With a whopping 7.8 billion people in the world, there’s a lot of room for original ideas, creative innovations, and new perspectives. Today, the global fashion apparel market is booming with a current value of $1.5 trillion US dollars, an increase from $1.3 trillion in 2015, according to Statista. Take a second to let that sink in. The consumer desire for apparel will continue to rise at an alarming rate, challenging producers and brands to develop a strong, strategic approach to meet the ever-increasing demands. In apparel product design and supply chain logistics, fashion brands have the advantage of consumer behavior analysis and trend forecasting, which they can use to best anticipate and meet the market demand.
Understanding Fashion Consumer Behavior
Socioeconomics has some of the most prevalent impacts on apparel buying behavior, heavily determining the degree of purchasing power. However, in the context of fashion, consumer buying behavior is quite complex. In this day and age, consumers are influenced by many different factors outside of socioeconomics. These fall into the psychological, social, cultural, personal, or economic categories.
Established brands have to stay up to date and modify their operations according to these categories in order to appeal to their target market. The challenge here is determining the most efficient way to maintain the original market while simultaneously attracting new customers. Hence, we see the importance of the psychological factor of people’s wants. What’s the point of producing apparel if customers don’t want to buy it?
From income to age to education, these demographic variables can guide brands’ determination of how to adapt to the current market. A prime example: teen consumers’ obsession with fast fashion and the accessibility that comes with it.
Fast fashion has controversial socioeconomic and environmental implications. In the past 15 years, clothing production has almost doubled as the middle class population rises across the globe, according to the Ellen McArthur Foundation. This data clearly shows rapid spread of consumption across the globe. Fast fashion brands were able to benefit from this market of consumers who valued low cost, quickly delivered, disposable clothing.
However, lately there’s been a shift in the fashion industry that sheds light on the issues surrounding fast fashion. Consumer education and awareness around global apparel production issues is driving a shift to more sustainable fashion principles. With this, brands will now focus their attention on how to create and produce more consciously sourced products at a cost efficient level while still smoothly adapting to new market trends.
Trend Forecasting
Trend forecasting uses extensive data from past sales and applies it to the current market in order to predict upcoming trends within the fashion industry. It is essential to predicting consumer demand because it gives fashion buyers and producers a deeper understanding of what to produce and how to produce it. Whether it’s predicting patterns, colors, or styles, the benefits that stem from long-term consumer trend forecasting are immense.
In order to attain commercial success, brands must understand consumer behavior and trend forecasting. By doing so, they learn how consumer decisions are made and how various products are used and are able to adapt their inventories to curate the highest selling product mix.
Comprehensive knowledge of your brand’s customers – why they’re buying and what they want to buy – is the key to establishing a competitive advantage against fashion competitors of all sizes. From creating effective omnichannel campaigns to the use of data analysis tools, apparel companies can use modern technology to put their production and marketing dollars behind customer data learnings, and expand their business’ reach, influence, and ultimately, sales. The use of data is essential for fashion brands every step of the way, from product design, to supply chain, to tempting the end consumer with a “buy now” hook that will capture their sale.
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