My interest in Data Analytics began in 2020 when I stumbled on an article about different case studies of analytics in the Fashion Industry. Honestly, it was a long read, about 60 pages in all, but I enjoyed every bit of it, way more than any other fashion tech-related articles I had read.
This sparked my interest in Fashion Analytics, especially in Africa Fashion Businesses.
Sadly, I found little information as regards this subject in the African Fashion Industry, and each time I mentioned to people I was exploring Analytics in Fashion, it sounded somewhat strange to them, yet interesting.
I discovered that not many fashion professionals were aware of the application of data analytics in Fashion businesses.
Rather than enlightening people in my immediate environment alone, I came to the conclusion that “Fashion in Africa needs to be re-imagined” and I began to think about how I could contribute to that, hence the reason for starting a fashion tech blog.
Each article gears towards enlightening and educating fashion tech enthusiasts, young professionals, designers, retailers, and students on the disruption of Advanced Analytics and Machine Learning in the Fashion Industry.
If you belong to either of the categories mentioned above, this article is certainly for you!
Before delving into the application of Advanced Analytics let me shed some light on the impact of the covid -19 pandemic in fashion retail.
The Impact Of Covid-19 Pandemic In Fashion
According to Fashion United, the fashion industry is valued at over 3,000 trillion dollars which is about 2% of the world’s Gross Domestic Product (GDP).
In 2019, the global apparel and footwear market was approximately $265 billion markets with Nike alone generating over $39 billion in revenue, and the market is projected to rack up to $3.3 trillion by 2030.
Irrespective of the unprecedented surprise of the covid 19 pandemics, fashion experts still projected a 20% or more growth in online businesses in 2021.
Unfortunately, not all businesses were quick to adjust to the changes induced by the pandemic. While some businesses were quick to embrace analytics (doing better by 68%, Source: McKinsey & Company report ), others that stuck with traditional marketing or were late to adopt technology and innovations began to lose market share and some closed down.