Website Personalization in 2022 and How it Grows Business For Apparel and Beauty
Product recommendations now serve merchants of all sizes
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. Online shopping 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.
Some companies have their own recommendation systems set up, some use marketplace and AWS personalize, but more and more are leveraging the best solutions from SaaS providers.
Website personalization has become more sophisticated in recent years and marketers with advanced personalization are seeing conversion rate increases of 300% on average.
Not all personalization solutions are created equal
While more solutions are available than ever before, it’s important to note that services vary now in application and effectiveness.
In fact, nearly ninety percent of retail marketers use personalization, but most haven’t adopted the latest personalization tools.
So what are most companies missing? What’s going on at the cutting edge of personalization?
Read on as we explore,
(1) personalization’s growing accessibility,
(2) how personalized product recommendations have matured for today’s needs,
(3) what’s new for 2022 (first party data is king),
(4) what recommendations look like on modern websites,
(5) and how they can grow your online business.
The growing accessibility of personalization
Everybody knows that personalization works and that consumers expect it now. In fact, 52% of customers expect offers to always be personalized — up from 49% in 2019. Source: Salesforce.
So SaaS providers have recognized this and delivered solutions for a growing variety of ecommerce merchants.
Now, even medium sized websites are personalized. Apps are available that are actually more advanced than Amazon. Baseline features and benefits for ecommerce teams include:
- Fast onboarding without complicated integrations that deliver faster ROI
- Easy-to-use dashboard control that eliminates the need for technical know-how
- Cross-functional usability that empowers a variety of marketing roles
- Automated shopper preference analysis that provides valuable insights and saves time
- Secure onsite control of customer data that keeps your site GDPR compliant
Gone are the days when personalization simply meant putting your customer’s name in the subject line of your email outreach.
With all this recent development, ecommerce teams should compare personalization services carefully before committing to a purchase.
How traditional personalization types 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. Marketplaces like Amazon track user browsing 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 behavioral recommendations, including 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 can make unique recommendations to shoppers that are truly one-to-one.
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 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 shoppers.
The personalization maturity graph below is an often-referenced standard in ecommerce.
Note that as specialization increases the recommendations get more accurate and deliver more cross-sells and overall revenue. Fashion-focused predictive personalization with image-based AI delivers far more revenue on apparel and beauty than even Amazon.
What’s new for website personalization in 2022?
Nowadays top SaaS providers run with a product led strategy that’s more focused on the merchants’ customer experience than ever before. Marketing tools are designed to be in touch with the jobs to be done by ecommerce marketing teams.
The most advanced solutions now include fast onboarding and easy-to-use dashboards that makes deep technical knowledge unnecessary. Features and benefits are immediately obvious:
- Personalization with image-based AI, optimized for particular industries, especially image-heavy ones like fashion and beauty.
- Affordable options for meeting medium-sized business goals thanks to reliable real-time recommendations that cross-sell more and deliver high ROI.
- The Rosetta.ai dashboard with highly customizable onsite recommenders that can adjust to match the look and feel of any website.
- Automated consumer preference analysis tools that collect valuable consumer insights 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 for their customers — tools once reserved exclusively for the biggest players in ecommerce.
What does modern personalization on websites look like?
On the front end, product 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, purchase frequency and average spending amount.
The recommendation can appear like the in-page carousel above, or the more discrete one below:
Besides that, many sites use them on landing pages, offering up a discount for first time visitors to improve the site’s click through rate.
Either way, the app gives you full control of the recommender scenario, the page it appears on, the type, position, design and more.
Websites nowadays also use triggered personalization messages that pop up when certain browsing behaviors occur (based on time, exit-intent, scroll pattern, clicks, etc.)
Also, AI-automated triggers can be set and an algorithm will find the best trigger for your recommender. So when a shopper begins comparison shopping or is about to abandon a cart, your site will know and engage before the bounce occurs!
These hesitant shopper discounts are also personalized with data from automated shopper profiles and as a result they end up converting at a much higher rate than generic pop-ups.
Whether you’re setting up a recommender box or hesitant shopper pop-up, it’s easy to do and there are plenty of pre-defined templates to work with.
The templates are highly customizable, letting you determine the design so it matches the look of your site. Background, border, typography and more can all be set to your liking.
How can advanced personalization grow your business?
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 product recommendations with image-based AI. This is the overwhelming power of personalization.
Personalized in-site recommender 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.
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 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 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 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 personalization tools from Rosetta.ai are helping fashion and beauty sites raise click-through rates, AOV 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.
Offsite personalized 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, brands are now using preference analysis tools to listen to consumers and find out what they actually like. Then, when shoppers arrive onsite, recommendations and discounts can be made that accurately match their preferences.
Actionable preference analysis
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.
Conclusion
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 and the latest SaaS web apps can recognize the particular aesthetics that individual shoppers desire from first party data.
The advantages that once were in the sole hands of big brands have now become available to merchants of all sizes. Medium sized business can use these new tools to achieve business goals increasing sales and growing their user base.
About Rosetta.ai
Rosetta.ai offers fashion-optimized, image-based AI personalization for unique onsite shopping experiences, authentic email marketing campaigns and preference analysis insights.
On average, our clients double their order value and triple their conversion rate because shoppers on their websites are more engaged by the industry-leading accuracy of our personalized recommendations.
Rosetta.ai has been featured in Forbes Top 25 ML startups and Analytics Insights Top 10 companies.
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