5 Amazing Ways to Harness AI in your Fashion & Apparel eCommerce Platform

In a world where technology is evolving rapidly, many B2C and B2B businesses are trying to adopt AI in the fashion industry (if they haven’t already). The major driving factors for this are that AI and automation essentially help businesses achieve increased efficiency and profitability.  

With AI, B2B apparel companies can streamline different processes ranging from designing, manufacturing, and supply chain, to marketing and sales. Adopting an AI-based eCommerce platform can help automate most of these processes with minimal effort. 

Let’s understand how can you make the most of an AI-powered eCommerce platform to stay relevant in the ever-changing world of the fashion industry.

Personalize with AI to understand your customer 

This is the age of digital shopping. 

Customers want to find things fast and the expectations are high. And it doesn’t matter if you are in the B2C or B2B fashion industry, your customers are people, and people make emotion-driven decisions.

A survey by Google and CEB of 3,000 buyers from 36 B2B brands found B2B customers were ‘significantly more emotionally connected to their vendors’ than consumers were to the brands they purchased.

If your customer visits your website and doesn’t connect with it immediately, chances are you are most likely to lose that customer forever.

88% of customers say the experience a company provides is as important as itsproduct or services – up from 80% in 2020.

– Salesforce

Similarly, if your customer loyalty system fails to recognize VIP customers in your database, you might end up giving them generic or irrelevant offers, and risk losing them. Remember that your customers have tons of options online. So if they’re being loyal to you, then you have to show them your gratitude for it. 

Personalization can be implemented for every aspect of the store, the most common being:

• Home page personalization
• Product recommendation
• Personalized search functionality
• Product page personalization
• Personalized account management
• Personalized, real-time inventory availability
• Personalized payment
• Tailored content

To avoid disappointing your online shoppers, you can leverage automation to offer them highly personalized customer experiences.

When you use AI, you can provide each customer with a unique shopping experience based on their individual preferences. Personalization not only boosts customer satisfaction and revenue but also increases your chances of getting more details from your customers. 

According to SmarterHQ, 90% of consumers are willing to share personal behavioral data with companies for a cheaper and easier experience.

Encourage curiosity with AI in fashion apparel product recommendations  

As buyers spend more time shopping online, AI in fashion technology has found new and innovative ways to help eCommerce businesses engage and retain their customers. And using an AI product recommendation engine is the best way to do that.

Let your customers find more of what they like through fashion product recommendations, and you can reap 3 incredible benefits through it!

Have a look:

• AI-based product recommendations can influence shopping behaviors and improve product discovery. In fact, 49% of consumers say that, after receiving a personalized recommendation, they have purchased a product that they did not initially intend to buy. 

• You can capture user data to understand user experience and how your customers interact with your eCommerce website. This helps apparel companies improve the personalization factor in their stores and stand out from the competition. 

• Product recommendation also helps your sales reps make stronger pitches based on all the data gathered. This is especially true for B2B clothing manufacturers and other B2B apparel companies that are just starting out.

Also Read: 7 tested touchpoints where you can boost eCommerce sales with personalized product recommendations

3 Types of product recommendation engines you can use in AI in fashion and apparel eCommerce

The most commonly used product recommendation engines in eCommerce websites are 

• Content-based filtering is when you use text, keywords, and attributes assigned to items in a database to map existing user profiles 
• Collaborative filtering is when you use lookalike audiences that have similar preferences. This model can also help users discover new interests.
• Hybrid filtering combines the two models to give more accurate and personalized product recommendations.

Let’s understand this with an example.

Netflix uses the hybrid filtering recommendation model, as it takes the best of both worlds. The platform gathers data from audiences who may be similar to you in some way and checks what their likes and dislikes are. A lookalike audience may be of the same age group as you or are living near your locality or both. This is how the collaborative filtering model works. 

Now, think of all the movies you’ve watched! You may have liked or disliked specific movies or genres, began watching something but quit midway, searched for specific movies in the search navigation bar, or looked for movies or series to binge under selected category lists. 

All of this data represents what you’ve personally liked (or hated), and maps it to Netflix’s existing database of movies that may have the same attributes as the movies that you’ve liked in the past. This is how the content filtering model works. 

Now, Netflix takes this data and maps it with the data from the collaborative filtering system to give you the best and most personalized movie recommendations. And this is how the hybrid filtering model works.

Choosing the best product recommendation engine for your apparel business 

AI technology can offer numerous benefits for businesses selling clothes, accessories, and other apparel items online. To get the best product recommendation engine in 2022, you need to do your research to find one that is future-ready. 

An AI-powered eCommerce apparel platform can be very helpful to your business as it is designed to be flexible, customizable, and scalable. With it, you can always tweak and add new elements to your existing store to meet the changing market requirements of the fashion industry. 

This is why investing in a B2B eCommerce platform would make more economic sense than having a traditional eCommerce website for your fashion and apparel business. 

There are many product recommendation engines in 2022 to choose from which you can easily integrate with your fashion and apparel eCommerce platform.

Automate your marketing to improve customer retention

If you have a fashion eCommerce platform or a website, you might already know how important customer retention really is. You must remind your customers to miss you before they forget you exist. 

After all, the cost of acquiring a new customer is 7x higher than customer retention. The probability of selling to an existing customer is about 60-70% whereas selling to a new customer is only 5-20%.  

But how do you actively retain your customers without spending too much of your valuable time and company resources on it?  You can achieve this by using automated marketing to grow your eCommerce business economically. 

The need for marketing automation and AI in fashion and apparel eCommerce

A thing to expect about owning a mobile shopping app or website is that you will have customers visiting your store –all day and all night. While this is obviously an added advantage over a physical store (that’d close after a certain hour), you still need to engage your online visitors. 

It is obvious that you can’t manually track every visitor and reach out to them immediately –unless you have a lot of time and money to invest in hiring a large team of marketers to work around the clock. And even then, it could be such a mess!

That’s where marketing automation comes to play. 

“AI helps to better understand your current customers and focus the majority of your marketing strategy on retention, not acquisition. AI-based systems are able to continually adapt to the likes and dislikes of your customer and react with recommendations in real-time. 

With a deeper understanding of customers, AI can be used to suggest personalized offers that will resonate with the targeted individuals.”

– Ouriel Lemmel, CEO and founder of Winit.

4 ways to automate marketing using AI in fashion and apparel

Using an email marketing automation tool to retain customers

Email marketing is one of those rare gems that has stood the test of time. It is also one of the most cost-effective ways to grow, nurture and retain customers. 

The average email ROI (return-on-investment) is $42 for every $1 you spend on it.

— DMA

With the right email marketing automation tool, you can capture the attention of your customers using an easy-to-use dashboard that will let you create, manage and view analytical reports of your email campaigns — all in one place. 

Ever wondered why you receive emails with subject lines like:

“Hey, we miss you.”

“Haven’t seen you in a while.” or

“There are items waiting in your cart, hurry!”

These are automated behavioral trigger emails that are sent to customers who show a certain behavior type or pattern.

At any point in the customer lifecycle, an online B2B and B2C clothing brand would need to fire a “triggered email” that is auto-sent to a list of segmented email audiences. 

• Cross and upsell campaigns 
• Dynamic product retargeting emails on abandoned carts and wish lists
• Price drop emails
• Incentivize with referral programs and giveaways 
• Back-in-stock emails
• Re-engagement emails for inactive users
• Survey/feedback and product review emails
• Order receipt and track your order emails

Automated emails grow open rates by 86%, click-through rates by 196%, and generate 320% more revenue than standard emails

— CampaignMonitor

Ewiz commerce offers users ready-to-use email templates that are also easily customizable using a drag-and-drop email builder, called the MarComm creator. 

Another feature that has proved to be extremely useful to B2B fashion and apparel businesses in the past is the use of AI-powered catalog creators that lets users design personalized catalogs within minutes!

Also Read: 11 Embarrassing B2B Email Marketing Mistakes You Need to Avoid

Automate your omnichannel marketing efforts

Rather than using a single-channel marketing approach like using only your online apparel store to drive revenue, you can use more than one channel to sell your products. This way, you can leverage the reach offered by multiple channels. This is called a multichannel marketing approach. 

The problem with this method however is that you’d be using separated, disconnected marketing strategies to target the same person across multiple channels. The end user is most likely to be bombarded with meaningless ads across different channels, which could be quite frustrating.

Now, when you have different channels communicating with each other with unified branding across all channels, you have a cross-channel marketing platform. 

Take, for example, your customer likes your product on your Instagram channel, you can show them a Facebook ad for the same product and then send them an offer via email. This way you can line up all the channels with a unified customer experience across all these channels. 

With omnichannel marketing, you take it one step further where all the channels not only do communicate with each other but the data from all sources is shared across all the other channels and can be used to provide a seamless customer journey from anywhere and at any time.

For example, if you buy a pair of sunglasses off a Google ad online but wish to return the product at your nearest physical retail store, you’d be able to do so. The customer service executive would easily be able to retrieve your data and process your return request immediately. 

You may then also receive a feedback email asking you to rate your customer service experience at that offline retail store. Your feedback would then be sent back to all these channels and to various teams within that company like the business intelligence, sales, marketing, and also the customer service teams. 

You may then receive a personalized offer for similar types of sunglasses, except this time, the features of the new glasses would be better than the one you had returned because your feedback was taken into consideration. So now there’s a higher chance that you’d keep it. You as a customer would be impressed to learn how your feedback was acknowledged through their value-based marketing. 

Ideally, an omnichannel approach is what you should be aiming for in order to provide your customers with a seamless user experience. It also lets eCommerce businesses use data collected at every touchpoint further to improve the next stages of customers’ buying journey. 

Leverage trend forecasting and dynamic pricing to keep the hype going

Fast fashion trends come and go out of style at an alarming rate. Decision makers have to manage the demands of digital, sustainability, and the supply chain, but often fail to do so.

Zara offers 24 new clothing collections each year; H&M offers 12 to 16 and refreshes them weekly.

– Mckinsey

Shein – known as an ‘ultra-fast fashion’ manufacturer in China – regularly introduces more than 6,000 new products per day. 

– BBC News

It is very difficult for clothing manufacturers and eCommerce companies to keep up with these fast-pacing fashion trends. 

When the consumer demand for a product increases, eCommerce stores have to stock up fast! 

And when a new trend replaces the older one, companies have to bear a huge loss on the dead stock and are forced to discard their stock in huge numbers. Recycling is a challenge.

This has a damaging effect on the environment, making the fashion industry the second-largest polluter in the world after the oil industry. 

And then the cycle repeats itself.

AI in fashion trend forecasting 

With artificial intelligence, fashion and apparel brands can predict and forecast trends using a trend forecasting platform. Trend forecasting can also help educate B2B fashion buyers with useful information that can help them plan ahead and stay up-to-date with fast fashion trends. 

Today, social media plays a significant role in trend-setting. Many fashion bloggers, influencers, celebrities, and trending movies have huge fan bases that try to keep up with new trends. Apart from this the fashion industry also follows fashion lines that present new collections at runway shows and fashion trade shows. 

Apparel brands and clothing manufacturers can keep up with these fast-moving fashion trends using trend-predicting AI and machine learning algorithms. They gather data from multiple online channels and offline channels and map them to different user groups. Large databases are segmented into different audience groups based on specific attributes like their age, demographics, income, online consumption patterns, lifestyle choices, etc.

Traditionally in the fashion eCommerce industry, pricing strategy is based on an initial fixed price, followed by a series of aggressive discounts as the season unfolds. These trends are analyzed by using past sales analysis to understand trends that are to stay for longer. 

Fashion trend forecasting platforms use early-stage signals to predict upcoming fashion fads. It uses image recognition technology to analyze the large database of fashion images on social media and other channels. 

To get more accurate predictions, trend predicting algorithms analyze trends in real-time and track changes in buying patterns and behaviors between seasons to help decision makers predict trends leading to more sustainable and economical business decisions.

Dynamic pricing using AI in fashion and apparel eCommerce

In North America and Europe, 17% of eCommerce companies planned on starting to use dynamic pricing in 2021, a survey revealed.

Additionally, 21% of the eCommerce businesses surveyed were already using dynamic pricing, and 32% did not have plans to adopt this strategy in the upcoming year.

– Statista

Whether you’re a B2B apparel brand owner, clothing manufacturer, or vendor, you know that price always matters to the customer. Undoubtedly, the same goes for B2C apparel buyers as well. Given that two companies offer the same products, the online shopper is going to look for items with the lowest price tags. 

This is where large retailer brands earn the highest profits through fast fashion. They lower the prices of fashion apparel, footwear, and accessories to a very affordable price. The only way they can make huge profits by selling cheap is to sell a lot of it all at once.  

On the other hand, if there’s a perceived scarcity for highly trending ‘premium’ products that are only available for a limited time, companies can then shoot up the prices, knowing very well that people will still buy them. 

Let’s look at this with an example by understanding how the world’s best eCommerce brand, having the highest reach, approaches pricing.

Amazon will account for nearly 40% of the U.S. eCommerce market in 2022. It is most popular for its competitive pricing, fast shipping, and great customer service. 

Amazon has a large base of loyal customers. By tapping into this database, B2B sellers can make huge profits. Apart from offering a global reach of customers, the eCommerce giant also provides additional support on logistics, warehouses, fulfillment, and customer services.

Our success depends on the success of our selling partners. Amazon’s work with third-party sellers is one of the greatest partnership stories in retail. Together, we make a great team.

–Dave Clark, CEO, Amazon Worldwide Consumer

U.S. Seller Performance (September 1, 2020 – August 31, 2021)

• There are more than 500,000 sellers in the U.S.
• US third-party sellers sold more than 3.8 billion products (about 7,400 products per minute). 
• 11,500 products per minute were sold by 3rd party US sellers between Black Friday and Christmas of 2021.
• Nearly 4,000 American sellers surpassed $1 million in sales for the first time
• The number of American sellers that surpassed $10 million in sales increased by nearly 40%
• On average, sellers see a 20—25% increase in sales after adopting Fulfillment by Amazon (FBA).

• Amazon

Amazon automatically reprices products by tracking by the slightest changes in the market, using artificial intelligence. While best-selling and popular product costs on Amazon are low, it increases its price for uncommon products. It also closely monitors prices against its competitors and updates its own prices accordingly. 

The real-time pricing compares data across customer activity, availability of a product, users’ order history, and more. Some platforms also increase the prices of products by tracking how long the user spends viewing the product on its website. 

In an online hotel, flight, or ride-hailing booking platform, you’ll see a sudden surge in price based on the demand, date, and time.

Create professional-looking fashion catalogs using automated AI image editors 

There’s nothing that artificial intelligence can’t do today. And so, fashion retailers don’t need to manually edit single images anymore. 

You can now use AI in fashion and apparel stores to automate bulk editing for appealing product images. 

The best part? You can edit almost 5000 images in one go and this process only takes a few minutes! 

3 Best AI photo editor software for apparel brands  

Vue.ai 

Vue.ai’s on-model imagery tool lets you ditch expensive photoshoots and use artificial intelligence to create high-quality on-model product photos at scale. It allows you to visualize and style fashion products on models for product pages.

Luminar AI

Luminar AI is a hands-on AI-powered image catalog and photo editor. The software analyses your photos and suggests templates.

All you need to do is choose a template and apply it to your catalogs. You can then fine-tune the images for more customization. It also lets you create a single style for your images and apply it to the whole series of your photos.

It also offers 20 unique photo effects and editing features like the 3D depth map to enhance 2D images and also add weather elements like fog, mist, snow, etc. Its composition AI features uses smart analysis and provides editing suggestions. 

You can use the Body AI feature to edit the body proportions of models in your catalog. Similarly, you can use Face AI to optimize facial features. Skin AI allows you to remove skin blemishes and skin imperfections and preserves the texture of the skin, and facial hair to keep it realistic. You can also use atmosphere AI to add interesting hues to the sky. 

Luminar AI is available as standalone software and as Photoshop or Lightroom plug-ins.

Imagen AI 

Imagen AI only integrates with Adobe Lightroom. With this software, you can edit images of a whole catalog consisting of 5000 images in a few minutes. 

You can choose to train the photo editing AI once and set it up with how your unique editing style. It will then process your entire catalog within minutes. 

Another option is to choose from editing styles listed by different photographers on the software. The software will then replicate the edits you chose and applies them to all of your images. You can then edit and customize the editing style and apply it to your whole catalog at once. 

You can use these newly edited images and add them to your marketing automation software to run different marketing campaigns. 

Not only that, but with an AI-powered eCommerce platform for your apparel business (like ewiz commerce), you easily tie up different software and automate your entire marketing process. 

While these AI product image editors might sound awesome, we have something that’ll blow your mind!

Text to Image AI models – Picture something in your mind, and AI will create it! 

AI technology has moved on to yet another level. You can use textual descriptions to convert them into high-quality images! 

1 DALL ·E 2

In January 2021, OpenAI introduced DALL ·E. 

One year later, DALL ·E 2, generates more realistic and accurate images with 4x greater resolution. It also self-learns and can take an image and create different variations inspired by the original. 

Take a look at what it can do!

2 Google’s Imagen AI

Imagen is “a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding.”

Basically, it can create images from input text.

About a month after OpenAI announced DALL-E 2, Google announced Imagen. And Imagen clearly outperforms DALL-E 2!

Take a look at what Imagen can do!

It is evident that we’re already in the future. And with the hope that soon these AI systems would be available for commercial use, the applications are limitless!

Make product discovery a cakewalk with AI 

For eCommerce, product discovery is a major obstacle. As customers have more choices, they are often left with the difficult task of finding what to buy. There are many ways to improve product discovery on your website.

One way is to use automation for apparel and fashion eCommerce. This will make it easy for customers to find products on your website quickly. It can also help them find the right size and fit by understanding their preferences and previous purchases. 

AI automated product tagging using visual AI

Better product descriptions and accurate tagging mean your customers can find what they’re looking for easily. Up to 30% of eCommerce visitors use internal site search, and shoppers using site search are 3x more likely to convert.

If someone actively looks for products on your eCommerce website, you can’t afford to lose them. And yet, 

61% of all sites perform below an acceptable search performance that is misaligned with the user’s actual search behavior and expectations (and 15% have a “broken” search query type performance).

Why do you need it? 

Internal site search, product recommendations, search filters, etc. will not work correctly if you’ve tagged a product incorrectly. If you set your foundations right, you can pretty much automate anything in your online apparel store. But if you do it wrong, automation cannot with function properly. 

While it’s quite easy to use AI copywriting tools like Rytr, Jasper, or Copy AI to generate relevant product descriptions using specific keywords, automating product tagging is a more complex process. 

The problem with manual tagging and semantic search

AI in fashion and apparel brands can improve their product discovery process by automating the process of tagging eCommerce products. Manually tagging each and every product in medium to large retail enterprises can be tedious, time-consuming, and prone to manual errors.  

To improve internal site search recommendations in online apparel stores, companies used semantic or text-based search, which leverages the power of Natural Language Processing. But the problem here is that sometimes people use synonyms or related keywords that don’t provide the most accurate results because the products aren’t tagged with those exact keywords.

That’s why most retailers and B2B apparel brands have started embracing Visual AI software to improve product discovery. 

Smart tagging using Visual AI

Visual AI can be used to automatically convert product images in the product catalog into tags, titles, and descriptions based on their attributes. This software recognizes what type of clothing or accessory each image contains and uses that information to generate relevant tags.

Visual AI tools like AutoScribe, pixyle.ai, ViSenze, Okkular, and vue.ai use computer vision and deep learning to improve the automation of product tagging and cataloging. It operates by scanning an image and detecting attributes that are linked to specific keywords (and their synonyms). These tools also offer retail customers with an option to look for ‘similar products’ based on their searches.

Each tag can have categories, attributes, and values assigned to them. Product Attributes are data points about your products, like size, color, price, fabric, necklines, sleeve type, etc. If there’s an incorrect tag, its value can be changed. 

All you need to do is upload your images onto the software, and it will generate tags. You can then choose to review them and make changes if you like. In case the software fails to identify certain products clearly, it will flag them and let you know. This helps retailers know when the images need to be updated or are unclear, and reduces the chances of tagging products wrongly.

Easily integrated with your eCommerce ecosystem

Some tools go beyond product tagging to give you a holistic solution to improve product discovery and user experience on your online eCommerce store. Apart from Visual AI, these tools also offer 

• Visual image search, where customers can upload an image to search for products
• Smart recommendations like ‘Shop the look’, ‘Complete the look’, and ‘Similar products’
• Category page personalization to eliminate endless scrolling with personalized sorting
• Collect meaningful user insights about how your customers interact with your products 

You get access to and track all the changes made and data collected on a dashboard that can be easily integrated into your apparel eCommerce platform, product information management system, and digital asset management platforms. 

Offer a humanized shopping experience with Conversation AI in Fashion and apparel eCommerce

Automated chatbots can instantly browse through customer order history and extract information related to it within seconds. They can also collect customer feedback and help businesses understand the pain points of their customers and better their services. 

Apart from basic customer support, you can use conversational AI chatbots to up your eCommerce game to the next level. Not only can they be easily  integrated into your eCommerce platform, but can also be used to

• Help customers find products
• Offer product recommendations
• Place orders
• Track orders 
• Analyze customer behaviors
• Act as in-store managers

Virtual Assistants however are revolutionizing apparel and retail eCommerce by offering customers

• Voice, text, and visual search for products they wish to buy online
• Personalized shopping experience and improved engagement
• Offers, discounts, promotions, up-selling and cross-selling
• Omnichannel assistance across multiple platforms 
• Personalized product recommendations 
• Assistance in multiple languages
• Instant lookup for product information, order updates, and website assistance
• Reminding visitors of an abandoned shopping cart, and more
• Presentation of products with augmented reality

People want, above all, more detailed and visual product information (37%), better search (29%), and easier access to a customer service representative via live help options such as click-to-call or live chat (20%).

– Oracle

Also Read: 11 powerful ways AI Chatbots can transform your eCommerce business

‘Bring that extra zing’ with an Augmented Reality (AR) Shopping App

What’s the most common reason behind most returns? 

Fitting issues, fabric issues, and color issues. 

Returns are usually trashed by retailers due to the costs of reshipping. Augmented reality shopping apps help customers make better choices and avoid returns. It allows customers to try on products and see how they look in real life, without having to go to the store. 

And so, AR apps are convenient for both the customers who get exactly what they paid for, and for retailers who don’t have to worry about unsold inventory. 

Sounds interesting right? But how do you get your own AR shopping app? 

The answer is very simple. I kid you not!

Augment lets you easily deploy augmented reality apps for their businesses. Shoppers can try on clothes and fashion accessories at home or view them in 3D directly from the mobile shopping apps or eCommerce websites of retailers. The 3D viewer can be installed on your app or site in less than an hour!

You can also upload a list of products you need with the required information and launch your production instantly.

Augmented Reality, as an emerging technology, has a lot of potential in the fashion and retail sector. AR m-commerce apps provide users with an incredible new way to experience the world, making shopping easier, and more engaging. 

Using a ready-to-use AR app would be much more efficient than building one from scratch. If you’re a startup or small business, AR can help you gain more visibility and build trust with your audience. 

Are you ready to harness the power of AI in Fashion?

Be future-ready with AI-powered eCommerce. Scale your apparel business to greater heights. 

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