According to McKinsey & Co, the global fashion industry profit has suffered a massive setback in 2020: -93% compared to 2019. While it is almost superfluous to point out the reasons for this, many brands are reacting towards simplifying operations. Above all, the period of difficulty has demonstrated the lack of resilience of the industry as a whole. On the other hand, it has highlighted the value of digital not only as a tool for marketing activities but also for business transformation. Therefore, there is now the possibility to reinvent e-commerce by creating a new shopping experience.
In terms of operations, the fashion world has for a long time followed more or less standard dynamics, timing and cycles, only to accelerate abruptly (before COVID-19) as a result of the need to satisfy an increasingly fast, unpredictable and connected consumer. In the clothing sector, for example, the rigid seasonality of production was already giving way to a sort of mass customization much appreciated by the younger generations. However, marketing times for new collections were becoming increasingly shorter.
The philosophy of mass production months in advance and poor demand forecasting is in no way adaptable to today’s speed. With trends that are constantly changing and consumers who are increasingly attentive and selective, efficiency has become a must-have.
AR in fashion industry means entering an ecosystem of solutions that range from the optimization of operations. Starting to the personalization of the relationship with the customer, up to the increase of sales after loyalty. Perhaps the most interesting aspect of all is the prediction of trends, that changes at an accelerated pace. AI can intervene directly on the design, that is, inform designers, in a predictive way.
Improving Efficiency with AI
There are AI-intensive tools on the market that apply image recognition technologies to ar clothing app and, by cross-referencing them with demographic and geographic data, identify current trends in specific areas and age groups, so as to intervene in time with dedicated collections and products. Demand forecasting tends to have a strong impact also on waste reduction, optimization of inventory levels and production costs. Thus having a beneficial influence not only on business efficiency and competitive advantage but also on sustainability and environmental impact. The latter is a major factor in the fashion industry, especially since fast fashion has taken over: frequently changing clothes to follow trends fuels a disposable model that encourages continuous purchases and shipments and ends up weighing on sustainability. More accurate forecasting of demand, including sizes, colours, tastes and assortments of individual stores can make a difference.
Thinking about efficiency, AI can optimize supply chain processes; creating not only more efficient relationships with players in the same supply chain and create a new shopping experience. Moreover, it can also optimize all the logistical of customer’s needs who are becoming less patient to see the collections.