Blog
Stylumia brings the latest blogs on Color AI, Retail AI, Fashion AI & Ecommerce AI with the help of data-driven insights
Messy Middle For Fashion Business
| 4 min read If you are in any creative field, you would not have missed Behance, a platform for creative people to organise their work. Its founder Scott Belsky is one of the knowledgeable professionals in the world who comes with a great blend of creativity and business. This edit is inspired by his recent book “The Messy Middle“. We could not resist […]
Finland’s Visionary Initiative: AI Literacy
| 5 min read Every transformation in our history has been through a leap in intelligence. Be it an industrial revolution or technological revolution. Intelligence starts with awareness. Maybe that is what made the Finnish government come out with an approach to “Turning Finland into a leading country in the application of artificial intelligence”. The approach document is 76 pages long and […]
2019: A Year Of Awakening For Fashion Players
| 4 min read The recent report on State of Fashion 2019 by Mckinsey/BOF captures popular sentiments across the global fashion industry. While the signals are popular sentiments, the exact impact on your business can be very different depending on how you adapt to the new paradigm. This edit looks at the top 5 trends for 2019 for fashion players […]
Fashion Risk Or Return: What To Manage For?
| 3 min read In this edit, we will introduce a construct to enable fashion business managers and their teams to effectively manage and differentiate fashion risk and return. The essence of portfolio management is the management of risks, not the management of returns. Well managed portfolios start with this precept Benjamin Graham This is a great perspective for […]
Why Experts Are Bad At Fashion Prediction?
| 5 min read It is a counter-intuitive fact that people with a lot of knowledge predict poorly. Whether it is the interest rate, diagnosis of a patient or fashion prediction, it is no different. Let’s find out why and also see what experts can do to improve the chances of better prediction. We hunt regularly for reviews on Amazon before buying […]
Sound Of Style: Sensing Beyond Human Perception
| 2 min read It is amazing to look at different human senses and learn from their interplay, for example, the visual and hearing. The seed for this edit occurred when I was reading a blog from StitchFix which conducts industry-leading personalization experiments. One of the challenging problems in fashion is to identify the style or taste of a consumer. Traditional ways to […]
The Future Of Retail: Metrics That Matter
| 4 min read With the summer coming to an end and the fall preparation on, it will be good to take a look at the Retail landscape from a consumer perspective for the future of retail. It is also the right time to review your goals and start to measure what matters. As Peter Drucker said, ”What is measured […]
The Dragonfly Vision: Super Prediction
| 3 min read One of the key questions as we talk about super prediction in the fashion world which keeps coming frequently is, What will be the trend one year/ x months from now? Every fashion brand or retailer the world over is looking at improving their accuracy on prediction and trying to improve their probability of success. We […]
Fashion And FIFA Football World Cup 2018
| 3 min read Living rooms these days are buzzing with football fans cheering for their favourite teams. While this is the scene at the front, there is an invisible Brobdingnagian – Artificial Intelligence, around this football world cup. While the surprise of what will turn out every match is thrilling for the fans, there is a lot of investment […]
Fashion Buyers Are Hedge Fund Managers: Demand Learning
| 4 min read Let me start with a disclaimer that I am not a proficient investment professional. Analogies sometimes help communicate a point lot more clearly. This edit is an attempt to bring in the word of investment and retail and brand buying together with demand learning. A quick look at wiki gives an idea of how hedge […]
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