Preference Analytics
Preference Analytics
Find your unique consumer insights
Personalized Product Recommenders
Personalized Product Recommenders
Use your insights for conversion optimization
Hesitant Customer Detection
Hesitant Customer Detection
Prevent hesitant customers from bouncing
Personalized Omnichannel Marketing
Personalized Omnichannel Marketing
Be proactive on customer retention
website personalization, 1-to-1 personalization, fashion ecommerce

What Website Personalization Means For Fashion Ecommerce in 2022

Style-savvy shoppers expect 1-to-1 personalization, how should online fashion brands provide it?
Photo of our Content Strategist, Ian McKinnon
Ian McKinnonApril 18th 20228 min read
Woman shopping online

Netflix and YouTube know what we want to watch. Spotify knows what we want to hear. Amazon knows what we want to buy.

The feeling that these companies can read our minds is familiar now, even expected. An online store experience that isn’t catered to our personal tastes feels out of touch.

And it’s not new. For the last 10 years or so, the biggest online businesses have been tracking our interests and showing us what we really want.

Many fashion brands have their own recommendation systems set up, coded in-house, some use AWS marketplace with AWS personalize; but these days more and more are leveraging the best no-code solutions from SaaS providers.


Not all no-code personalization solutions are created equal

While nearly ninety percent of retail marketers use website personalization, most haven’t adopted the latest personalization tools.

So what are most companies missing? What do the latest hyper-personalization solutions have to offer?

Read on as we break down the latest trends, beginning with how easy it is for SMBs to get started these days.

The growing accessibility of website personalization

Everybody knows that personalization works and that consumers expect it now so more and more SaaS providers are providing new solutions for ecommerce merchants of all sizes.

Now, even medium-sized websites are personalized. There are plenty of subscription-based personalization software services that are actually more advanced than Amazon.

Baseline features and benefits for ecommerce teams include:

  • Fast onboarding and ROI without coding or complicated integrations
  • Easy-to-use dashboard control that eliminates technical know-how bottlenecks
  • Cross-functional usability that empowers a variety of marketing roles
  • Automated shopper preference analytics that provide first-party customer data insights
  • Secure onsite control of customer data that keeps your site GDPR compliant

Long gone are the days when personalization simply meant putting your customer’s name in the subject line of your email outreach. Now the customer journey is personalized from start to finish and ecommerce marketing teams should compare personalization services carefully before committing to a purchase.

How personalized recommendations have matured

Rules-based segmentation is one of the original onsite personalization solutions that’s still used today. For example, a very common segment is based on the rule of whether or not a user abandons a cart. If a cart gets abandoned, a rule can be set to offer a recommendation or a discount.

Behavioral recommendations came next, and again it's still going strong. Marketplaces like Amazon track user behavior (what users view or buy) and then when the user clicks a product the website recommends other “Related Items” and/or “Best Sellers in this Category.” Most websites using personalization today still use these user behavior recommendations, including Amazon.

Traditional behavioral based recommendations on Amazon

Predictive recommendations are a more recent development, the result of Amazon (and other big companies) refining their algorithms in recent years. Now machine learning can predict what individual visitors want after just a handful of visits to the site. By paying attention to our personal browsing history in real-time, companies with the the AI-driven recommendations systems can make recommendations to shoppers in real time that are truly 1-to-1. On the Nike website the “You Might Also Like” recommendation box shows items that become more personalized as visitors continue to frequent the site.

The you might also like recommendation box on the nike website

The more the visitor views, adds to cart, or buys, the more accurately the recommendation engine becomes at predicting what that visitor wants to see. It’s at this point that a website begins to make more cross-sells because the products being recommended really resonate with individual shoppers.

The personalized recommendations maturity graph below is an often-referenced standard in ecommerce.

Rosetta AI personalized recommendations maturity graph

Note that as specialization increases the recommendations get more accurate and deliver more cross-sells and overall revenue. Fashion-focused, predictive 1-to-1 personalization with AI visual recognition delivers far more revenue on apparel and beauty than even Amazon.

What’s new for website personalization in 2022?

Nowadays top SaaS providers are more focused on the merchants’ customer experience than ever before and predictive personalized marketing tools powered by AI visual recognition and NLP, which were once only in the hands of the biggest players, are now becoming more specialized for SMBs.

  • For marketing teams in the image-heavy industries of apparel, cosmetics and accessories, steps are taken immediately during onboarding to optimize the personalization tools to the niche.

Rosetta AI onboarding industry segment selection page

  • And while big companies like Nike can set up their own advanced recommendation systems, options for meeting SMB business goals like increasing sales and growing a user base are now widely available and quite affordable.

Rosetta AI onboarding business goals selection page

  • The latest personalization solutions are highly customizable so they can provide onsite recommenders that can adjust to match the look and feel of any website.
  • Automated consumer preference analysis tools that collect CRM data and valuable consumer insights from first-party data about product preferences for sales and marketing.

This is how the experience begins with a modern personalization solution. Merchants of all sizes can now use these powerful tools to create unique shopping experiences on their ecommerce sites for their online shoppers — tools once reserved exclusively for the biggest players in ecommerce.

What do modern personalized experiences on websites look like?

On the front end, personalized recommendations from SaaS providers are usually presented in a recommender box and can appear on landing pages, category pages and especially on product pages and checkout pages (where shoppers are most likely to add to cart).

On the backend, automatically created visitor profiles feature individual data on product preferences.

Fashion shopper preference attributes and a most popular product recommendation

The recommendation can appear like the wider in-page carousel above, or the more discrete one below:

A small size recommendation carousel on the IROO homepage

Besides that, many sites use pop-ups on their homepages or special landing pages, offering up a discount for first time visitors to improve the page's click through rate.

Discount pop up window

Websites that use these pop-ups nowadays can get Hesitant Customer Detection to assess browsing behaviors (based on time on page, exit-intent, scroll pattern, clicks, etc.), and time the pop-up just right. So when a shopper begins comparison shopping or is about to abandon a cart, your site will know and engage before the bounce occurs!

Getting back to basics is the key to using advanced personalization

Marketers who invest in advanced personalization solutions see immediate and lasting improvements for the three “Cs” of ecommerce:

  • Conversion optimization
  • Customer retention
  • Consumer insights

Conversion optimization

Getting shoppers to visit your website is one thing, getting them to buy something is another. For fashion and apparel, a recent August 2021 study found that the conversion rate rose to 1.71% from 1.48% during the same period in 2020, an increase of 0.23%.

Now pause for a moment and compare that small increase to the whopping 140% conversion explosion that L’Oréal Luxe brand, Shu Uemura, experienced last year when they adopted personalized recommendations with image-based AI. This is the overwhelming power of personalization.

Personalized recommendations boxes and pop-ups

Shu Uemura used a combination of in-site recommender boxes and pop-ups, all personalized to create unique customer experiences at important moments during the customer journey.

A preference profile and personalized discount pop-up on the shu uemrua site

A preference profile and a personalized discount pop-up on the Shu Uemura site.

For example, when a shopper arrives on your landing page a personalized recommender box or discount pop-up can be set to engage them and then each time they return the personalized recommendations will get more and more accurate.

Engaging shoppers with predictive personalization provides the one-to-one attention that people are much more likely to respond to and it makes a real difference when deciding to purchase or not.

Cross selling to increase average order value and ROAS

When personalized recommendations are timed correctly shoppers are more likely to add items to their carts than they originally intended. Personalizing the offer increases the chances of a cross-sell even more.

Many sites opt to add a recommendation box or a pop-up on the product details page, just as the shopper is considering clicking the Add To Cart button.

At this stage the shopper just needs a little emotional nudge to convert and recommending an item from the shopper’s preference profile can deliver a feeling of being empathized with.

Another way to do it is to offer a discount on something that the shopper intends to buy. Again, a well-developed preference profile on the backend makes this possible. Presenting a good deal on another item that a shopper truly wants increases your chance of converting.

Automating this kind of engagement during the final part of the online customer journey is like the merchandising you can find in a grocery store store, where tempting treats are presented near the cashier; or even in a clothing shop, where socks and underwear are near the checkout counter.

ROAS up, customer acquisition cost down

Advertising can help grow traffic, but in the fashion industry converting it requires special effort at the point of sale. For apparel and beauty shoppers, including personalization all along the customer journey makes a big difference. On average, websites that deliver this experience have tripled their conversion rates and doubled order value.

The specialized website personalization tools from Rosetta AI are helping fashion ecommerce sites raise click-through rates, average order value and CVR, thus achieving higher return on ad spend and lower cost per customer.

Customer retention

The lowest costing customers are ones that return to shop again. So it’s important to be continually developing strategies to keep shoppers engaged and coming back for more.

Onsite customer retention strategies

First impressions count. If you welcome new visitors with personalized campaigns they will remember the experience.

And as the customer’s journey progresses the idea is to continually engage and reduce friction.

However, there will be problems that are out of your control and some shoppers will inevitably bounce. Some will be comparison shopping and they will abandon their carts at the last moment.

This is a normal part of ecommerce so it’s best to have a strategy in place to deal with these situations when they occur. Providing a last chance incentive just as customers are about to bounce has been shown to be very effective when it’s personalized.

Personalized exit-intent pop-ups offering a discount or a recommendation when a hesitant shopper is just about to leave your site often reverses their intention.

So how does your site know if a shopper is about to leave? Machine learning monitors hesitant customer behavior. When indicative patterns of clicking and scrolling are detected, a pop-up is automatically deployed.

Personalized omnichannel marketing

Even when customers bounce they can still be encouraged to come back through remarketing, but it requires a contact list of customers.

So an email address is valuable and websites work hard to get them because a personalized email sent to entice the shoppers back can be extremely effective with the average purchase rate from such campaigns up at 11%!

In fact this type of email is the most effective way to reach out to customers. Besides email, remarketing can also be achieved via SMS and IM, which are also extremely good ways to retain customers and make more conversions.

Consumer insights

Instead of telling consumers what they should like, fashion brands are now using preference analysis tools to listen to consumers and find out what they actually like. Then, when shoppers arrive onsite, personalized product recommendations and discounts can be made that accurately match their preferences.

Actionable preference analytics

Gaining a deeper understanding of customer buying habits and product preferences has traditionally been a competitive advantage for bigger companies with the resources to perform market research.

But now even medium sized businesses can understand what customers want thanks to AI-driven solutions that provide automated data collection with specialized analysis parameters for certain industries, especially fashion and beauty.

The consumer insights gleaned by these tools help to get daily jobs done for marketing teams responsible for website customer experience optimization and even for product designers.

Discover audiences, plan experiences

Groups of consumers with common preferences can be targeted as a single audience and today’s personalization tools give you the ability to discover the attributes that shoppers share.

This is the first step in planning a personalized online experience. Knowing the attributes that appeal best to certain groups provides the content for the messages you want to send.


Personalization has come a long way in a short time. In recent years it has become especially optimized for particular industries like apparel and beauty.

The advantages that once were in the sole hands of big brands have become available to merchants of all sizes and now small and medium sized businesses can use these new tools to scale business like never before.

But with the explosion of new personalization platforms offered in the ecommerce website fashion space, marketing team leaders and brand operators must choose wisely to find services that are truly in touch with what shoppers are seeing in thing products they desire.