Evolving Fashion Industry With Augmented Reality & AI/ML

    Evolving Fashion Industry With Augmented Reality & AI/ML

    In the 21st century, technology-driven innovations like artificial intelligence (AI) or machine learning in the fashion industry are changing every aspect of this forward-looking business domain. Fashion brands, emerging designers and industry professionals can use the digital hub to interact with buyers, media, influencers and consumers from anywhere in the world through an engaging, multi-channel experience that includes chats, video conferences, bots, holograms and completely virtual spaces.

    The use of AI in the fashion industry has become so well entrenched that 44% of the fashion retailers who have not adopted AI are today facing bankruptcy. Supported by the easy availability of big data, customer personalization, and other services in fashion companies are simply no longer feasible without the use of AI in fashion.


    Source: https://www.chainofdemand.co/how-artificial-intelligence-is-fashions-perfect-fit/

    According to TEC, the leading 20% of the global fashion brands are generating 144% of the industry profits. Driven by this necessity, fashion brands are investing in AI and ML technologies to remain relevant in a highly competitive marketplace. 

    Accelerating Innovation and Growth

    If you aren’t using Artificial Intelligence (AI) to communicate with your customers, your company is already falling behind. 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. Here are some of the ways in which these technologies are making an impact:

    AI- Enhanced Apparel Designing

    With more sophisticated data collection, we can help fashion brands to adopt technology to understand customer needs and design better apparel. TEC can power your company using AI-powered fashion designing that is based on the customer’s preferred colours, textures, and other style preferences.

    AI-Powered Visual Recognition

    Visual recognition is most often used on the detail pages of online stores, ensuring that customers will always find the right product. With Visual recognition we can assist online fashion retailers by providing a solution that recommends appropriate tags when adding new products to the store, saving time. Visual similarity can also be used with past products to help to purchase departments better understand the volume needed, minimizing overstock.

    Artificial Intelligence for Clothing and Apparel: Visual Recognition

    AI -Induced Trend Prediction & Manufacturing

    TEC can help Fashion brands using AI and ML tools to identify fast-changing fashion trends and supply the latest fashion accessories to retail shelves faster than the “traditional” fashion retailer.

    AI apparel and AI clothing styles: AI could be utilized to predict the next trend in fashion through monitoring social media and other data sources, learning from similar past behaviour and its results. AI-based approaches for demand projection, however, can reduce forecasting error by as much as 50%. 

    AI systems are being used to spot defects in fabric and ensure that the colours of the finished textile match with the originally designed colours. AI technologies such as computer vision technologies are allowing quality assurance processes to be more streamlined. 

    AR & VR Powered Virtual Merchandising

    AI-enabled technologies like augmented reality (AR) and virtual reality (VR) are now closing the gap between online and in-store shopping experiences. TEC can help develop in-store AR that allows shoppers to access any merchandise through intelligent mirrors, smart Bluetooth tags and digital media. Using VR technology we can assist fashion brands to create a virtual image of their pop-up retail store.

    AR Fitting Room Features

    AI Automation= Lesser Operational Costs

    TEC with its expertise in AI and ML technologies can enable fashion houses to automate repetitive or mundane tasks usually performed by human agents. Tasks like data entry and customer support can be handled now by AI, thus freeing human agents to focus on more strategic activities. 

    Return of sold items is a major bane for the entire fashion industry and can increase operational costs. AI-enabled personalization and product information, customers are more informed and are less likely to buy the wrong clothing item. This, in turn, does reduce returned products and also improves customer satisfaction.

    Adopting a data-driven approach is the way to go in this modern age. TEC harnesses AI and big data to make more accurate predictions. We help inform brands through product personalization and solutions in AI and machine learning technologies. AI isn’t a magic formula that can eliminate every pain point at the snap of a finger. For it to be truly effective, retailers and vendors should begin entering as much data into their systems as early as possible, and start immediately. Get Your Quote Now.

    Moving to the center of the customer’s universe

    Moving to the center of the customer’s universe

    Data is to this century what oil was to the last one: a driver of growth and change. Flows of data have created new infrastructure, new businesses, new monopolies, new politics and—crucially—new economics.” – The Economist, May 2017

    If you purchase this ‘data is that the new fuel’ analogy like several have, ar|you’re} already aware that firms altogether completely different industries are defrayment (or reaching to spend) a major level of investment in AI initiatives. Giants like Google and Baidu spent $30B and $20B severally on AI in 2016, according to McKinsey, and investment is anticipated to grow by three-hundredths in 2017, according to Forrester. the price of doing nothing is unconscionable. within the same report, Forrester predicts insights-driven firms will ‘steal $1.2B’ from competitors annually by 2020.

    What’s motivating such a big amount of firms altogether {different|totally completely different|completely different} industries to leap on the AI bandwagon? we have a tendency to believe one among the first drivers is to deliver essentially different expertise for his or her client – one that focuses on growing the link and meeting the requirements of their customers once and wherever they’re.

    Imagine associate degree illustrative client scenario: alphabetic character and Jason understand they’re quickly outgrowing their house with a growing family. Do they appear to shop for a much bigger home, or do they increase the footprint of their existing home?

    Intelligent Bank Scenario

    Figure A: Typical client Interaction with Bank vs. Future AI-Enabled Relationships

    Today: The couple during this state of affairs undergo a series of tasks and activities to assist them create their call, starting from doing their own analysis, rebuke friends and family, aiming to completely different websites to seek out rates, home costs and alternative items of information. the primary bit purpose the monetary service company has with this couple is after they finally select a mortgage or home equity line. In alternative words, at the top of that entire client journey.

    Tomorrow: Imagine if you because the institution will move up front within the decision-making method. maybe serving as associate degree enabler for serving to to optimize the choice and lay out all the situations. associate degree AI-enabled bank anticipates the requirements of a client and brings a group of tools and information along to empower and inform the client on their journey – not simply at the top of it.

    The benefits of re-positioning the role of the bank among this client journey square measure large. The monetary services organization evolves from being a transactional entity to 1 that’s targeted on building the connection and meeting the client wherever they’re (Figure B). In alternative words, you because the monetary services supplier square measure ready to move to a additional strategic, proactive and relevant position.

    Re-Positioning Your Brand Enabled by AI
    Figure B: Re-Positioning Your Brand Enabled by AI

    So where do you as a business start on this journey? It ultimately begins with what value you want to unlock and a use case that will highlight your organizational aspirations. One way to determine where and how to focus is through the use of an innovation agenda framework that brings together customer, business, and trend analysis to pinpoint opportunities to test.

    Once you identify the right use case, you want to enable that experience in the best way possible – allowing for experimentation, quick pivots, and speed to market. We would propose an investment in the foundational technical building blocks that enable faster software production releases, and easier integration of systems and data through APIs.  These core capabilities allow you to experiment faster and with greater efficiency. This platform approach also enables more consistent customer touch-points across digital channels. Our Intelligent Bank Platform strategy brings together those building blocks (Figure C) and enables you to start your journey towards becoming a smarter financial institution.

    Building Blocks to Building a More Intelligent Bank
    Figure C: Building Blocks for a More Intelligent Bank

    So you want to fundamentally change the relationship you have with your customers leveraging AI as a means to re-position your organization at the center of a customer’s experience. How do you go about doing this? Here are 5 things you can do today:

    1. Look at your options, but avoid locking yourself into a specific AI vendor solution. The switching cost of a misaligned vendor solution is high.
    2. Identify a customer pain point that can benefit from a more proactive relationship with the bank powered by better insights and a suite of relevant third party services.
    3. List the services, APIs, and experiences you want to bring together to create the optimal customer journey.
    4. Establish a mechanism for experimentation so you can quickly connect to the right services and APIs and test them in the market to get quick learnings.
    5. There’s no doubt about it – this is challenging work. But, broken down into manageable parts, it’s easier to get a meaningful win sooner rather than later.