Kostas Koukoravas, Author at Intelistyle

Ecommerce Recommendations – 68 Examples For Your Store

Kostas Koukoravas — Tue, 06 Jul 2021 15:39:37 +0000

Ecommerce Recommendations - 68 Examples for Your Store

Today’s highly connected customers don’t have the patience to sift through endless product category pages to find items that are relevant to them. Instead, shoppers expect brands to make it easy for them to find products they will love and will want to buy — even if they don’t know what these products look like themselves. That’s where eCommerce recommendations come in.

As many as 50% of shoppers will ditch a brand for a competitor if a business fails to anticipate their needs. For this reason, every successful e-commerce store today uses ecommerce recommendations, otherwise known as product recommendations.

Whether they’re generic or personalised, product recommendations can speed up a customer’s path to purchase by showcasing items they are most likely to be interested in.

Ecommerce recommendations can be based on items other customers have purchased, situational context, or customer browsing history, among other things. As a powerful driver of purchase intent, recommending products can be useful across an entire e-commerce site, from the homepage to the product page to the shopping cart. Often, brands will also use ecommerce recommendations in their retargeting campaigns, regardless of whether they’re delivered via email or a social media app like Whatsapp.

Below are some of the places where brands can include product recommendations:

Homepage

The first page that visitors coming from direct traffic will see, the homepage serves as an important welcoming point for new visitors and should be used to introduce potential customers to your brand, products, and the latest deals and discounts.

On the other hand, for returning customers, the homepage can display personalised recommendations, including products they have browsed previously, to persuade them to make a purchase.

Popular products/Best-sellers/Trending

When it comes to making recommendations to new visitors you don’t have any data on, calling their attention to trending or most popular items is a good idea.

Take a look at how Book Depository does this:

However, Book Depository doesn’t stop there. It segments bestselling book recommendations by different categories, for example, “Bestselling Food and Drink Books”:

The popularity of items (in this case, books) chosen usually depends on the number of times other shoppers have purchased them in a specific period of time. However, in some cases, other factors may be taken into account as well, for example, the total number of views or clicks.

Note how the UK-based bookseller also includes customer ratings for each book, giving shoppers important information on each book and saving them a trip to a book review site. Almost 8 in 10 customers trust online reviews the same way they trust personal recommendations. Including reviews in product recommendations is, therefore, a no-brainer.

A similar idea is behind the eco-conscious fashion brand’s Nobody’s Child “Trending Now” section:

The items shown here are based on what’s trending at the online store right now.

eCommerce Recommendations In the media

Who said that eCommerce recommendations had to be based on other customers? The Irish book retailer Easons features an “In the Media” section that spotlights “the most-talked about books right now”:

The wording here is clever. If everyone is talking about these books, customers may feel like they have to read them too lest they be left behind.

Trending brands

For businesses that stock multiple brands, highlighting particularly popular brands can work as well.

For example, this is what visitors see on the Asos homepage:

Clearly, the brands Monki, never fully dressed, COLLUSION, Reclaimed Vintage, Topshop, and Weekday are responsible for the majority of sales that Asos currently makes. As another brand becomes more popular with customers, the “Trending Brands” section will change to reflect this.

Trending categories

Similar to trending brands, trending categories show the different categories that customers are most interested in. These are usually (but not necessarily) based on location.

For example, Holland & Barrett, a chain of health food shops, has stores in 13 countries. It also caters to customers in all 13 countries via its e-commerce store. Accordingly, the categories that appear in its “Trending Categories” section depend on where a site visitor is coming from.

Here’s what the “Trending Categories” section looks like in the US:

And here’s what it looks like in the UK:

Observe how the two sections differ. The only thing Holland & Barrett customers in the US and UK have in common is that they are interested in sleep & relaxation and chlorophyll.

For a fashion-specific example, look no further than H&M:

Notice how H&M shows trending categories across different sections, including “baby”, “kids”, “women”, and “men”. H&M’s “Trending right now” section is not location-based. In other words, it stays the same, regardless of where customers in the world are coming from.

eCommerce Recommendations for New arrivals

To emphasise new products, brands can incorporate a “New Arrivals” section on their homepage.

Here’s an example of Sephora’s “Just Arrived” section:

A “Just Arrived” section can be particularly beneficial to loyal customers. That is because they may already know what the brand stores, so being able to see new items at a glance will save them a lot of time.

For retailers that store multiple brands, it’s a good idea to show new arrivals from brands that customers have shopped with before, which is precisely what Nordstrom does:

Coming soon

For items that are yet to be released but can already be pre-ordered, a “Coming Soon” section can ratchet up the excitement.

This works exceptionally well with books but can be applied to pretty much any other item, as well.

Here’s how Easons does it:

Editor’s pick

An alternative to trending products, “Editor’s Pick,” as seen on the luxury department online store Lane Crawford, can help customers discover unique pieces chosen by people who work at the store and know its stock — and the world of luxury — inside out:

Etsy does something similar with its “Shop our selections” section. The eCommerce Recommendations in each category are hand-picked by Etsy’s editors:

So, rather than racking their brain trying to think of the best anniversary gift for a friend or a parent, a customer can go to “Anniversary gifts” and see what an Etsy employee would choose if they were in the customer’s shoes instead.

One of a kind

Yoox has a “one of a kind” section on its homepage that features products that have only one example of a specific item left:

Showing customers that there is just one of something left is an ingenious marketing trick. Customers know that they can either purchase the item that has caught their attention now or potentially risk losing the opportunity to buy it for good.

Previously viewed

Customers may not always purchase products that interest them immediately. Sometimes, they may want to think about it. Case in point: less than 20% of customers that visit an e-commerce store for the first time do so with the intent of buying something.

For this reason, it’s a good idea to include a “Previously viewed” section on your homepage, like Etsy:

A “Recently viewed” section can jog a customer’s memory and prompt them to purchase the item they considered buying the last time they were on your site.

Yoox also includes a “Recently Viewed” section on their homepage to ensure customers can complete their purchase quickly:

Daily deals

Who doesn’t love a good deal? The online marketplace eBay shows visitors a “Today’s Deals” section. Since the deals change daily, customers know that they need to make up their minds promptly. Otherwise, they risk missing out on a heavily discounted item.

Rather than showing deals across multiple brands, Nordstrom displays discounted items from brands they know customers already love:

Personalised recommendations

For customers that have visited/browsed an e-commerce store previously, brands can use historical data to show eCommerce Recommendations based on what they have viewed or bought in the past.

Here’s what Redbubble’s personalised recommendations section looks like:

Search page

When visitors go to the search bar on a brand’s page, they’re usually looking for something very specific.

Brands should try their best to surface the most relevant results at the top of the page so that customers don’t have to scroll through the whole category page before they come across a product they’re looking for.

Best match

Searching for a particular item on Amazon (in this case, “pan”), customers see a whole section dedicated to eCommerce Recommendations called “Amazon’s choice” or products Amazon believes to be the best match for a specific keyword:

Top-rated eCommerce Recommendations

Amazon also shows the top-rated products for a specific keyword:

Customers know: if other customers were happy with their purchase, chances are, they will be too.

Curated collections

Wayfair allows users to explore curated collections:

Rather than seeing lots of different lamps, site visitors can filter them by specific categories curated by Wayfair employees.

Visual search

Ikea lets its customers search for a particular item by uploading a photo of it and showing them the closest matches:

Although not perfect (notice the armchair among the recommended products), visual search can save customers a ton of time.

Category page

The category page is where customers can find all the items that fall within a particular category.

Popular products

Popular products that are low in stock can create a sense of urgency.

Net-a-Porter does this across all of its categories. Here’s an example from its “dresses” page:

The “Annabella asymmetric pleated printed crepe de chine dress” by Altuzarra is “low in stock,” a tactic that can encourage a customer interested in the dress to buy it immediately instead of thinking whether they actually need it and potentially missing out on it.

Etsy does something similar, but instead of saying “low in stock,” it is even more specific:

Seeing that there’s “Only 1 available” of an item they like and that it’s already “in 1 person’s basket” can create FOMO (fear of missing out) and prompt a customer to act quickly.

Top-rated products

Customers are naturally more likely to gravitate towards products that other people have rated highly — this is known as social proof.

Brands don’t even need to show the exact rating that an item received. Simply marking products with the words “Top-Rated” can go a long way in making the customer trust that the product is high quality.

This is exactly what Urban Outfitters does:

Product page eCommerce Recommendations

A product page is where potential customers can find out more about a specific product and add it to the cart.

However, just because a visitor clicks on a product page doesn’t mean that they will necessarily want to buy the item they’re viewing. For this reason, it is important that a product page includes other product suggestions. That way, there is a “next step” visitors can take to continue with their buyer’s journey.

Visually similar

A customer may like a specific item, but there may be something about it that puts them off slightly, like the material or sleeve design. Or, the product they love may not be available in their size.

By including a “Similar Items” section underneath the item, brands show eCommerce Recommendations that they are likely to like due to their similarity to the item they are viewing.

For example, when a customer views a blue sweater with stripe details by Victoria Beckham on Lane Crawford, the site suggests similar options, including a sweater with a stripe design and a colour block sweater.

Note how all the sweaters recommended are different shades of blue and include an interesting detail, whether it’s an off-the-shoulder sleeve or a slogan, resembling the original item (the Victoria Beckham sweater).

What other customers are doing now

This can include things like “x people are viewing this product right now” or “this item is in x people’s baskets.” Again, the idea here is to create a sense of urgency.

When viewing popular items on Etsy, customers not only see “Low in stock” but also “Selling fast! Only 3 left, and 9 people have it in their baskets.”

More from this brand/shop/designer

Most customers have their preferred clothing brands. For retailers that stock multiple brands, showing eCommerce recommendations from the brand a customer seems to particularly like can be an easy way to boost sales.

For example, when a customer views an item from “Treasure & Bond” on Nordstrom, the site suggests more products from the same brand:

Yoox does the same thing, but for a specific designer:

Notice how Yoox also includes the sizes available underneath each recommendation, saving customers time and potential disappointment if they click on a product page and realise that their size is out of stock.

Customers who searched for/bought x also viewed/bought

To show customers what shoppers with a similar taste to them also viewed or bought, brands can use “Others also viewed” or “Others also bought” recommendations, as seen on H&M:

Complete the look

In the fashion industry, it is all too common for customers to decide against buying a specific item because they don’t know how to style it. Outfit recommendations can solve this problem while at the same time, enhance customer value by cross-selling.

Lane Crawford includes a “How to style it” section underneath all it items:

Yoox does something similar with its “Complete the look” section:

Tommy Hilfiger goes a step further by providing unique outfit recommendations for the same item (in this case, a dress) based on different occasions.

Here’s how, according to Tommy Hilfiger’s stylists, you could wear its “fit and flare twill dress” if you were going for a “glam” look:

And here’s how you could wear the same dress if you were more into “street style.”

By the way, the eCommerce Recommendations change every time a customer refreshes the page, so there are infinite outfit combinations for a customer to see.

Here’s another suggestion of how to wear the dress for a street style look after refreshing the page:

Shop the look

The Outnet recreates their own editorial photography outfits as fully shoppable outfit recommendations:

When specific items go out of stock, they are automatically replaced with the most visually similar option in stock so that the retailer can continue selling the full look even when the original item is no longer available.

This approach by The Outnet prolongs the return on investment from their editorial costs and reduces the time and effort merchandising teams have to spend on outfit recommendations. As a result, they increase their capacity to focus on other key areas where their expertise will make a difference to the business.

Evereve, on the other hand, offers a hybrid service of both “Complete the Look” and “Shop the Look,” covering both items they have editorial photography for but also showing unique outfit recommendations for ones that don’t have an editorial look. This way, they can benefit fully from all their products while selling their editorial looks.

Here, Evereve recommends the exact items shown in the editorial photographs, down to the jewellery worn by the model:

In contrast, the eCommerce recommendations in the example below don’t match the editorial photographs exactly but are items that would go well with the product (white tank top) being viewed.

Both Evereve product pages also have a “How to wear it” section that displays photos of customers wearing the item, with product suggestions to recreate their outfits:

Personalised recommendations

Based on what customers have looked at, Tommy Hilfiger gives personalised recommendations:

Frequently bought together

In an attempt to upsell customers, Proviz includes a “Frequency bought together” section on its product pages:

New items

When looking at a specific product, Trader Joe’s customers are presented with a “So, What Else is New” section to upsell them products that are new in stock:

Checkout/cart page eCommerce Recommendations

Just because a customer has reached the cart or checkout page doesn’t mean that they’re not interested in anything else the brand has to offer.

In fact, both the cart and checkout pages are ripe for up-sell and cross-sell opportunities — customers have already decided to buy something from a brand and are therefore more likely to increase their spend if shown attractive potential additions to their shopping list.

Brands can make general recommendations or recommendations based on the items that the customer has in their cart.

Don’t forget

If a customer adds items to their basket on Amazon but then leaves the site without actually purchasing them, Amazon will automatically save these items and include them in a “Your Items” section next time they go to buy something.

Recommended products

When Wayfair holds a sale, it shows you a “Your Featured Sales” section in your cart. The items in the section are based on what you’ve added to your cart (in this case, curtains).

In addition, Wayfair also features other items you may need depending on what it is you’re buying. Here is what the site recommends you also buy when you are about to purchase shower curtains:

In contrast, IKEA shows eCommerce Recommendations with random items it thinks you may be interested in. Here are its recommendations when you purchase a sofa:

When customers go to check out on Tesco, the grocery and general merchandise retailer suggests items it knows you buy regularly but for some reason have omitted this time:

Rather than personalised recommendations, Aritzia’s shopping cart page includes a “Stock up on essentials” section, regardless of what customers are purchasing (in this case, a blazer):

Buy it again

Amazon knows that sometimes, customers may want to buy the same item again, which is why it has a “Buy it again” section on the cart page:

Popular products

As a last attempt to upsell its customers, & Other Stories recommend “Popular Products” to customers that are about to check out:

Frequently bought together

When shoppers add an item to their cart, Target recommends them items that are frequently bought together in its mini-cart:

404 page eCommerce Recommendations

In an ideal world, customers would never see a 404 page. However, that is not realistic, and often, 404 pages mean the end of a customer’s session.

The good news is that instead of seeing 404 pages as a failure on your part, you can turn them into opportunities to inspire customers to continue with their journey.

Recommended products

In the event that a product a customer is looking for is unavailable and returns a 404 page, Steve Madden shows them alternatives:

Best-sellers

Urban outfitters, on the other hand, brings up some of its most popular items instead:

Pop-ups

No one likes pop-ups, right? Not quite. While it is true that irrelevant pop-ups are annoying, pop-ups that bring visitors’ attention to trending items or products picked out exclusively for them based on their activity can turn hesitant visitors about to leave your site into enthusiastic customers.

Trending items

When a customer returns to the Lammeskindet site, they see a pop-up that welcomes them back and shows them the most popular items with quick links to each and a prompt to “get them before they’re gone.”

Other items you may like

Rather than a separate section on its product pages, Crocs instead uses a pop-up to recommend items the customer may love based on the product they are currently viewing:

Recommended products

To stop customers from leaving their site empty-handed, the Three Drops of Life shop brings up a pop-up that recommends visitors items picked out just for them right before they are about to exit the page:

Tommy Hilfiger does the exact same thing after a customer is inactive on their page for a while:

Retargeting campaigns

The best brands engage customers long after they’ve left their site, regardless of whether they’ve made a purchase or not.

Use email and social media apps to send customers information about new stock and trending items and share personalised items and outfit ideas picked out specifically for them.

New arrivals

Every time the Irish chocolatier Bean and Goose has new stock, it sends out an email newsletter about it to their customers:

Popular products

The fashion brand Na-kd sends out regular email newsletters featuring popular products and must-haves to its customers to encourage them to visit the site.

Back in stock

For items that are currently out of stock, Zara allows customers to sign up for an email alert. When the product is back in stock, the fashion retailer notifies the customer:

Outfit recommendations

Rather than just featuring items on their own, fashion brands can provide outfit recommendations, either via email or social media apps like Whatsapp:

How to style it Recommendations

A great way to get your customers to come back to your shop right after they buy something from you is to send them a “How to style it email“. To make the most of this and increase your chances of another sale, it is a good idea to provide item recommendations for different occasions:

New Item Email Recommendations

Poshmark sends its customers a“new and exclusively for you” email with new item recommendations:

H&M sends customers a periodic email with personalised item recommendations based on items they have browsed or bought:

Get Started with Ecommerce Recommendations Today

With the right item recommendations, brands can boost user experience and engagement, increase customer retention, and ultimately improve their bottom line.

However, as the above examples show, there are many options to consider when it comes to recommending products. For this reason, many brands find getting started with product recommendations daunting — but it doesn’t have to be this way.

The team of experts at Intelistyle can help you decide what route your brand should take with recommendations to optimise your business and meet your objectives. Ready to talk ecommerce recommendations? Get in touch with us today.

Book a free consultation

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Intelistyle awarded best AI Product in Fashion at CogX 2021

Kostas Koukoravas — Wed, 23 Jun 2021 16:36:26 +0000

Intelistyle awarded best AI Product in Fashion at CogX 2021

London, June 2021. We are pleased to announce that Intelistyle was awarded “Best AI Product in Fashion” by the judges at the prestigious CogX 2021 festival, alongside global leaders, CEOs, entrepreneurs, policy makers, artists, academics and activists – addressing the question “How do we get the next 10 years right?

Winners were decided with the help of an expert team of judges featuring some of tech and global innovation’s most prominent change leaders, including: Abadesi Osunsade, VP Global Community & Belonging for Brandwatch, Education & Healthcare Technologies Investor and Advisor Alan Greenberg, Dr Milly Zimeta, Head of Public Policy at Open Data Institute, Gary Stewart who is the CEO and Founder of FounderTribes Educational Technology Ltd, Gillian Docherty OBE, CEO of The Data Lab, Cambridge University Professor, Jon Crowcroft, Kate Arthur, CEO & Founder of Kids Code Jeunesse, Robert Hercock, Chief Research Scientist, at BT Group, Terry von Bibra, Director of Numenos, Priya Guha, Venture Partner of Merian Ventures, Innovation and Business Development at University of Oxford, James Semple and many more.

You can see the full list of winners at the CogX website.

The award is a welcome recognition of the work of Intelistyle’s commitment to build the most accurate Fashion AI solution in the industry. In 2018 we saw a first glimpse of the power of Intelistyle’s AI, when it managed to outperform human stylists at London Fashion Week. Since then, Intelistyle’s Fashion AI has improved its accuracy even further to create product recommendations for fashion that deliver significant increases in revenue for it’s clients.

Starting in the luxury space it’s client list has grown to encompass mid market and fast fashion brands and retailers that see the ROI of differentiating their online user experience with a fashion specific recommendation engine.

Our vision for the future remains unchanged. Intelistyle is here to help fashion retailers create digital discovery experiences that increase conversion, basket size and retention, by helping their customers find the right clothes to look and feel great.

How we deliver on that vision changes every day by using the latest advancements in Artificial Intelligence to help retailers get to know their customers and serve them with more accuracy than ever before.

Here’s to a more fashionable, sustainable and personal future.

– The Intelistyle Team

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Best Practices For Product Attributes

Kostas Koukoravas — Fri, 11 Jun 2021 10:27:44 +0000

Best Practices For Product Attributes

In our previous post, we talked about product attributes — what they are and why they matter. In case you missed the post, here’s a quick recap. Product attributes are characteristics or features that a product may or may not have (for example, size, colour, fit, and similar) and are a way for brands to distinguish one product from another.

For retailers, product attributes are incredibly important and can play a crucial role in whether a brand succeeds or fails. Without product attributes, customers will not be able to find what they are looking for, or, on the off chance that they do find their ideal product, the scant quantity of product information available will not allow them to make an informed decision that would lead to purchase.

Aside from streamlining and customising the customer experience, product attributes also make life easier for inventory management staff (by optimising the inventory management process) and floor staff (by simplifying inventory, making it easier to find items customers are looking for in-store).

Product attributes are the hero of fashion personalisation. However, the question remains: how can brands incorporate product attributes into their product pages? Brands that want to make the most of product attributes should follow the below best practices.

1. Understand Which Product Attributes Are Important to Your Customer

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Although it is generally a good idea to attach as many relevant attributes to a product as possible, not all product attributes are created equal. Customers assess and evaluate products based on attributes that are important to them, so knowing which product attributes to highlight is particularly important.

There are a number of ways brands can figure out which product attributes are most relevant to their customers, including:

- Market research. Through surveys and questionnaires, brands can directly ask customers which product attributes they pay attention to when shopping on their site and which product attributes they ignore. For example, one study that analysed the preferred product attributes for sustainable outdoor clothes found that the most important attributes for that brand’s customers were the type of down, label, price, and fabric.
- Text mining or product reviews. In addition to surveys, brands should also pay attention to consumer feedback. Often, when customers leave reviews, they will mention specific product attributes without even realising that they’re doing so, including product attributes that may turn them off a product. For example, if a photo of a dress looks red but customers complain that it is actually orange in real life, it is a clear sign that a brand needs to include its colour as a product attribute.
- Product comparison. Comparing similar products, regardless of whether they belong to the brand in question or a competitor, can also help retailers figure out which product attributes a brand’s customers are most focused on in a specific product category.

- Using product attributes directly. Examining the product attributes customers search for most often on a brand’s site is another way a brand can understand customer preferences and backgrounds (i.e., where in the world they’re located and their demographics). For example, customers from one area may frequently search for maxi dresses when shopping for dresses, whereas shoppers from another region may instead be more interested in mini dresses. Knowing customer preferences based on the area they come from can allow brands to make better regional stock allocations.

2. Optimise Content for Search Engines (SEO)

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While knowing which product attributes your customers value is vital, proper attribute placement also requires knowing where on your product pages you should include them to optimise your store for search engines. Two of the most critical places brands should incorporate product attributes into are product titles and product descriptions.

Properly optimised product titles let customers know whether the product they’re looking at is something that meets their needs or not at a glance. When a customer comes across a product with a product title that seems to match what they’re looking for, they’re highly likely to click on it to learn more about it via the product description. The best titles for products tend to be written in precise, simple, and clear language and include both the category and subcategory of the product, the model, and any other essential attributes.

Just like product titles, product descriptions should also be optimised based on the product’s attributes. This means not only including any relevant information about the product — such as colour, size, material, and fit — but also explaining what the product does, even if it’s something as self-explanatory as a rain jacket. To provide further value, brands can offer additional information, such as styling tips.

Note that a long product description does not equal a good product description. Every word and every sentence in a product description should add value to the product. If it doesn’t, it should not be there. That means that replicating content from other products isn’t good enough and can actually cost a brand its customers.

3. Automate Product Tagging

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If copy-pasting from one product description to another is detrimental to a brand’s success, why do so many retailers continue to do so? The answer is simple: Because they still tag their products manually.

Tagging products manually is a time-consuming process that usually requires retailers to hire additional labour. This pushes up costs and makes stores less profitable. However, that’s not the worst of it. Humans are also subject to bias and are apt to make costly mistakes, like forgetting to match all product categories or sort through relevant attributes. The end result? A customer won’t find what they’re looking for, and a brand will lose a sale.

In contrast, automated product tagging improves operational efficiency, making the process of tagging products faster and cheaper. It also ensures brands have accurate, standardised, and consistent metadata.

4. Invest In a High-Quality Attribute Tagging Product

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When it comes to products that offer automated product tagging, there is an abundance of options to choose from. However, finding an attribute tagging product that delivers on the promises it makes is not easy. For this reason, it is vital that brands looking to automate their product tagging do extensive research before they invest in an attribute tagging tool. A poor quality attribute tagging product may actually be worse than tagging all your products manually. Here are some things to consider when choosing an attribute tagging tool:

Fashion-specific data set

For fashion brands, a generic list of product attributes is useless. Instead, you want to find an attribute tagging tool that offers a fashion-specific data set that can be calibrated to the needs of an individual retailer.

Intelistyle has 500 fashion-specific attributes developed with the sole goal of addressing the needs of brands within the fashion industry.

With Intelistyle, you can tag each product using a hierarchical product tagging system, which makes it easier to control your stock. For example, when tagging a silk blouse, you can choose “blouses-shirts” as the general category and “blouses” as the subcategory. Known as “mutually exclusive” product tags, these tags allow you to sort your product catalogue into high-level categories, making it easier to find products quickly.

However, when tagging the same silk blouse, you can also add additional tags, such as “silk” (fabric), “floral” (print), “straight” (cut), “fitted” (fit), “smart” (occasion), “summer” (weather), and so on. Known as “non-mutually exclusive product tags,” these attributes can help brands enrich their catalogue to full capacity.

Visual recognition and multi-product detection

An attribute tagging product that features visual recognition technology, such as Intelistyle, will detect and tag all products on product photos, regardless of whether they’re editorial-style photos or user-generated full-body shots.

Attribute groups

The last thing any brand wants is to accidentally omit product tags that will either help customers find their products in the first place or convince them that a specific product is exactly what they’re looking for. Attribute groups break down and assign tags for each product in a categorical way, ensuring that your product is tagged optimally.

Optional control

A good product tagging tool should give a merchandising team the ability to approve or edit product titles and descriptions. While an attribute tagging tool will do all the hard work for you, some retailers may prefer to have a human team member check that product titles and descriptions match what they had in mind.

Final Thoughts

With customers growing more impatient and demanding, retailers can’t afford to forego product tagging. However, the days when brands could get away with tagging their products manually are long over. From improving customer experiences to freeing up staff time, a high-quality and reliable attribute tagging tool, like Intelistyle, can give retailers the edge they need to succeed in this ever-changing and evolving industry.

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What Are Product Attributes And Why Do They Matter for Fashion Brands

Kostas Koukoravas — Fri, 11 Jun 2021 10:04:50 +0000

What Are Product Attributes And Why Do They Matter For Fashion Brands

“Red suit,” “black jeans,” “gold bikini,” “white t-shirt,” “brown shirt,” and “black leather skirt” were among the most searched clothing items in 2020, according to Semrush. However, even if your store stocked all of the above, that doesn’t necessarily mean that you saw an influx of customers last year or that you sold a notable volume of these items.

As demonstrated by Semrush, unless they’re just casually browsing, customers shopping for clothes typically look for items that meet their specific requirements at a particular moment in time. This finding means two things. Firstly, to find items that meet their needs, customers tend to search for certain features, or attributes, within particular categories of clothing. Secondly, and critically, brands that use product attributes sell their stock and grow their business.

On the other hand, brands that fail to implement product attributes are inevitably left behind. Your brand could sell twenty different types of red suits, but if customers can’t find them, they won’t buy them. As a result, understanding that product attributes drive this status quo is vital.

What Are Product Attributes?

Every product you stock has a unique set of features and characteristics, which can be described as “product attributes.” Also known as metadata or product tags, product attributes help you and your customers distinguish one product from another.

For example, a blouse can be differentiated from another blouse by its brand, material, and colour, among other things. No two blouses are the same (unless, of course, they’re the exact same product). Even two blouses that look very similar can differ in their cut, length, hemline, and similar.

In fashion, product attributes commonly fall under the following attribute groups:

Fabric/material
Pattern/print
Cut
Fit
Occasion
Weather
Length
Colour type
Colours
Waistline
Hemline
Neckline
Sleeves.

Groups can be further refined into attributes. For example, fit can be sorted into categories such as fitted, chunky, oversized, skinny-fit, slim-fit, regular-fit, bandage, bodycon, boxy, loose, slouchy, maternity, and so on.

Why Do Product Attributes Matter?

The importance of product attributes for fashion retailers cannot be understated. Product attributes are the building block for all customer-facing/user experience and internal/operational efficiency technology solutions. Having a robust foundation of product attributes and accurate metadata allows brands to easily adopt additional revenue-boosting solutions.

Below are just some of the reasons why some of the most successful retailers value product attributes.

Improved product discovery

Imagine this scenario: Patricia, a potential customer, goes onto your brand’s site and searches for a “polka dot summer dress.” Patricia is in the right place: your brand has a dress that meets the customer’s description exactly.

However, your brand’s products are not tagged correctly, forcing a potential customer to wade through multiple pages of irrelevant results before they finally find a dress that resembles what they’re looking for. What are the chances that Patricia will sift through your product catalogue looking for what she wants? Honestly, extremely low — it’s more likely that Patricia will get frustrated, go back to Google, and visit a competitor’s site instead.

This sort of scenario ultimately has one result for your brand: site abandonment. The vast majority of site abandonment happens during the discovery phase when visitors can’t find what they are looking for quickly and easily. That’s because customers — especially customers that shop online — are impatient. Research shows that less than a third of customers will put up with more than two inconveniences before they leave an e-commerce store. Furthermore, almost two-thirds of consumers say that if a shopping experience is poor, they are unlikely to shop with the same brand ever again.

On the other hand, if a brand’s stock is tagged with correct and detailed attributes, visitors can find exactly what they are looking for. Better search results inevitably lead to improved product discovery and, most importantly, a frictionless customer experience.

The usefulness of product attributes also extends beyond just digital storefronts. For shop floor assistants, properly tagged products make it easier to locate items in-store customers are looking for. Rather than spending valuable time attempting to hunt down that skirt a customer may be interested in, shop assistants can instead spend that extra time delivering personalised and attentive experiences.

Persuasive product pages

When customers find the item they’re looking for, product attributes can provide them with additional information on top of what may be apparent from the product title, description, and photo.

Seeing how cart abandonment often happens due to concerns about the quality or fit of clothing — in one study, 20% of purchase failures were the result of incomplete or unclear product information — having extra information can influence a customer’s purchase decision and is especially important when shoppers can’t see or touch the product physically.

Increased personalisation

To further boost conversions, brands can combine product attributes with insights into customer behaviour, like their geographic location and past purchases. As a result, you can make better, more relevant recommendations to both new and returning customers.

Online, this personalisation can take the form of “Complete the Look” outfit recommendations and relevant, customer-specific promotional campaigns. In store, understanding each customer’s style based on the types of product attributes they go for can help store assistants offer VIP experiences to more customers through personalised styling recommendations.

Predictive and stock performance analysis

Product attributes are also invaluable when it comes to understanding more general customer preferences. Retailers who have implemented product attributes can see what type of products are selling versus the types that are not. For example, if you can see that “bishop sleeves” are continuously selling out; you know it makes sense to stock more blouses, dresses, and jumpers that feature that specific sleeve type. Conversely, if you notice that “puff sleeves” are constantly getting discounted, you gain valuable insight into what your customers don’t like.

Product attributes also help brands draw on and understand seasonal trends and how they impact their customers’ purchasing decisions. If the vast majority of a brand’s customers search for relaxed-fit, floral, maxi dresses with cowboy boots, then they know that their customers have adopted the “Boho Chic” trend. Brands can then push this trend more in their store, for example, by automatically creating an occasion/trend shop by pulling the products that have those attributes, as well as use this trend on other touchpoints.

Final Thoughts

With so many use cases, leveraging attributes is increasingly vital for growth-oriented fashion businesses. However, in addition to understanding the value of product attributes, you also need to know how best to implement them. To learn about the best practices for product attributes, check out part two of our blog post series on product attributes, where we outline the four steps each brand should take if they want to increase sales with product attributes.

Book a free consultation

The post What Are Product Attributes And Why Do They Matter for Fashion Brands appeared first on Intelistyle.

Fashion Personalisation: Top 12 Examples

Kostas Koukoravas — Fri, 28 May 2021 13:43:33 +0000

The Top 12 Examples of Fashion Personalisation

Fashion personalisation is changing the paradigm around consumer fashion. Trends that once came from the top down are now crowdsourced from customers themselves as individuals search for ways to customise their looks and make their style uniquely their own. For this reason, the vast majority (80%) of consumers today prefer to purchase from retailers that offer personalisation. However, for fashion businesses, leveraging personalisation can be a challenging task — particularly if you don’t quite know where to start.

When fashion personalisation is implemented poorly, businesses can end up giving customers too many options, which, rather than boosting conversions, engenders decision paralysis. It doesn’t help that the fashion industry also has a tremendous amount of variables (like technological changes and economic conditions, to name a few) when it comes to consumer behaviour, and understanding what really drives customer purchases can be a challenge.

To help demystify how fashion personalisation works in the real world, here are ten examples of this trend in action.

1. YOOX: A Virtual fitting room to dress up your digital avatar

(Source)

Launched in 2018, YOOXMIRROR is an AI-powered virtual styling app developed by YOOX, an Italian online fashion retailer, that lets users preview how they would look in a full outfit. By taking a selfie or uploading a photo, YOOXMIRROR users can create a digital avatar of themselves that they can dress in more than 50,000 digitised clothes, shoes, and accessories from the store’s catalogue. Once users have found the outfit they like, they can share it with their friends on social media for a second opinion or make a purchase.

2. The Outnet: Wear It With

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Styling clothes is hard. Regardless of whether a customer has fallen in love with a piece that they know is going to be hard-to-wear or they’re looking to upgrade their wardrobe but don’t want to invest in a personal stylist, being able to see other clothing items that would work with the piece they’re eyeing can be incredibly helpful — especially if they can buy them all on the same site. On TheOutnet, a site that sells luxury designer fashion brands at better prices, every item features a “wear it with” section that recommends customers items that would go perfectly with the product they’re about to buy, based on the look photographed.

3. Tommy Hilfiger: Styling for Occasions

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To make their customers’ product discovery journey easier, Tommy Hilfiger makes product styling recommendations that are tailored for every event, including “glam,” “street style,” “classic,” “casual,” and “sporty.” Not only does this make cross-selling and up-selling easier, but it also shortens the customer’s journey from discovery to purchase.

4. Lane Crawford: Visual Similarity and Complete the Look

(Source)

Luxury brand Lane Crawford uses fashion personalisation with AI-powered customised recommendations to find items that look similar to a customer’s first option but with a twist, for example, a slightly different cut or shorter sleeves. Once customers find the piece they love, they can then use Lane Crawford’s “How to Style it” feature to complete the outfit. In contrast to most other fashion brands, Lane Crawford does not recommend additional products based on the look you see in the styling shot. Rather, the feature showcases different products curated by Lane Crawford’s stylists that are available for purchase on the same site.

5. Victoria Secret: Personalised Chatbot

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Launched in 2016, Victoria’s Secret’s Pink line (VSPINK) has a Kik chatbot that helps women find their perfect bra. Whether it’s asking for feedback about a customer’s measurements or recommending a bra for a particular occasion, VSPINK’s Kik bot creates a fun, personalised customer experience that is ideal for younger users. Importantly, since VSPINK’s chatbot is integrated into a popular messaging platform, new users can access it without having to download or install another mobile app on their phones.

6. MaxMara: WhatsApp Remote Selling AI Chatbot

(Source)

With two billion active users worldwide, it comes as no surprise that MaxMara wanted to utilize the most popular mobile messenger app in its marketing efforts — WhatsApp. By integrating Intelistyle’s AI chatbot experience in WhatsApp, Max Mara was able to provide customers with a personalized shopping experience on a channel they use daily. From answering customer queries about products immediately to giving them personalized recommendations based on an automated styling interview, Max Mara’s WhatsApp chatbot led to x18 higher customer engagement.

7. Ralph Lauren the Custom Shop: Custom Embroidery Instore

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As personalisation overcomes standardisation, consumers are increasingly interested in products they can customise and make uniquely theirs. Ralph Lauren’s Polo Custom Shop puts this principle into practice by allowing visitors to create their own custom embroidery pattern. With only a few taps on their smartphone or tablet, customers can make a design in a matter of minutes and have the staff embroider it over their favourite polo shirt, cap, or blazer. Additionally, Ralph Lauren lets customers design their own sweaters by choosing the colour and colour layout, front and back graphics, and sleeve designs.

8. ZOZO: Size Personalisation Through a 3D Body Measurement Suit

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Japanese retailer ZOZO has developed a 3D body measurement suit that allows customers to get highly accurate scans of their bodies. Using ZOZOSUIT 2 and a smartphone camera, customers can take precise measurements from the comfort of their homes. Because ZOZOSUIT 2 has 20,000 fiducial markers, its scans have an average error of 3.7 mm, meaning that customers can finally say goodbye to general sizes that don’t ever really fit and only buy clothes that are tailor-made for them.

9. MTailor: Size Personalisation Through Mobile Phone App

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MTailor allows users to take their measurements in 15 seconds or less. Once a customer has spotted a piece of clothing they like, they can use MTailor’s app and their phone’s camera to record a quick video. The app’s 3D Point Cloud technology measures 16 body features and then creates a pattern that the company’s tailors can use to make clothing that fits perfectly.

10. Dolce & Gabbana: Instant access to styling service

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In some cases, AI stylists can be better than human stylists. To enhance the customer shopping experience in their stores, Dolce & Gabbana partnered with Intelistyle to equip their front-line sales representatives with instant access to AI styling tools. This allowed the Dolce & Gabbana team to provide a VIP experience to every customer, taking into account their unique features like hair colour, body type, and preferences and recommending visually similar products if a particular item was out of stock. The results speak for themselves: employees who used AI styling expertise and services saw a 100% boost in their sales efforts.

11. CoverGirl: PersonalisedMakeup Try-on

(Source)

At CoverGirl’s flagship store in Times Square, visitors can immerse themselves into a makeup-driven experience. Once they step into the store, visitors are greeted by their beauty AI assistant, Olivia, who advises on store products, makeup trends, and lipstick application. From there, customers can use augmented reality mirrors to see how a particular lipstick they’re holding in their hands would look on them without actually having to swatch it on their lips. Shoppers can then try on additional makeup products to complete the look, take a photo, and receive personalised product recommendations via email.

12. Very: Weather-Based Personalisation

(Source)

British online retailer Very took an ingenious approach to personalisation. Knowing that the weather has a massive impact on business — particularly in Britain, where the weather is so unpredictable — Very launched a campaign that made clothing recommendations based on local weather patterns. When shoppers visited Very’s website or app, they were instantly presented with products relevant to their local weather conditions, like umbrella offers if it was raining in their location or summer clothes if they were from a warmer climate.

Final Thoughts

Finding the right clothes is never an easy task. Between browsing the internet and window shopping, a customer’s journey can last hours, days, or even weeks. However, by harnessing the power of personalisation, fashion brands can create customised journeys that can lead even the most indecisive customer to the checkout point.

Don’t let this trend pass you by while other brands increase their conversions and keep their customers coming back for more. Instead, contact us for a free consultation and join our exclusive list of satisfied customers today.

Book a free consultation

The post Fashion Personalisation: Top 12 Examples appeared first on Intelistyle.

Fashion Personalisation: The Ultimate Guide

Kostas Koukoravas — Wed, 19 May 2021 16:34:40 +0000

Fashion Personalisation: The Ultimate Guide

For years, consumers have passively imitated popular celebrity looks and followed the latest fashion trends when putting together outfits or updating their wardrobes. Now, however, fashion personalisation is set to change this status quo. Making facilitating individuality a requirement for every brand, it will soon turn the buyer’s journey on its head.

Although fashion personalisation has been the top-rated fashion trend since 2018, we haven’t seen its full impact just yet. Indeed, McKinsey predicts that personalisation will become the main factor behind marketing success in retail within the next five years.

That said, even though personalisation will undoubtedly define future retail success, it is an incredibly important factor for today’s consumers too. According to Epsilon and GBH, 8 out of 10 online customers are already more likely to buy from companies that help them find personalised fashion that looks perfect on them.

What Is Fashion Personalisation?

Fashion personalisation allows companies to deliver an individualised and differentiated experience to each customer.

Whether it’s personalised recommendations based on the clothing items customers have just viewed (i.e., “if you like this t-shirt, you might also like these t-shirts), AI chatbots that give consumers fashion advice based on their location and unique physical characteristics, or virtual fitting rooms that allow people to try on clothes from their homes, fashion personalisation is any technology which makes it easier for customers to express their individuality.

Fashion personalisation puts customers at the centre of the shopping journey. Instead of wading through hundreds of items they don’t care about, customers can find the products they’re looking for much faster.

For businesses, a core benefit is a faster customer journey from product discovery to conversion. More importantly, however, being offered personalised buying recommendations reduces the analysis paralysis that causes almost 40% of customers to leave e-commerce stores empty-handed – a problem that is even more acute in fashion, where matching people to the correct sizes is trickier.

Why You Need Fashion Personalisation

Consumers are growing accustomed to personalised fashion — so missing out is out of the question.

Because personalisation is something that consumers want, most are willing to pay for it, at least in kind. Even as data privacy becomes a pressing issue, research shows that consumers are eager to give away more personal data in exchange for a customer experience that’s tailored just for them – and in turn, give your company plenty of leeway to cross-sell and up-sell different products.

Brands that take personal preferences seriously — instead of recommending the same in-season items to everybody — can use AI to ease the shopping experience and even recreate (or exceed) the personal service their customers would receive in-store.

Types of Fashion Personalisation

Some of the most popular types of fashion personalisation techniques include:

Visual similarity

Companies can use AI to show customers other products that visually resemble what they are looking for — a great short-term solution if a specific item is out of stock.

Unlike Amazon’s collaborative filtering, which recommends other products that customers with similar preferences have browsed or purchased, visual similarity analyses specific attributes from an item a customer already likes.

Implementing visual similarity makes business sense: visual similarity can deliver 130% more revenue than collaborative filtering.

Complete the look

Besides building a brand’s name, “complete the look” recommendations create valuable opportunities to maximise conversions by cross-selling and upselling more products.

Unlike human employees, AI can sort through an entire catalogue of clothing and accessories off the bat and give a sensible recommendation to customers who don’t know how to complete their outfit or style a piece of clothing.

Personalised recommendations

Personalised recommendations allow brands to curate what customers see based on factors like gender, region, and browsing and purchase history.

In this way, personalised recommendations go beyond the simplistic clustering of different customer preferences presented through industry-agnostic recommendation engines. Instead, personalised recommendations allow brands to adapt to changing customer preferences as well as to predict which items specific customers might purchase in the future.

For example, by examining the cut, colour, fabric, and pattern of previous purchases to create a unique customer profile, fashion AI can help brands suggest hyper-personalised pieces that have slightly different attributes. With personalised recommendations, customers can find new pieces that might work with their existing outfits or fashion items that stand out on their own.

Visual search

Humans are visual creatures which is why using keywords feels so unnatural to us. Customers who are forced to slog through keyword searches will always give up eventually.

However, by offering customers visual search features, brands can provide them with the opportunity to find exactly what they’re looking for in a matter of seconds, even if they can’t put their wishes into words.

Visual search is especially important now that most people get their fashion inspiration from social media platforms. More than 70% of people make fashion, style, or beauty-related purchases after spotting something on Instagram. In instances where the original poster does not tag a piece of clothing they’re wearing in the picture, visual search can be invaluable.

AI styling advice

Regardless of whether they come from friends or store clerks, opinions help customers pick clothing that suits them.

However, while chatbots and human stylists may ask the same questions — such as body type, skin, hair, eye colour, or occasion — AI chatbots are better at sorting out all the variables and coming up with the best styling advice.

Indeed, fashion chatbots are increasingly able to beat human stylists at their own game and are already being used by famous brands, including Victoria’s Secret, Asos, and Sephora. That’s not surprising considering that AI chatbots can universally deliver the personalised and attentive experience, which was once the preserve of VIP customers at luxury brands.

WhatsApp marketing

WhatsApp’s popularity makes it a natural platform for consumers to seek and get real-time communication from their favourite brands.

Whether it’s answering product queries, making personalised recommendations, or offering last-minute discounts to reduce cart abandonment, WhatsApp marketing is an excellent tool to acquire and convert new customers as well as reactivate them.

Smart mirrors

Smart mirrors allow customers to get in-store styling advice and “preview” themselves in an outfit without having to visit the fitting room.

Brands like H&M have already tried smart mirrors with voice and facial recognition features and even allow users to take selfies and download them into their phones.

Email marketing

Acquiring a new customer can cost up to five times more than retaining an existing customer. Existing customers have also been shown to spend 31% more than new customers.

So how do you grow retention rates and repeat purchases? With well-designed and highly personalised email marketing campaigns.

As fashion brand marketing gets personal, data-driven email campaigns are increasingly curated based on customers’ preferences and past purchases. For many brands, segmented, targeted, and personalised emails are responsible for more than half of their revenue.

Sizing technology

One of the downsides of online shopping is that it’s difficult to gauge the size of a piece of clothing from a picture. Sizing technology makes it easier for customers to find the right size for them while also helping retailers increase conversions and keep returns to a minimum.

Virtual fitting

With the pandemic keeping most clothing stores closed, many brands (such as Macy’s and Adidas) have accelerated their adoption of virtual fitting rooms.

Today, consumers can use their smartphones to try on a brand’s entire catalogue from the comfort of their bedrooms before they make their online purchase.

Final Words

Finding the right dress has always been a science of its own. But thanks to fashion personalisation, decoding and delivering precisely what the client wants is now easier than ever — as long as you have the right AI styling platform in place, of course.

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Intelistyle voted judges’ top pick among leading retail startups

Kostas Koukoravas — Tue, 04 May 2021 15:16:22 +0000

Intelistyle voted judges’ top pick among leading retail startups

Intelistyle has been named among the top 40 retail tech start-ups operating globally in Retail Week World Retail Congress’ (RWRC) second annual Discovery report, published today.

Most retailers know they need to work with tech start-ups to give them a competitive edge – it is understanding which firms are going to truly add value that is the challenge. Judged by an a panel of retail and start-up experts*, the Discovery report tells retailers all they need to know.

Virtual try-on assistants, vertical farming, ‘save now, buy later’ payments, in-store marketing robots and bookable shop space are just a handful of fresh-thinking players featured.

And it is this fresh thinking that is required if retailers and brands are to remain competitive and balance bottom lines with customer expectations as disruption from the pandemic persists.

Drawing on case studies from Discovery, the ROI from retailer-start-up partnerships is clear:

M&S has trialled a partnership with instant virtual try-on start-up Texel to drive purchasing intent; customers that use the tool are five times more likely to purchase and 30% less likely to return items
ASDA has partnered with Intelistyle to style customers in physical stores, allowing them to receive automated outfit recommendations for their body type, skin and hair tone.
Carrefour UAE is using Simbe Robotics’ inventory robots Tally to monitor all-important inventory availability and has now expanded this to 12 of its stores
Lidl has used ParcelLab’s automated personalised shipping message service to engage 85% of customers receiving shopping emails to return to its website

Featuring solutions from supply chain and store innovations to personalisation, AI, data and marketing, the report looks at how retailers have benefited from adapting their businesses – and their thinking – to lean into a whole new set of disruptions, trends and challenges.

The start-ups operate across all parts of the world, from Europe and the US to Singapore and Israel, and have worked with more than 30 retailers and brands including Tesco, ASDA, M&S, Nespresso, Asos, Carrefour, Samsung, Depop, AO.com and John Lewis Partners.

Ian Shepherd has been one of the Discovery judges for the past two years. Shepherd is non-executive director at Bensons for Beds, former CEO at retailer Game, author of The Average is Always Wrong and runs the consultancy Moving Tribes where he advises retailers, digital start-ups and consumer businesses.

Shepherd commented: “This year’s Discovery cohort – just like last year’s – are going to be critical to the future of our sector. A different retail sector is possible, a million miles from the old world of ‘how many stores are you going to open?’ and ‘what was your like-for-like last quarter?’ – a retail sector that marries the instinctive customer understanding any good retailer has with the innovation and laser-like focus that new technology allows.”

Download the FREE report!

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7 ways to include WhatsApp in your Marketing Mix

Kostas Koukoravas — Fri, 16 Apr 2021 15:19:08 +0000

7 ways to include WhatsApp in Your Marketing Mix

Marketing for WhatsApp Users

Over the last few years the popularity of WhatsApp has really just grown exponentially with users worldwide using it to connect with friends and family and consume content in a more intimate space. DigitalMarketing reports that an average WhatsApp user opens the app 23-25 times every day, spending 28 minutes daily with it.

And while WhatsApp has primarily been so far a space to connect with friends, its popularity with businesses is rapidly increasing over the last few years, especially in places like India, Latin America and the Middle East. WhatsApp is investing heavily in its business proposition with Mobilesquared reporting that it is the most on demand messaging channel amongst brands and businesses looking to communicate with their customers. In fact, they estimate that WhatsApp Business will experience unprecedented growth of more than 5,400% among medium and large businesses looking to use its API.

Why? The answer is obvious. With 71% of consumers expecting to communicate with businesses in real-time, WhatsApp provides a personal and natural channel to interact with users, reducing barriers and friction, while increasing conversion. We see whatsApp as a great way to acquire and convert new customers as well as reactivate them.

With that in mind, we’ve compiled the top 7 ways to use whatsApp to grow your business.

1. Answer product queries and reserve

By offering a whatsApp number on your website you provide customers with a quick way to answer any questions that they might have, increasing your opportunity to convert that customer. Just like you would in a physical store. Your offline stock can also be surfaced on a microsite that customers can navigate through WhatsApp and reserve items. When they visit the store, they can show their reservation or QR code and store staff can find the reservation details allowing customers to quickly collect reserved items.

2. Offer an appointment reservation system

With COVID it is a requirement now in many countries that customers visit the store only after an appointment has been made. You can use AI to offer an automated appointment system through whatsApp.

3. Offer personalised recommendations to customers

Often customers have queries such as “what’s the right dress to buy for my bodytype”, “what colours will enhance my natural complexion”, “I’m going on a date tonight, what should I wear”? You can offer your customers an AI stylist that asks them the same questions that a human stylist would and offers them real time advice. The AI can choose the most suitable product for the customer’s needs or even suggest an entire outfit for them. Customers can reserve or buy the item directly from whatsApp. What’s more, customers can upload an image of a look that they would like to replicate and the AI will find the right clothes from your stock.

4. Reduce cart abandonment with whatsApp notifications and discounts

With average cart abandonment currently hovering at 70%, this is one of the biggest problems in eCommerce currently. It is a real lost revenue opportunity for businesses because those customers already have purchase intent. When you detect that your customers are about to leave the page, you can offer them to contact you via whatsApp for a special discount for items that they have in their cart. That’s where the AI takes over. Our AI negotiator will offer that customer the right discount to convert based on their past behaviour, as well as your minimum and maximum settings while making sure that the customer is offered the lowest minimum discount needed to convert.

5. Back in stock campaigns

Stock outs are another key issue in physical and eCommerce. Not only do they result in sales loss but they also hurt customer loyalty, with competitors being only a click away online. Reassure customers that they will be the first to know when an item comes back in stock by sending them a notification via WhatsApp. Not only is it a personal way to get back in touch with a customer, but customers can buy and pay directly from the message, with a frictionless user journey.

6. Loyalty campaigns for new collections

Research shows that acquiring a new customer can cost five times more than retaining an existing one. Engaging with existing customers through whatsApp is a perfect opportunity to reach a customer that you already know has a high potential to convert. Show customers that you really know them with a personalised campaign. For example, MaxMara sends customers a personal lookbook for any item they just bought in the store. That allows customers to get more value from their recent purchase, while giving them the opportunity to explore more items from the store’s collection. By knowing what customers previously purchased, you can offer them items from your new collection that match their style or even items that complement their past purchases. AI is used to effectively predict the items they are most like to purchase by analysing the attributes of their past purchases.

7. Effective Customer support

The importance of customer support these days cannot be overstated. Not only does it increase brand loyalty, but it can be a major source of new customer acquisition. 77% of happy customers are likely to share a positive brand experience. WhatsApp can play a key role in keeping customers up to date with the status of their order as well as helping them deal with problems and returns in a timely and easy to access manner. Images and rich media can be shared to identify and address issues as well as collect customer feedback, all in a channel that is more secure than email.

Intelistyle’s extensive whatsApp suite of services, coupled with its fashion AI platform have created the ultimate experience for fashion retailers on whatApp. We’ve already seen huge demand for the solution with a number of retailers moving fast to capitalise on the growth of whatsApp business as a customer engagement channel. Customers, such as MaxMara, Tory Burch, Swarovski and Fossi, that were diligent enough to move fast and launch a WhatsApp solution for their business already enjoy 15% revenue uplift.

If you’d like to find out more, get in touch for a free consultation to create a solution tailored to your needs.

Book a free consultation

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How to differentiate and increase conversion with AI styling advice

Kostas Koukoravas — Tue, 30 Mar 2021 15:07:52 +0000

How to differentiate and increase conversion with AI styling advice

How to deliver a curated customer experience at scale using AI

Imagine you are visiting a store to buy a new dress. The sales associate comes and asks if you’d like some help. Immediately you assume that they are trying to sell you anything they can from the store. You reluctantly start chatting to them only to find out that they are really knowledgeable. Not only do they know the stock that the store has very well, they also understand what makes each piece special and what attributes it has. They are a qualified stylist and they know how these attributes complement different bodytype and skin tones. You soon realise that you can trust their advice because they recommend clothes that actually look good on you. Not only that but they’re aware of all the latest trends while listening to you and respecting your personal sense of taste. After all, you don’t always follow the latest trends, but you are selective about what you like and what looks good on you.

Product Discovery through AI styling advice

Meet Intelistyle’s AI Styling Advisor. Our AI constantly crawls the web for the latest fashion and trends and learns from them, extracting the essence of style. Our Style and AI expert teams then calibrate it to the styling identity of your brand and your stock. Fine grained styling rules allow you to be in full control of your styling guidelines and direction. Your stock is then analysed for all possible attributes relating to cut, material, fabric, style, occasions, colour and various other fashion attributes.

Our AI analyses more than 400 different fashion categories, subcategories and attributes to assign the right tags to every SKU in your inventory. The fashion taxonomy that is used is a comprehensive list of attributes and tags developed alongside merchandising teams and fashion retailers. It currently forms the industry gold standard for labelling clothing and accessories, covering the needs of merchandising teams worldwide, while being concise enough for it to be searchable by customers. It constantly gets updated with the latest trends on social media so that your data is always tagged with the words that your customers currently use to describe their clothing and needs.

We use that taxonomy to provide customers with varied styling advice on each and every one of your product pages. The advice is so vivid and clear that it feels like you are talking to a knowledgeable sales associate. See for example the screenshot below.

In this scenario, the user is informed that embellishments add depth and volume to an outfit and that they can be used to draw attention to a part of the body and how. It also provides alternative ideas for how to use embellished pieces.

In the case of the knit cardigan shown above, the flexibility of a classic top with long sleeves is highlighted and a couple of options are given for wearing it at different temperatures.

The example below highlights the prime benefit of using vertical stripes and provides a few options for how to style them.

Personalised styling advice

We don’t stop there though. We learn more about customers by asking them about their bodytype, skintone and hair tone. By going through a guided discovery process, that mirrors the conversation they would have with a stylist, we find out more about them. We provide a free styling consultation for them, telling them about the clothes that work best for them. They can save that information on their email or whatsApp for future reference.

We then use that information to customise the styling advice that we give to them. Customers will see how a particular piece of clothing compliments their bodytype or skintone. All advice gets personalised to them.

How to increase conversion on product pages

As a result, retailers enjoy improved conversion rates. In February 2020 one of the biggest fast fashion retailers in Europe introduced this feature on their website. They then run a campaign to promote the feature both through targeted display ads on instagram and facebook as well as a newsletter campaign. Customers were then split into two groups depending on whether they were exposed to the advertising of the new feature or not. Those that didn’t see any advertising with regards to the feature, didn’t see the styling advice. The results were impressive. Customers that saw the styling advice had a conversion rate of 130% higher than those that didn’t. The feature was priced in such a way that when comparing additional gross profit to the cost of the service, the retailer got 15x ROI. It is now being rolled out across native iOS and Android apps.

What else can I do to create a personalised discovery experience?

This is just one of the features you can use to differentiate your discovery experience online and help your eCommerce website or app stand out. For example, when customers are shopping for fashion they use two different modes. They are either looking for similar items or they’re looking to style something that they already have or are considering buying. You can help customers meet those needs with Visually Similar items or complete the look recommendations. Visual search is another great example of functionality that can help your customers find the product that they are looking for by uploading an image of the look they are trying to achieve.

If you’d like to differentiate your user experience and increase the conversion rate of your eCommerce Website or apps, book a free demo with one of our conversion optimization consultants and get a price quote as well as a calculation of what Revenue increase and ROI you should expect.

Book a free consultation

The post How to differentiate and increase conversion with AI styling advice appeared first on Intelistyle.

Product Discovery Reimagined: Style Customers with Outfits That Fit

Kostas Koukoravas — Thu, 18 Feb 2021 10:45:58 +0000

Product Discovery Reimagined: Style Customers with Outfits That Fit

Intelistyle partnered with Easysize to elevate fashion eCommerce experiences to the same quality service you’d expect in a physical store. We decided to bring together Intelistyle’s AI-powered styling solution with Easysize’s size and fit recommendation platform to create a discovery experience, that allows shoppers to find the right products for them regardless of their bodytype or style. Because buying the right item in fashion means that it’s both the perfect fit and style for us.

Why did we decide to partner with a solution like Easysize? Because we think that their pragmatic approach to solving the sizing problem is easy to integrate, low cost and can be made readily available to fashion retailers of different sizes and categories.

The goal was, on the one hand, to help shoppers find the right products, while on the other hand increase conversion, basket size and reduce returns, which is one of the key problems that merchants currently face.

Read on to find out more about what problems we’re solving and how.

Why should I care about fit and style on my eCommerce website

With the pandemic accelerating the shift to e-commerce by 5 years and increasing customer spending in online channels, improving the customer experience in eCommerce has become an urgent priority for fashion retailers.

Product discovery in the physical world has stark differences from that of online. Customers can walk around the store and pick up the items they need one by one to create a stylish outfit. They can walk into the fitting room and see how the outfit will look on them, but also assess the fit of those items and whether they have the right size.

“ Visiting a product page is the offline world equivalent of a customer picking up an item ”

– Kostas Koukoravas, Co-founder & CEO, Intelistyle

This allows customers to answer the three most important questions they have once they pick up a piece of clothing from the rack – the offline world equivalent of visiting a product page:

Will I look and feel great in this?
Is this the right size for me?
How do I style this?

Online product discovery is very different, offering significantly fewer quality opportunities for evaluating an item and more opportunities for clicking away to a competitor’s website.

Even today, most eCommerce websites remind us of the good old days of catalogue shopping. There is a listing page with products that we can endlessly scroll through. That leads to a more detailed product page, which is pretty much standard across the industry.

The Cost Of Returns in Fashion & How to solve it

The quality of photography has seen significant improvements over the last years, with customers being able to see how clothes look on a model as opposed to still life shots. However, not everyone has the same body. We’re all different and customers know that all too well when shopping online.

The percentage of online returns has hit 50% of all orders in some cases, as Zalando reports, and is typically at the 30% mark across the industry. Customers buy more than one size to see which one fits. They also chose a selection of products, only some of which they intend to purchase, so that they can assess at home which one is right for them. Just like they would do in a fitting room,

And while offering free returns has been key to the growth of eCommerce and forms part of the core business model of eCommerce giants, it has significantly impacted merchant margins with returns increasing sale price by 20%.

By helping your customers find the right size before they purchase you are achieving two key goals in the customer’s buying journey. First and foremost you build confidence that they have chosen a product that is right for them, more than doubling your conversion. On the other hand, by helping them find the right size in advance, you help them achieve the same goal they would in a real-world fitting room. That means fewer purchases of multiple sizes, reducing the cost of returns and its impact on your operations and margins.

Shoppers are asked a few simple questions about their size in other brands and the typical fit that works for them. Shopping and returns behaviour of individual users, as well as unique product features, style and fit preferences and fashion choices, are analysed. They are then used to predict and recommend the best possible size and fit for a shopper.

Easysize uses a vast database of fashion and shopping fit preferences of more than 17 million shoppers across womenswear, menswear, streetwear, luxury and fast fashion all the way from evening gowns to modest fashion. Its algorithms understand the complexities of fit and size to make recommendations as accurate as possible. For example, a customer might like slim-fitted shirts in one brand but oversized in another. To achieve that, the technology doesn’t use inaccurate or subjective data such as garment or body measurements. Instead, it analyses shoppers preferences and finds others with similar preferences, creating fashion doubles, accurately predicting what they’re likely to enjoy.

In the scenario where the right size is out of stock, Intelistyle’s technology kicks in, analysing the style, pattern, colour, cut and fabric of the item to show customers visually similar products that are in stock and can be instantly purchased, ensuring that the customer converts.

The lost basket size opportunity

To add to that, it’s difficult to visualise how different pieces of clothing can be combined to form a fashionable outfit. Most retailers rely on antiquated recommendation engines that work across industry verticals. And while “you may also like” does wonders for electronics it doesn’t really work for fashion. While you might also like products that other shoppers with similar preferences purchased, that doesn’t mean those products are actually similar nor that they can be combined to form a fashionable outfit.

In order to understand that better, it’s worth looking at how people shop for fashion. That happens primarily in two ways. When they are out shopping for a t-shirt, for example, they will be looking at similar t-shirts to find the exact right t-shirt for them.

Once they find that, they start thinking about how they can style it and what other products they need to form a fashionable outfit.

For example, Tryano found that by replacing their industry-agnostic leading recommendation engine with a fashion specific solution, they were able to deliver 130% more revenue.

Intelistyle uses two modules to solve this problem. Our eCommerce recommendations platform allows shoppers to see Visually Similar recommendations, by analysing cut, style, product features, colour, fabric and more. It then shows products that are visually similar to what the shopper was looking for.

Our wear it with module, shows shoppers entire stylish outfits that they can put together to complete the look. Our A.I. is trained on millions of data points that constantly evolve to examine the latest trends. It then gets calibrated to your brand’s styling identity by our team of experts and monitors the shoppers’ behaviour to offer outfits that are on brand and just right for the customer’s style.

But we don’t stop there. We also examine each piece of clothing to understand its attributes and then show customers styling advice for it. So that it really feels they’ve just walked into a store with a knowledgeable sales assistant.

How to increase basket size while reducing returns

Increasing basket size while reducing returns sounds like two exact opposites right? After all, we know that often customers buy multiple items with the intention of keeping just one. That’s why Intelistyle and Easysize teamed up.

By enabling Intelistyle’s Complete The Look and Visual Similarity recommendations on your product pages, you align your user experience with the way shoppers buy for fashion. Tommy Hilfiger saw 20% of their product discovery experiences powered by those two modules. This is an astounding number. 1 in 5 customers actually used these recommendations to find the right products for them, resulting in a 5% revenue uplift for the entire brand. With a 2 minute integration (video) and 19X return on investment, that was 2 minutes well spent. Lane Crawford saw an 8% revenue increase by tempting shoppers with visually similar products and outfits tailored to their brand identity. Conversion soared by an impressive 124%, while full-price sell-through rate increased by 20%, highlighting that shoppers got inspired to buy the right product for them, as opposed to looking for the cheapest product.

Veepee, a company that pioneered the model of online flash sales with €3.3bn in revenue, decided to use Easysize to decrease the number of size-related returns and boost user confidence by providing the right size. Easysize size recommendation was used in 22% of all purchases. By auto-recommending the size to shoppers, Veepee was able to lower its return rate by 14%. In addition, the sales conversion (from a page view), when the recommended size was shown, increased by 35%.

Brands such as Freshcotton, Ash & Erie and Superette managed to increase their conversion rates by 139%-187%, while Modomoto decreased size-related returns by 29%.

The partnership

Intelistyle and Easysize teamed up to help your shoppers answer all the questions they have when they visit your product page. That incredible feeling of picking up a product in the real world. By helping them find the right size as well as by providing them with styling advice for every product in your catalogue, customers can be confident they have found the right piece for them, increasing conversion and basket size, while decreasing returns.

Based on the data we’re already seeing, this new solution, first of its kind in the market, is a practical approach to drive instant and measurable results, while helping retailers differentiate with a customer experience that meets fashion shoppers’ unique needs.

If you’d like to find out more about how you can use this full suite of product discovery experiences to differentiate your eCommerce offering, reduce returns and increase conversion and basket size, get in touch for a free 30-minute consultation session. One of our user experience experts will deep dive into your unique challenges and metrics and create a tailored plan for growing them with a measurable return on investment.

Book a free consultation

The post Product Discovery Reimagined: Style Customers with Outfits That Fit appeared first on Intelistyle.

Kostas Koukoravas, Author at Intelistyle

Ecommerce Recommendations – 68 Examples For Your Store

Ecommerce Recommendations - 68 Examples for Your Store

Homepage

Popular products/Best-sellers/Trending

eCommerce Recommendations In the media

Trending brands

Trending categories

eCommerce Recommendations for New arrivals

Coming soon

Editor’s pick

One of a kind

Previously viewed

Daily deals

Personalised recommendations

Suggested searches

Search page

Best match

Top-rated eCommerce Recommendations

Curated collections

Visual search

Category page

Popular products

Top-rated products

Recently viewed

Product page eCommerce Recommendations

Visually similar

Recently viewed

What other customers are doing now

More from this brand/shop/designer

Customers who searched for/bought x also viewed/bought

Complete the look

Shop the look

Personalised recommendations

Frequently bought together

New items

Checkout/cart page eCommerce Recommendations

Don’t forget

Recommended products

Buy it again

Popular products

Frequently bought together

404 page eCommerce Recommendations

Recommended products

Best-sellers

Pop-ups

Trending items

Other items you may like

Recommended products

Retargeting campaigns

New arrivals

Popular products

Back in stock

Outfit recommendations

How to style it Recommendations

New Item Email Recommendations

Get Started with Ecommerce Recommendations Today

Intelistyle awarded best AI Product in Fashion at CogX 2021

Intelistyle awarded best AI Product in Fashion at CogX 2021

Best Practices For Product Attributes

Best Practices For Product Attributes

1. Understand Which Product Attributes Are Important to Your Customer

2. Optimise Content for Search Engines (SEO)

3. Automate Product Tagging

4. Invest In a High-Quality Attribute Tagging Product

Fashion-specific data set

Visual recognition and multi-product detection

Attribute groups

Optional control

Final Thoughts

What Are Product Attributes And Why Do They Matter for Fashion Brands

What Are Product Attributes And Why Do They Matter For Fashion Brands

What Are Product Attributes?

Why Do Product Attributes Matter?

Improved product discovery

Persuasive product pages

Increased personalisation

Predictive and stock performance analysis

Final Thoughts

Fashion Personalisation: Top 12 Examples