Shopify has over a million merchants on its platform and around 25% of them fall within the fashion industry. It’s one of the most popular industries and one of the most competitive ones. While setting a fashion store on Shopify can be easy and straightforward, finding the right apps for your store can prove a challenging and daunting experience. To help you out with this process we’ve compiled the top 15 Shopify apps for fashion stores.

1. UpPromote

The power of affiliate marketing is to use affiliate’s voices for reaching a wider customer and increasing revenue. And UpPromote: Affiliate Marketing is one of the best Shopify apps to support you build, track and succeed with affiliate marketing.

No technical knowledge is required, UpPromote is friendly even if you are a newbie. With this app, each affiliate will have an auto-generated affiliate link which leads directly to your store. In addition, if you want to assign coupons for members, the app can do that automatically. The app allows you to track all referral orders and your affiliate’s performance via multiple tracking methods.

The highlight of UpPromote is UpPromote marketplace in which you can approach more qualified ambassadors. The more affiliates join your program, the more customers know your brand. Besides, you can expand your affiliate team through Converting customers to affiliates feature, or Multi-level Marketing feature. Therefore, UpPromote is a great supporter for you to succeed with affiliate marketing.

2. Omnisend

Omnisend is the go-to email and SMS marketing platform for ecommerce stores. With Omnisend, you can automate your marketing campaigns, reach your customers across multiple channels, and drive more sales — all while building stronger relationships with your customer.

Here are some key features of Omnisend:
• Multichannel marketing automation: Reach your customers wherever they are, whether it’s email, SMS, or push notifications. Create custom workflows that trigger automated messages based on customer behavior, purchase history, and more.
• Personalization: With Omnisend, you can personalize every message to make it relevant and engaging for each customer. Use dynamic content blocks to add personalized product recommendations, discounts, and more.
• Segmentation: Segment your audience based on their behavior, interests, and purchase history. Create targeted campaigns that speak directly to each segment, and see higher engagement and conversion rates.
• Reporting and analytics: Get real-time insights into your email and SMS campaigns. Track your open and click-through rates, and sales, and use that data to optimize your campaigns for better results.

Whether you’re just starting out with email marketing or looking to take your campaigns to the next level, Omnisend has everything you need to succeed. 

3. Adwisely

Adwisely is an online ad automation platform for eCommerce stores. It helps online store marketing managers create and manage efficient ads on Facebook, Instagram, Google, and YouTube. Once you sign in, you can either set up a campaign by yourself – this should only take you a few clicks – or contact their support team if you have questions or need help. Adwisely combines the ad automation with human expertise & work with a wide range of markets and products categories. The account manager they provide can monitor the ad results, provide improvement suggestions and send regular reports on ad activity. As a result, Adwisely users get high return on ad spend – on average, their ROAS is 600%-700%.

4. SuperCEO

SuperCEO helps you get your daily business metrics on your mobile app and email daily. You can get accurate store sales insights to track your store’s growth from the total sales, new VS repeat customers, to the average order value on a single tap. It also helps you learn your daily business metrics instead of making decisions from your gut feeling.

Here are some key features of SuperCEO:

• Real-time insights on your mobile and email: You can get tailored real-time store metrics on your mobile & email every morning.
• Monitor revenue, cost, and profitability metrics: Now, you can unlock your store’s revenue growth with crucial metrics. Discover trends & insights to drive growth.
• Deep dive into data: Compare sales metrics by days, weeks, and months & discover insights and trends.
• Updates via notification: Get notifications on your mobile for critical sales metrics.

5. Tada

6. Smile: Rewards & Loyalty

Smile is one of the most popular reward and loyalty Shopify apps for fashion stores in the marketplace. It is currently being used by more than 25.000 merchants and keeps growing. A reward or loyalty program is a must-have in your fashion store, as it can help you improve your retention, so your customers will keep coming back.

With Smile app, you can run three kinds of programs: a loyalty points program, a referral program or a VIP program. Once you choose the program you wish to run, your customers can start collecting points for a variety of actions like purchases, friend referrals, registrations or social media shares/follows. These points can later be redeemed for discounts, vouchers, free shipping or other customised rewards.

7. Intelistyle

Intelistyle is one of the best Shopify apps for fashion stores to increase your sales and conversion. They have been working with some of the biggest fashion brands in the world like D&G, Tommy Hilfinger and MaxMara helping them increase their sales by up to 10%. Intelistyle has recently made its award-winning AI technology available for Shopify merchants, so they can get advantage of all the features they offer a fraction of the price!

Once you install the app, you will get:
1. Complete The Look Recommendations & Visually Similar
Intelistyle generates automatically personalised complete the look recommendations for all the products in your store to help you cross-sell and upsell your products easily. It also has visually similar recommendations in case one of your products goes out of stock, so you don’t lose that sale.

2. An AI Fashion Chatbot
Your customers can get styling advice from an AI stylist that will help them find what they are looking for easily.

3. Fashion Attribute Tags
Tagging all your products manually with the right labels and attributes can be a time-consuming experience. Intelistyle uses AI to automate this process for you and help you manage your products better.

8. Product Filter & Search

Have you ever wondered how easily can your visitors find what they are looking for in your store? Product Filter & Search allows you to create different filters for your search and allows your customers to search the products they are looking for by title, description, product type or even SKU.

Its smart search engine offers spellcheck, autocomplete and smart auto-suggestion in the form of thumbnails providing a great user experience. It is currently installed in over 7000 stores including brands like Mavi, Banana Republic, Lacoste and more.

9. Pinterest

You are probably already familiar with Pinterest, one of the biggest social media channels with over 300 million users. Pinterest Shopify app allows you to connect your store to your Pinterest account and quickly publish product pins to reach more customers. It basically gives you another sales channel to increase your reach and get discovered by new shoppers.

To sweeten the deal, Pinterest offers $100 ad credit when you connect your account to the Pinterest Shopify app and run your first ad.

10. Wanelo

Wanelo is another sales channel you can use to reach more customers. Their marketplace is bringing together 800K stores and 50M products, all shoppable from one place. Once you install the app, you will have to go through their review process (which might take a while) and then you can start selling your products in their marketplace.

Unfortunately, Wanelo is only available for US customers at the moment.

11. Oberlo

If you are just starting out and don’t have any supplier yet, Oberlo is the perfect app for you. Oberlo allows you to dropship your products directly from AliExpress. They even have a chrome extension, so you can discover products from AliExpress and add them to your store with a few clicks.

Once you have imported your selected products, you set your prices and you are ready to go. The moment an order comes in, you just confirm the order inside the app and that’s it. You don’t need to worry about logistics or inventory.

Aside from Oberlo, there are many other Shopify dropshipping apps for adding products to your store. Most of them are free to use and compatible with a variety of suppliers, not just AliExpress.

12. Rise: Gift Cards

Rise is a great app if you are looking to create a loyalty or rewards program for your customers. It includes a variety of marketing tools you will need to increase loyalty, retention, and satisfaction. You can use store credit to manage rewards and loyalty cards or set up a referral program to get your customers to advocate for your store.

Your customers can also send branded, digital gift cards and gift vouchers directly to gift recipients via email. The variety of their features give you the opportunity to structure your loyalty program as complicated as you want.

13. SEO Optimizer

Search Engine Optimisation should have a constant place in your marketing mix. SEO optimizer is currently installed in over 382,000 stores and runs automatically SEO improvements for your store. It will take over your technical SEO optimization, so you don’t have to worry about the continuous changes in Google’s algorithm. They run updates for your store daily to make sure everything is updated to best practices.

The app doesn’t guarantee increased search engine rankings, but they use the latest and best practises to optimize your store.

14. Klarna

You won’t find Klarna on the Shopify marketplace. Klarna is a direct payment method that allows your shoppers to pay at a later date. What’s more, is that you are getting paid full upfront, while your customers can choose to pay for their orders with a variety of options. One of the best Shopify apps for fashion stores to increase your conversion. The bad news is that is currently available only to merchants in Austria, Germany & Sweden.

Klarna is enabled by default when you set up Shopify payments provided you pass their review process. Once approved, your customers can choose Klarna as a payment option on checkout. They have also a Shopify app that provides customized messaging to let your customers know instantly how they can pay before they buy.

15. Size Matters

One of the most common reasons your customers are returning their clothes is that the fit wasn’t right. Size Matters allows you to create size guides for your customers to help you minimize returns. The app can easily be customised to the look and feel of your store, but most importantly it’s free!

Final Thoughts

There are a number of Shopify apps that can unlock new features and functionalities for your site and can provide a better customer experience for your customers and more sales. While the apps above are some of the best Shopify apps for fashion stores in the Shopify App Store, there are plenty more that can leverage your store to the next level. It all comes down to you to find the best app that suits your unique needs. Happy selling!

The post 15 Must-Have Shopify Apps For Fashion Stores in 2025 appeared first on Intelistyle.

Find out how remote selling allows your brand to sell more without the cost of increasing your existing sales capacity

Increasing Post-Pandemic Competition

Luxury and fashion consumers expect to spend less in physical stores and more on e-commerce moving forward, according to McKinsey & Company. They are not alone in establishing that online fashion sales will keep growing exponentially even when concerns about the Covid-19 pandemic ease. A study by Alvarez & Marsal in partnership with Retail Economics found that a quarter of the entire population who have adopted online shopping during the pandemic do not intend to change their new habits. While store traffic has nearly halved from a year ago, consumers are more inclined to buy and the average fashion spending has actually increased. However, as the demand for online fashion grows, so does the competition.

Service Is The New Competitive Advantage

In-store services conducted remotely have become a major competitive advantage across the retail spectrum in recent months. With global retail bodies warning that brick and mortar footfall will remain low, remote selling capabilities become crucial to the success of fashion and luxury retailers. Personalised shopping assistance is proven to increase consumer spending. While in the long run, strengthening the relationship between brand and consumer significantly increases customer lifetime value. Luxury and fashion brands are experts at relationship building and catering to the individual’s needs. The new challenge is doing this remotely and at scale. Director of Brand Engagement at retail intelligence agency Stylus, Katie Baron-Cox, explains to Forbes that “Generosity of service will become a key new metric for brands’. With the correct tool, personalised services will no longer be limited to in-person encounters: Retailers can easily channel their existing physical sales force to remote selling and enjoy a greater share of the growing online fashion spending ready to be claimed.

What Is Remote Selling

Remote selling – or virtual selling – is a buying cycle where sales and post-sales communications take place between a customer and a sales associate in different physical locations. Put simply, it means that a sales associate can sell to a customer who is located anywhere in the world.

Why Choose Remote Selling

In-store sales associates are a fashion retailer’s biggest asset in relationship building and customer loyalty. They communicate brand identity, convert new customers, truly know their loyal customers and serve them with the personal touch that is expected. All of this translates into higher single transaction values and long-term customer retention. Instead of restricting your sales capabilities to a branch or even a physical space, remote selling means that their expertise can be utilised when and where it is most needed. Yet, there’s a gap in resources that enable retailers to build in-person relationships remotely and recalibrate existing modes of selling for the online space. Enter Intelistyle’s Remote Selling Solution that delivers all benefits of face to face, in-person selling with the additional power of A.I. and data intelligence in one, easy to use App that is specifically designed to meet the unique needs of fashion and luxury retailers.

The Benefits Of Using A Remote Selling Tool

Sell On A Global Scale At No Extra Cost

Regardless of where they are based, sales associates can service any customer from around the globe as if they have just stepped into their local branch. The beauty of remote selling is that you can expand your in-store services to any location without the associated cost of opening a store and building a new team.

Zero Training Required

Once a retailer starts using Intelistyle’s Remote Selling Solution, store managers can easily onboard as many sales associates from their team as they want with a simple invite. The App is designed with user-friendly functions and quick user tips so that zero training is required to start remote selling immediately.

Increased Sales Capacity

Real-time customer requests for shopping assistance collect in a joint pool where all sales associates can see and pick them up. This means that your sales teams can swiftly alternate between serving customers in the store and serving an online customer remotely when store volume is low. Or even keep serving customers from their home. Removing physical barriers of service increases the capacity of your existing sales teams without investing in additional human resources.

Increased Sales Effectiveness

Assigning your sales force to real-time demand instead of location ensures that no sales opportunity goes missed. Additionally, assisting the customer at the optimum point when they are already invested in making a purchase allows sales associates to successfully upsell and cross-sell at the fraction of a full sales cycle. This means they can serve more customers and make more sales in the same time frame.

Enriched Customer Data

Sales associates can easily create customer profiles with detailed information on size, body type, colouring, price ranges as well as clothing attributes the customer favours and dislikes. They can even link a customer’s social media accounts and Pinterest wish boards to the profile. The A.I. merges all this information to filter a retailer’s entire stock. Sales associates can quickly see the products and complete outfits that match an individual customer’s requests, without any manual search. The profile is enriched with every interaction to include favourite looks and products, preferred occasions and past purchase activity. Sales associates can even take notes directly on the profile for future reference. Customer profiles can be shared, edited, marked as VIP, downgraded or deleted at any time.

Uninterrupted Customer Experience

In the event that a returning customer can’t be served by the same person, the sales associate taking over has access to their profile details, activity and notes. Additionally, they are supported by Intelistyle’s award-winning A.I. Stylist on the next best actions for that individual customer. This smooth hand over ensures that a customer can pick up their interaction with your brand where they left, independent of who is serving them. Continuity of exceptional service builds a trusting relationship with your customers and increases their lifetime value.

Choice of Multiple Platforms

Customers can choose how they get remote assistance: Intelistyle’s Remote Selling App supports multiple platforms including an online chat on the brand website and on the customer’s WhatsApp. Sales Associates can also get on a video call with the customer directly on the App. This feature closes the physical gap in selling from a distance so that sales associates can truly recreate a face to face store visit: display products from the store, demonstrate fit or show styling tips. 

Data-Driven Recommendations

While serving a customer, sales associates see product and complete outfit recommendations put together by the A.I. based on individual customer preferences. The outfit recommendations are presented in a tasteful mood board layout and can be titled for an occasion or trend. A.I. recommended outfits can be edited quickly by changing, adding, removing products or by changing the outfit layout with an easy drag-and-drop function. Alternatively, sales associates can create an outfit from scratch by using detailed search filters to find the right products at the fraction of the time spent on manual search. One or multiple recommendations can be shared with the customer directly on the chat at the click of a button.

Increased Team Performance

Managers can track individual and team performance on a master dashboard. Moreover, sales associates can monitor their own performance compared to the team average on important metrics including total sales and conversion. They can see the distribution of their commissions from individual products and from complete outfits. This visual, easy-to-digest dashboard allows sales associates to see their strengths and weaknesses. The weekly Leaderboard ranks top performers, introducing an element of gamification and constructive competition. These metrics encourage sales associates to meet higher performance levels and helps them identify areas of improvement.

Sales Strategy Support

Every day, sales associates can see new-in products coming to the online store, the trending products and most popular items. This knowledge allows them to make strategic sales decisions such as prioritising the newest stock or pushing products to clear out older stock before they are discounted.

Empowered Sales Associates

The App empowers your sales teams with a wide range of functions designed to increase their speed without compromising their service quality. Each sales associate can create and add to their own list of pre-set questions and group them under topics such as price-related or size-related enquiries. Pre-set questions significantly increase conversation speed, while ensuring the tone-of-voice is always on point. A comprehensive in-built filtering system lets them quickly refine stock by price ranges, available sizes, body types, colours and detailed product attributes. They can even browse the entire stock for all items that are suitable for a requested occasion – such as a cocktail party or a trend -such as monochrome looks. Upon customer request, sales associates can search for stores by location and stock availability to find the best physical store to visit. Through all of this, sales associates are able to serve customers with the human touch at A.I. speed.

Final Thoughts

The future of retail will be increasingly more remote and not only due to the pandemic effect. Yes, Covid-19 accelerated this shift but consumers were already feeling more comfortable online and prioritising the convenience of service. The most successful retailers are the ones who have adopted a customer-centric approach that combines physical and digital, technology and human to focus on the most important metric: Meeting customer demand wherever that is. If you want to see Intelistyle’s Remote Selling tool in action and explore how you can start selling remotely, get in touch!

Brands we work with

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Brands we work with

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Let’s have a comprehensive look at all current applications of AI in the fashion industry that can be integrated into a retailer’s value chain:

Artificial Intelligence (AI) has swept into many industries with the potential to revolutionise businesses through higher speed, lowered operational costs and access to a depth of consumer and market data that promise a strong competitive edge.

AI is a branch of computer science that stimulates intelligent behaviour in computer-controlled machines to perform tasks associated with human reasoning and capabilities.

It was no surprise that the fashion industry’s initial reaction to AI was a curious eagerness to be at the forefront of innovation mixed with reluctance. After all, automating an industry built on human creativity does come with understandable concerns.

At this point, it is important to highlight that AI uses human reasoning as a model but the end goal is not replacing it.

Best use cases in fashion look at AI as “Augmentative Intelligence”: Utilising machine learning, algorithms and rich data to augment the capabilities of humans and businesses.

The key here is to understand different applications of AI in fashion and adopt a tailored approach that plugs only into the areas where it can add value to your business model.

AI in BUSINESS OPERATIONS

Design and Product Development

AI to Assist New Product Development

By tracking design elements like colour, fabric, patterns and cut as well as their past retail performance and future performance indicators, AI reinforces and gives credibility to the creative decision-making process of product development in fashion.

AI as Designer

Using a powerful algorithm that analyses past designs and future trends, AI makes new apparel designs complete with sewing patterns. Retailers can choose to send AI-designed apparel straight to manufacturing or incorporate this as an additional step to automate the pattern making and fit process.

Human designers can then make alterations on these pre-designed garments to significantly speed up design to market time.

AI in Textiles

Garment Manufacturing

AI scales the manufacturing process in fashion through automating fabric quality control, pattern inspections, colour matching and defect detection. Manual manufacturing processes are completed by AI at a fraction of the time with increased accuracy.

Wearable Technology and Smart Fabrics

Although still at an infant stage, AI-controlled smart textiles promise clothing that delivers added value to the wearer: increase performance, enable communication, conduct energy and even grow with the wearer.

On the other hand, as more fashion brands shift towards environmentally responsible practices, AI in biotech facilitates the production of alternative materials that are cruelty-free and fully biodegradable.

Buying and Merchandising

AI empowers fashion buying and merchandising teams to make future buying decisions grounded in smart analytics with reduced risk of wrong predictions.

Traditionally, buying decisions have been based on the past performance of products and human instinct. This is not an accurate projection as sales are influenced by many dynamic factors like new trends.

Predictive Analytics

Through automated product tagging, AI analyses market performance on a per attribute level. Buyers are informed not only on the products that are performing well but also on detailed attributes like colour, prints, sleeves, necklines and more.

Additionally, instead of looking at trends and product performance as a snapshot at the end of each season, AI provides real-time data to observe shifting trends and stock performance as they are happening. Hence, buying and merchandising teams can adopt a proactive strategy to address consumer demand as it arises and always stay relevant.

Trend Forecasting

AI collects, analyses and interprets rich data from social media, e-commerce platforms and the runway to spot future fashion trends for each product category.

This information is then combined with the data on past performance and customer behaviour to establish the optimum product assortment mix that would resonate best with a retailer’s consumer base.

Styling and Merchandising Platforms

Personal Styling Platform

Retailers can build, track and manage comprehensive customer profiles using a flexible AI Styling Platform that automates and scales exceptional quality styling services. AI generates hyper-personalised recommendations for each client that can be speed edited on the platform. Finally, these outfits can be put into the shopping basket, shared via email or sent directly to the customer as a fashion concierge styling box.

Visual Merchandising Platform

Visual merchandising teams can use an AI-powered platform to speed up product page curations for the online storefront. AI curates bespoke pages to address different trends, customer segments and geographical regions more effectively. Using a drag and drop interface to edit automated product pages cuts down the time and cost of manual product presentation. 

Performance Analysis

Merchandising managers can use an AI-powered internal dashboard to track detailed performance analysis of each member on their team. Allocating team members to the customer/product segments they are best at optimises team resources and improves overall performance.

Head Office Operations: Retail Decision Insight

Inventory Management

AI provides detailed analytics that enables fashion retailers to accurately determine best geographical allocation and market drop calendar for their inventory while tracking and managing the entire product life-cycle in real-time.

Product and Pricing Mix Strategy

Retailers can use AI-powered rich data to address each customer and market segment with a tailored product and pricing strategy.

Making data-informed business decisions to achieve the ideal product-pricing mix for each market means less surplus inventory and fewer price cut-downs.

AI increases stock turnover by forecasting the need to “move” older stock and analysing it against demand forecasts. Inventory can be reallocated to targeted locations in order to meet demand and prevent store clustering. Markdowns and promotional strategies can be planned and prioritised accordingly to resonate with the right value-seeking customers at the right time.

Competitor Analysis

Monitoring competitor pricing, AI recommends ideal price points to optimise revenue by gaining a competitive advantage. Retailers can spot the best seasonal timing to keep lower prices while retaining minimal margin and when to slightly increase prices to maximise profitability.

Supply Chain: Improved Efficiency, Agility and Sustainability

Understanding the customer and market better reduces the production of styles that won’t sell which directly translates into lowered product waste output.

AI can also be implemented into the supply chain management process at earlier stages to improve efficiency, agility and sustainability.

Improved Efficiency

Combining historic timeline information with real-time data such as weather reports, AI can make accurate Time to Market (TTM) forecasts. 

Improved Agility

Equipping businesses with real-time data on inventory performance and rising trends, AI enables agile supply chain practices. Retailers can spot the best and worst performers in advance to stop scheduled production of products that don’t sell and increase orders on hero products.

Improved Sustainability

Analysing complex factors that contribute to carbon footprint, AI can identify the most sustainable supply partners and modes of transport for a business that still makes financial and operational sense.

Retailers are able to create a more sustainable business model without compromising on profitability.

AI in E-COMMERCE

Online Product Recommendations

Visual Similarity Recommendations

AI uses visual detection and key product attributes to recommend visually similar alternatives for each product on a fashion retailer’s online store.

When a product goes out of stock or size, customers are redirected to multiple relevant product pages on the retailer’s website. They can easily find what they are looking for without the hassle of restarting product search, which often leads to frustration and site abandonment.

Using similarity recommendations increases customer engagement and reduces sales opportunities lost to competitors.

Complete The Look Recommendations

AI uses the latest fashion trends and top styling principles to show complete outfit recommendations for each product on a retailer’s online store.

Customers often want to try out new clothes but simply don’t know how to style them. Outfit recommendations show customers the ways they can wear different products together.

Inspiring the customer with editorial quality AI styling means upselling and increasing basket size from just one product to a complete look.

Personalised Recommendations

• Personalisation Per Region

AI can personalise recommendations to show different results for different regions a retailer operates in. Trends, style identities and personal taste can significantly vary between different geographical locations.

What constitutes a ‘region’ can be tailored to every retailer depending on their own regional strategy.

For example, one retailer might use Europe and Asia as macro-regions. Meanwhile, another retailer might want to further personalise results for micro-regions within Europe to show different recommendations in Northern Europe, Central Europe and Southern Europe.

• Personalisation Per Customer Segment

Retailers can address their different customer segments with personalised recommendations that connect best with each segment.

Additionally, AI enables retailers to focus on different strategic goals for different customer segments they want to address. For one customer segment, it might make more sense to show recommendations that promote upselling, while for another one the goal might be to cross-sell.

AI combines different customer identities with different strategic business goals to show recommendations that help retailers achieve their business objectives on a per-segment basis.

• Personalisation Per Individual Customer

The power of machine learning and AI can be used to make visual similarity and product recommendations that are hyper-personalised to each customer, taking into account their individual:

and merge these with data on the individual customer’s past browsing and purchase behaviour.

Each customer is shown a different similarity and outfit recommendation customised to them for every product on the online store.

This brings online recommendations to the same quality standard of a bespoke personal styling service.

Retailers can scale personal styling services provided in-person to top tier VIP customers down to all customer segments without the cost of dedicated stylists.

Product Search & Discovery

Automated Product Tagging

AI-automated product tags are attribute labels that enrich each product on a retailer’s inventory. This detailed and fashion-specific information enables customers to filter their search by specific attributes they want to see: such as colour, print, fit, fabric.

Product searches return results with increased accuracy and relevance that bring the customer closer to a buying decision.

Automating manual product tagging with the use of AI means faster processing times, lowered cost, richer data and improved consistency free of human bias.

As previously mentioned, once a retailer’s inventory is enriched with product tags, their own stock becomes a powerful tool to understand performance, customer behaviour and inform future business decisions. This insight can be incorporated into multiple stages of the value chain.

Natural Language Search

Natural Language Processing (NLP) is the ability of a computer program to understand daily language as spoken by humans.

AI allows customers to search for products using the language and descriptions that they would naturally use in their daily life.

Simplifying product search reduces e-commerce friction and improves the customer experience.

Visual Search

AI-enabled visual search lets customers use pictures of clothing they like or influencer/celebrity styles they want to imitate to search for products. AI identifies all products in the photo and finds the closest match for each of those products from a retailer’s stock.

Visual search helps customers find exactly what they are looking for even in cases where putting it into text is difficult.

Letting the customers show what they want gives retailers the ability to inspire them with styles that match their taste. In addition, they gain a deeper understanding of changing consumer demand.

Personalised Landing Pages

A landing page is the entry point to a website or a particular section of a website built to drive traffic for a specific marketing goal.

AI personalises landing pages by displaying targeted content and a tailored product selection based on the marketing campaign: merging data of past customer behaviour and preferences with factors like campaign time and season.

Personalised landing pages increase lead generation, conversion rates and ROI of marketing activities.

Personalised Product Ranking

AI identifies what each customer is most likely to want and buy from a retailer’s inventory. Products are displayed in a personalised order for each customer to optimise sell-through rate while factoring in additional parameters like depth of stock and margins.

Personalised product ranking enables the best customer-to-product matching and ensures the right products are seen by the right customers at the right time.

AI in CONVERSATIONAL COMMERCE: CHATBOTS

AI-powered chatbots let fashion retailers stay in one-to-one touch with their customers before, during and after a sale. Chatbots fill the gaps in the omnichannel customer journey to deliver a seamless and uninterrupted brand experience.

A chatbot can be integrated into multiple touchpoints at a retailer’s e-commerce and social media platforms: the website, Facebook and even instant messaging applications such as WhatsApp, iMessage and WeChat. Communicating with customers on the same channels that they already use increases the convenience of shopping. Instead of waiting for the customer to come to them, chatbots enable retailers to be present when and where the customer is ready to engage.

Customer Service

Chatbots can be tailored to mirror a brand’s identity and tone of voice. This way, fashion retailers can scale their service capacity in key areas such as customer relationship management (CRM) and personal styling that are directly linked to the brand experience.

The chatbot can make product recommendations, arrange exchange and returns, answer customer enquiries and offer styling advice 24/7.

Also, the AI assistant interprets the flow of conversation and spots the best hand-over point where the customer can be connected with a human assistant. This approach significantly reduces the volume of enquiries for customer service teams while still allowing a human touch where needed.

Direct Sales

Chatbots can take pre-orders, make reservations for in-store collection and take payments to make direct sales.

Business Insight

As customers interact with a chatbot, AI collects rich data on individual customers and spots common patterns across the data. For instance, styles most frequently enquired or products most frequently complained about provides valuable business insight to retailers that inform future strategy.

AI and IN-STORE INTEGRATIONS

Physical retail remains a powerful tool in the fashion retailer’s arsenal to create exceptional omnichannel brand experiences. The use of AI can be extended offline to seamlessly tie in a customer’s online journey into the physical store.

Customer Service and Clienteling Support

In-store sales teams can use AI technology to easily browse in-stock inventory and find products that are right for the body type, physical features and individual taste of each customer they serve. Results can be further filtered to make spot-on recommendations for different occasions the customers are shopping for.

An AI clienteling tool empowers sales assistants with expert outfit styling for each product in stock. This means retailers can scale their personal styling capacity without the time and cost of training required to transform a sales assistant into a personal stylist.

An AI Remote Selling tool can connect your in-store sales teams to customers from anywhere in the world to augment your existing sales capacity and increase your quality of customer service at zero additional cost.

Personal styling adds real value to the in-store experience and significantly increases spending.

Shop Floor Time Optimisation

Sales assistants can use AI technology to instantly find and recommend similar items for products that go out of stock in the customer’s size or desired colour without the need to go through all available inventory. By spending less time on finding products, they can offer quality assistance to a higher number of customers per hour.

Making relevant product recommendations reduces missed sales opportunities while increasing sales per employee.

True Omnichannel Shopping

AI enables a retailer to recognise returning customers at every touchpoint regardless of the channels they have engaged within the past, truly breaking the boundaries of traditional retail. Connecting the data from all digital and physical retail locations under one umbrella means a loyal customer walking into a retailer’s physical store for the first time or at a different location can receive the fully customised service they are accustomed to.

Sales assistants can easily access a customer’s profile and immediately know their style, likes, dislikes and purchase behaviour to delight the customer with a bespoke experience every time.

Digital In-Store Experiences: Smart Mirrors

Retailers can integrate AI technology into a number of customer touchpoints on the shop floor to turn their store into an experience hub.

On The Shop Floor

AI-powered smart mirrors directly interact with the customer to make personalised product and outfit recommendations. This facilitates product discovery and reduces fatigue from an abundance of choice.

Through AI visual recognition, smart mirrors scan the customer and suggest outfits that complement the clothes they are wearing in the right size and fit.

Alternatively, they can be used to scan a product and see different ways of styling a complete outfit with other products in the store.

In The Fitting Room

When placed in the fitting rooms, smart mirrors let the customer find alternatives for the clothes that don’t fit or look as expected and request them to be brought to their cabin. Without the inconvenience of leaving the fitting room, customers are more likely to find the right products that result in a purchase.

Virtual Try-Ons

While this looked like a science-fiction scenario a couple of years ago, virtual try-on solutions have started making an appearance this year in the stores. Companies like Texel can show your store visitors (or online shoppers) how garments or entire outfits would like on them in a few clicks. 

Physical Store as The Experience Hub

Finally, smart mirrors can be used for interactive installations in the store as part of visual merchandising. These displays combine aesthetic and functional value, driving footfall and repeat visits to the physical store. They can be used in numerous ways to inspire customers and act as a storytelling tool.

AI in MARKETING & CRM

The power of AI, machine learning and rich customer data can be used to create marketing and promotional campaigns that are personalised to each customer. AI can accurately predict future purchase behaviour based on past purchases, browsing behaviour and individual customer preferences.

Retargeting Campaigns

Retailers can increase retention and repeat purchase by reaching out to their customers with relevant products and outfits that complement past purchases. Instead of retargeting campaigns that push alternatives from the same product category a customer has already purchased – let’s say, more white dresses – AI can create a personalised campaign per customer to suggest products that would complete a look – such as the bag and shoes that would look great with the white dress they already own.

Promotional Campaigns

AI detects the product categories, seasonal occasions and offers that a customer is most likely to engage with. Retailers can extend personalised promotions that correspond to the value each customer is seeking. Instead of generic promotional campaigns that might or might not have significance to a customer, they can extend targeted promotions backed by data that combine the right product selection with the right time of the year.

Loyalty Programs

AI builds a better understanding of what will drive higher engagement and a longer-lasting relationship between a retailer and each unique customer. Retailers can use this data to build a personalised loyalty program combining points, rewards and tiers. This adds value to the customer journey and accelerates loyalty by giving the customers more reason to keep engaging. Offering personalised rewards for referrals is a smart way of integrating customers into the client acquisition strategy as brand ambassadors.

Content Generation

AI is being used in content creation and automation by retailers who want to turn content into a powerful tool for lead generation and conversion.

AI-powered copywriters can automatically generate original content using natural human language. Automating periodic, short-form content frees up copywriters to work on higher concept creative brand assets and strategy.

Data-driven marketing content delivers higher conversion, click and email open rates in addition to a consistent tone of voice that is always on-brand.

Marketing Strategy 

AI accurately predicts future market trends to formulate short-term and long-term marketing strategy rooted in data and consumer insight. Taking the guesswork and ‘gut instinct’ out of key marketing decisions, retailers can make informed strategic choices on areas ranging from new product launches to periodic content planning. 

Key Takeaways

Integrating AI into a fashion retail business has proven benefits throughout the value chain:

AI provides multiple solutions for fashion retailers to more effectively address each pain point in the omnichannel customer journey and deliver a better brand experience that sets them apart from the competition.

However, integrating AI into a fashion business is like finding the right suit: one size does not fit all and the best fit will be achieved through a tailored application.

Fashion retailers who leverage AI as Augmentative Intelligence to supercharge their existing business model will scale their resources, amplify their core strengths, be empowered by data-driven insight to overcome their weaknesses and maximise their market penetration as a brand. Growing market share and revenue while cutting down operational costs means an increasingly profitable business.

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Brands we work with

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“Ones to Watch” list showcases 50 UK-based projects praised by experts for delivering new products, services and experiences through creative and tech expertise. This report, described as “who’s who guide of the UK companies at the forefront of Createch” was the highlight of the Createch 2019 conference held at London’s Code Node on 11^th June, as part of London Technology Week. The list was compiled by innovation research specialists Springwise with support from London & Partners and Digital Catapult.

Tim Davie, CEO of BBC Studios and Co-Chair of the CIC, a joint forum of government and industry said: “The intersection of creativity and technology is one of the most exciting growth areas in today’s economy. Createch 2019 will provide a unique guide for anyone trying to navigate through this fast-changing landscape.“

Createch has identified 4 key sectors that revolutionize user experience:

1) Immersive Entertainment

2) Transformative Experiences

3) Seamless Service

4) Personalised Tools

Intelistyle, AI styling and omnichannel personalisation start-up, is one of the 50 companies featured in the “Ones to Watch” list. “Styled by AI” isn’t yet a commonly used term, although that may be about to change, the report concludes. 

Intelistyle features in the “Personalised Tools VR ⁄ 3D ⁄ Robotics” category both for its B2B personalisation services to fashion retailers and for the personalisation offered to the end-user through its chatbot. The artificial intelligence (AI) software basically offers effective styling results across platforms: from in-store to online, even at home – a truly omnichannel experience.

Another reason Intelistyle made the list is the revolutionary technology that outperforms latest academic research to ensure excellent styling quality: Through the use of machine learning, the data from thousands of outfits put together by stylists, influencers, designers and retailers is extracted to decode the ‘essence of style’ and offer styling solutions.

The same exceptional styling quality got Intelistyle featured in Forbes, for outperforming human stylists during London Fashion Week in 2019.

Intelistyle’s “secret power” is providing customised, on-brand, personalised recommendations to fashion retailers, improving their KPIs (revenue, conversion, clicks-through-rate, average order value and more) while delivering a better customer experience.

Intelistyle in Createch: You can read the full report here.

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This article has been updated for the latest developments in fashion technology as of 2022 and was first published in May 2021

The world’s most significant and profitable industries are facing massive changes thanks to advances in technology. More specifically, blockchain, artificial intelligence (AI), new types of financial transactions and a number of other big leaps in tech are responsible for these ongoing changes to how most industries do business.

Focusing on the fashion industry in particular, these are some of the technology we expect to transform businesses on both online retail and in-store operations.

Blockchain Will Fight Counterfeit Products & Streamline The Fashion Supply Chain

The distributed ledger technology called blockchain is mostly known for being the foundational tech behind cryptocurrency. More generally, a blockchain is basically a string of chronologically arranged code. Each new block of code on the chain requires every computer with access to the blockchain to approve the addition of that data via a shared cryptographic solution, which translates to peer-verified security in every data transfer, addition or modification. It all happens nearly instantaneously, without any of the red tape commonly attached to security protocols. And this same technology can be used to protect products and ensure quality in the fashion industry.

Label Tags Will Redefine Origin and Ownership

Each individual fashion item can be tagged with labels attached to blockchains, which allows everyone in the supply chain to verify its origin, ownership and every time it has changed hands. The LuxTag Project took to Medium to detail how some fashion designers are already taking advantage of this potentially revolutionary technology as a product integrity solution. Back in 2017, Londoner Martine Jarlgaard produced the first smart label-tagged garments. Scanning the tags gave users time-stamped info on everything about the garments – from raw material acquisition and factory information down to how the finished products were packaged and delivered. Similarly, fashion retailer Babyghost used near-field communication (NFC) chips to tag its 2017 summer and spring collection. This allowed customers to use the NFC tags to find out everything they wanted and needed to know about every Babyghost product.

Supply Chain Transparency

Apart from ensuring product integrity, this can also push fashion labels to be more honest about where they get their raw materials, how they conduct labor practices and everything else customers in 2020 (and beyond) will be concerned about. Essentially, information sharing and supply chain transparency are about to become realities in the global fashion industry. This technology is a potentially huge boon to managing the fashion supply chain, the fight against counterfeit goods, and corporate social responsibility.

Competitive Payment Options Will Dictate Retail Preferences

In recent years, payment platforms such as Paypal, Amazon Pay, Payoneer, Venmo and Dwolla have played increasingly large roles not just in online retail, but in various other spaces such as vacation rentals, gaming and service industries. The reason is simple: these payment options offer the convenience and security that some more traditional methods lack. By and large, newer, more innovative payment platforms are now making things even easier for both customers and product and service providers.

A payment technology that has already changed the way customers shop is the buy-now-pay-later services that allow customers to buy a product today and pay for it later. Klarna is one of the service providers at the forefront of this technology in the fashion industry.

Another example is the service called Paysafe Pay Later allowing customers to delay payment until after their ordered products have been shipped, all in a way that doesn’t impact the company’s cash flow. A New Zealand-based gaming company details how online casinos now use the Paysafecard, which is similar but slightly faster than using VISA and other debit/credit cards. Independent of bank, card or other personal financial information, Paysafe instead relies on a single, 16-digit pin to credit money to a customer’s account and verify transactions. It’s currently seeing heavy use in gaming and retail – two of the biggest revenue sources on the web. And it’s just one example of a new payment service that could prove to be a deciding factor in how customers choose which fashion retailers to shop from in the future.

Artificial Intelligence Will Change Everything

There are several reasons why Intelistyle cannot help but cover how AI will change the face of retail. For one thing, AI algorithms are responsible for well-informed and relevant product suggestions for online retail customers. For another, AI can be used to predict trends and product demand, allowing retailers to be better at managing inventory and catering to customers’ needs.

Though they may seem simple, even those small perks can help retailers avoid serious problems – such as the massive surplus Under Armour faced in 2018 when it overestimated product demand and wound up $1.3 billion the hole! And even this is only scratching the surface of the benefits A.I. can provide to retailers.

When integrated into a chatbot, AI can help fashion retailers scale their personal styling services and improve their omnichannel customer service experience.

Examples could go on and on, but even the relatively brief write-ups above provide a picture of how a small handful of tech innovations can and will revolutionize the fashion retail business.

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AI Stylist Outperformed Fashion Influencers

In February 2019, after training and testing our AI Stylist for 2 years we decided we were ready for London Fashion Week. We previously spent a lot of time testing with various stylists we worked with, as well as by withholding parts of the dataset from the model and measuring user behaviour in our app. We were itching though to take it to the ultimate fashion event of the industry and see the reactions of random members of the public.

Our goal was not to run a scientific experiment. This happens daily in our lab, where we test with thousands of outfits (see how ai fashion styling works). Our goal was to interact with real people, hear their feedback, see their reactions and most importantly satisfy our curiosity. Would fashion lovers from all over the world be able to tell the difference between an AI and a human stylist?

AI Stylist vs Human Stylists

So we decided to design an experiment. We generated 10 sets of outfits. In each set, we had two outfits of similar style: One generated by our AI stylist and the other created by Instagram fashion influencers.

The question we asked participants, was “Which outfit was created by an influencer?”. Here is an example.

We used SurveyMonkey to run the survey. Our sample consisted of 27 participants, 82% of whom were female. Each correct guess got 1 point. Participants scored on average 46%. For reference, if they were randomly responding to the questions they would have scored 50%. The highest score by a participant was 80% and the lowest 10%.

Often participants asked what were the criteria to make the decision and our answer was “Choose the outfit you like best”. 70% of them prefered the outfits created by our AI Stylist.

How the AI Stylist Works

So how do we do this? We examine thousands of outfits put together by human stylists, influencers, designers and retailers. Through deep learning, we extract the essence of style. We go a lot further than your typical computer vision techniques that focus on pattern recognition. Using machine learning to find visually similar clothes is commonplace these days.

However, style is a lot more nuanced than finding similar patterns or colours. Two seemingly different patterns or fabrics can be combined together to build a stunning finished look. And two pieces of clothing that would normally clash, can be brought together in a beautiful outfit with the use of right accessories. Employing the latest deep learning technology, we have just started decoding the genome of style which enables us to assign a unique signature to every piece of clothing. AI is only at the beginning of its journey but it’s making huge leaps every day.

Why is this important? Well, it is a huge step for diversity in the fashion retail industry – both luxury and fast fashion retailers are putting inclusion to the forefront of their offering. While body positivity is a huge movement, most retailers still build their lookbooks through studio photoshoots with fashion models. This means that looks offered to customers on retail websites cater to one body type, skin tone, hair tone and eye colour. Offering styling advice to each customer is expensive for a retailer. And what about different occasions, weather and style preferences?

AI offers the potential to scale fashion styling advice, creating outfits personal to the needs of each customer, celebrating diversity and individuality. Companies such as Stitchfix have already demonstrated the power of that approach. We want to take this further, allowing customers to digitise their wardrobe, style their own clothes and receive a personal service across their favourite retailers.

Read the full Forbes article on the success of our AI Stylist at London Fashion Week.

Interested in learning more? Get In Touch!

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