Online fashion retailers are excited about the prospects that are brought upon by implementing artificial intelligence into their businesses. When you offer someone the capability of managing processes faster, better and cheaper, you can instantly see their eyes glimmering with glee.
Is it actually the case with AI, which fashion retailers use today, or is that a promise of an uncertain future?
Nowadays, AI is often being communicated as a black box – you feed it data and you get great results, fast. Although it may be the case for certain AI use cases, we are still far from such instant successes. The reality is that commercial AI is still in its infancy and are we on the frontier of its development and application in the real world.
Most current AI algorithms are making predictions and choices not unlike humans. They learn from historical data, and as we will be able to provide AI with higher quality training data, its precision could dramatically improve.
That being said, even now AI supported by big data already ignited the so-called 4th industrial revolution. Two years ago, industry magazine Business of Fashion proclaimed that no area of life or business will be insulated from AI and today these technologies, as well as easy access to their utilization, are disturbing every aspect of any industry, not just fashion, like never before.
Companies Stumble to Find Ways to Apply AI
Even though media is buzzing with AI and big data, we are still scratching the surface of what’s currently possible as fashion retailers are actively looking for ways of how to best apply the benefits that AI promises.
According to a study by IMRG & Hive, Three quarters of fashion retailers will invest in AI over the next 24 months and e-commerce giant, heavily involved in fashion retail, Alibaba, already invested $15bn in R&D labs in a push to become the AI leader.
Still, with great potential of AI, sometimes it just doesn’t work out. Let’s take Original Stitch as the example.
This startup, which sells custom dress shirts, promised their customers that after sending them the picture of their shirt, their AI armed with visual recognition will extract customers’ sizes out of photos of shirts which they already own as a basis for a custom-tailored shirt.
Sadly, this didn’t work out and the outcomes were underwhelming, leading the company to pull its AI until they work out the issues.
Impact of AI on Online Fashion Retail
The ever-increasing scale and granularity of personalization in online fashion retail are impossible to manage without the assistance of AI and related automated processes. Gartner predicts that by 2020, customers will manage 85% of their relationships with an enterprise without interacting with a human.
A growing number of companies who have adopted these new technologies are raising the bar on service and personalization, which customers have learned to expect.
Currently, 44% of UK fashion retailers are facing bankruptcy and AI could be one of the many factors that attributed to it as companies who didn’t find a way to properly implement it, are struggling to be competitive with the ones that did.
McKinsey says that the top 20 percent of fashion businesses generated 144 % of the industry economic profit and unless you become one of these top performing companies, you are highly unlikely to make any profit. That’s why finding ways to implement AI is crucial as it helps companies streamline their costs and provide a better customer experience. This helps in becoming competitive and being placed among the TOP 20 percent of fashion businesses which actually turn a profit.
How Are Customers Interacting With AI
Generation Z is highly accepting AI, and most notably, personalization that comes with it, but older generations still tend to be unsure of AI’s impact on their lives and are wary.
The distrust may be in part because companies utilizing AI still didn’t find a way to best communicate the positive impact of artificial intelligence on the user experience and that increasing sales are just a product of a seamless customer journey.
Today’s customers expect from their ideal online store that it won’t “waste their time”, that they will find the products that fit them, in stock and in a large variety to choose from. With that in mind, customers yearn for a personalized experience, which is exactly what AI can help them achieve, using deep content personalization and thus, AI is slowly, yet steadily transforming the way customers shop for fashion online.
What are the Uses for AI in Online Fashion Retail?
Some AI use cases could be highly niche, such as Sephora’s virtual artist, which lets customers try out makeup online. Yet others are already being widely implemented with a varying degree of success due to utilizing varying algorithms and data they are basing their decisions on.
One of the most common AI use cases in online fashion retail is visual recognition. These algorithms will recommend similarly looking apparel to customers and are most often used on detail pages of online stores ensuring that customers will always find the right product.
Visual recognition can also help online retailers recommend appropriate tags when adding new products to the store, saving time. Or, using visual similarity with past products to help purchasing departments better understand the volume of how much they should be purchasing to minimize overstock.
Customer Purchase Prediction
Leveraging aggregated data from all of the customers, AI algorithms could be used to predict whether certain customers are showing signs of making a purchase out of data, such as visits of a certain number of product pages or increasing frequency of newsletter opens.
These insights are then being leveraged to ensure the purchase and create a positive customer experience.
By monitoring social media and other data sources, AI could be utilized to predict trends according to similar behavior in the past and its results.
These insights could be used to inform the purchasing department to stock certain types of products or marketing to prepare specific communication campaigns.
One of the worst problems which fashion retailers are facing is overstock issues.
AI is being utilized to predict which products should be purchased to meet the upcoming trends and in what volume. This is being based on the purchasing power of customers and even current stock in hopes to reduce overstock.
Some algorithms could also be used to predict supplier price changes and recommending the ideal purchasing windows to lower the purchasing costs.
Fashion retailers tend to have significant capital tied up in inventory and artificial intelligence is being utilized to help them increase the turnover of stock by taking into consideration the “need” to sell older stock as soon as possible.
This is a crucial AI use case that helps fashion retailers increase their profitability, since the longer you have inventory in stock, the chances to sell it decrease.
Ideal Price Point Recommendation
Using freely available data, AI can be used to monitor competitor product prices and recommend ideal price points to maximize revenue.
These changes could be automatically applied using a broad strategy, such as keep the lowest prices, but retain at least a minimal margin or to maximize profitability even by slightly increasing the price.
Another use of AI in e-commerce are AI chatbots, alternatively called smart assistants, which could be used by online retailers to help their customers find what they are looking for through a conversation mimicking a help from an assistant in a brick-and-mortar store which could lead in the increase of store’s global conversion rate.
A pioneer in the use of AI chatbots in online fashion retail is Levi whose chatbot helps their customers to find the perfect pair of jeans.
What Are The Realistic Expectations For The Future?
Undoubtedly, the complexity, speed, and precision of tasks which AI will be able to expertly execute will grow. Artificial intelligence will become embedded in our daily lives and it will enhance our professional performance which will create an ever-increasing divide between businesses which will find a way to utilize AI and those who would be too late.
One example of AI’s evolutionary path is being implemented by Tommy Hilfiger. This highly recognized fashion brand would like to use AI to kickstart their creative process. To do that, they announced a partnership with two major players: IBM & Fashion Institute of Technology.
The goal of this initiative is to monitor real-time trends in the fashion industry and customer sentiment centered around individual products or runway images and extract themes in patterns, silhouettes, colors, and styles.
Avery Baker, Tommy Hilfiger’s chief brand officer said that “the goal was to equip the next generation of retail leaders with new skills and bring informed inspiration to their designs with the help of AI.” He continued by saying that “AI can identify upcoming trends faster than industry insiders to enhance the design process.”
Companies armed with such a powerful utilization of AI will be able to produce new apparel faster than their competitors and with a higher probability of matching market’s needs with their collections, becoming more profitable than their competitors.
Why Are SaaS Companies Like Exponea Leading The Charge
Proprietary algorithms developed by sole fashion retailers could have a lasting impact on their businesses and are providing them with a competitive advantage. But, their development isn’t contributing to the evolution of AI across the whole industry.
SaaS companies, such as Exponea, whose consultants are on the lookout for repeating patterns across various online retailers are supplying AI development teams with insights, which are pushing the precision of algorithms, which could be applied across the industry.
AI development teams are coming up with new solutions to test out across multiple online retailers, proving their feasibility behind a pure hypothesis or a single use.
That is the reason why we at Exponea are so highly focused on AI. By developing and perfecting our algorithms, we empower our clients to leverage our collective know-how to become highly competitive in their respective markets.