and implicit first-party data about your customers. Explicit data includes information gleaned from satisfaction surveys, products your customers reviewed, and items they’ve “favorited,” while implicit data encompasses product page dwell times, geolocation and IP address information, and previous purchase patterns.

#2 | Choose The Right Tools For Your Store Size/Budget

Next, you’ll need to select and integrate personalization tools. These software solutions can be from free, or they can cost five figures or more per month. You’ll need to choose tools that work for your store size, budget, and hosting platform.

Before settling on a solution, consider your pain points. For example, which parts of your buyer funnel are the leakiest? Are you experiencing high bounce rates or cart abandonment rates? How many SKUs do you sell? Is your inventory varied enough for personalization engines to deliver helpful cross-selling recommendations? Knowing where you stand can help you determine the personalization features most important to you.

Also examine offerings to make sure they check all “must-have” capabilities. Support for AI-powered recommendation approaches, real-time analytics, privacy and security features, and tight integrations with your existing tech stack should all be priorities.

#3 | Test & Optimize Personalization Strategies

Successful personalization will require continuous testing and refinement. Once your initial personalization campaigns are in place, you’ll need to monitor their performance and tweak them based on new data you collect.

A/B testing your personalization algorithms, product recommendations, or email and SMS messaging can reveal what’s driving conversions and revenue, and what’s not effective.

Be sure to pay close attention to how your customers are interacting with personalized elements. For example, are product recommendations driving revenue from cross-sells? Is it more effective to recommend additional products earlier or later in the buying journey? What percentage of customers interact with personalized elements?

Then, learn and iterate off user behavior and feedback. Doing so can ensure that your personalization strategies remain relevant to your customers and impactful for your topline over time.

#4 | Set Realistic KPIs

What isn’t measured can’t be managed, so make sure to rigorously and continuously benchmark your personalization initiatives against realistic key performance indicators (KPIs). 

These metrics should align with your broader revenue and profitability goals, and can include conversion rates (at each stage of the buyer journey), AOV, repeat order rates, customer lifetime values (LTV), and click-through rates on personalized content or recommendations.

#5 | Track & Evaluate ROI

At the end of the day, eCommerce personalization is only successful if it delivers a return on investment. That means the incremental revenue attributable to personalization should exceed the one-time and ongoing costs of implementing and maintaining your personalization strategy (including tool subscriptions, data collection efforts, and personnel time).

Of course, ROI isn’t static, so make sure to track trends over time. Are returns increasing or diminishing? Are any new approaches driving additional revenue? Which KPIs appear most closely correlated with revenue growth?

Tying all of these steps together can help you gradually optimize your approach to eCommerce personalization.

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