Big data analysis is key to onboard buyers successfully (Part 1)

Our marketing and the merchandising teams are now under pressure as lots of buyers are canceling their running orders. Some buyers postponed their shipment dates due to the ongoing COVID situation. If the factory cannot be able to deliver the goods at a scheduled time the inventory will go up, payment will be delayed and liabilities will go higher.Our marketing and the merchandising teams are now under pressure as lots of buyers are canceling their running orders. Some buyers postponed their shipment dates due to the ongoing COVID situation. If the factory cannot be able to deliver the goods at a scheduled time the inventory will go up, payment will be delayed and liabilities will go higher.

So it is a normal demand to onboard some new customers to survive and continue the business expansion. However, in this pandemic situation, it is very hard to onboard new buyers since the buyer is under pressure too. They do not want to develop any new suppliers as they could not settle their existing orders, also the end customer is saving money to face the COVID challenge. In this dire situation, it is very important to understand the future demand of a market. If you do not understand the future demand of the market, you will not be able to give quick support to the buyers and cannot bring customer satisfaction that will lead you to lose the business.

Way to identify future market demand to understand the future market demand, we need lots of data and data analysis tools. Nonetheless, it’s really unfortunate that though we are passing the mature stage as a producer country, we are not using any data collecting tools yet which can analyze the big data. Big data is a field that treats ways to analyze, systematically extract information from, or otherwise, deal with data sets.

The gravity of data has been gradually recognized by fashion professionals to improve sales and margins because fashion brands and retailers need to develop, manufacture, and sell styles that resonate with consumers.

Finally, advancements in data analytics, machine learning, and computing power, the value of utilizing artificial intelligence (AI)-based software or applications has been well recognized by fashion brands, suppliers and retailers who want to apply a data-driven decision-making approach to develop more efficient fashion design, merchandising, and marketing strategies. Data is abundant in the current fashion business environment as sales data, product information, and consumer data are constantly collected and analyzed. There are many retailers like Amazon, eBay, Alibaba, or pure online players who have been aggressively finding ways to apply advanced data analytics to improve performance in design and product development, merchandising, marketing, operations, channel management, etc.

The most significant reason fashion brands and retailers are seeking ways to optimize data analytics is to improve their product offerings through precise personalization for targeted customers, which would eventually bring higher sell-through and profitability.

According to the survey done by JDA Software Inc. in 2018, 2019 43% of fashion brands and retailers planned to invest in customer-based data science in the next five years for converting customer data into personalized merchandising assortments based on their lifestyle and localized trends.

Big data collection software collecting data from social media like FB, Twitter, Likee, Tik-Tok, shopping behavior, eye movement, body language and so many ways. This type of scattered data does not give the specific decision, to make any specific decision about design, fashion trends, target customer, seasons, and cultural trends need to use data analysis tools which will give the perfect decision to make the best design for the target customer and it will increase sales and the profitability.

If Bangladesh’s fashion industry does not align with the customers’ demand and the marketing strategy, the industry will lose business and some smart manufacturing countries will be replaced in our position.

I know about one of the giant textile factories of Bangladesh–didn’t want to mention the name of the factory–who attended a Trade Fair in the USA in 2019 when US buyers were looking for winter collections, the company brought all of the summer products.

A customer came and observed their products, but they did not express any interest to place an order. When they did the root-cause analysis found they are lacking in having enough data about the market, upcoming situation, future prediction, trends, seasons, etc.

So that suppliers in the fashion industry need to incorporate data analytics and AI technologies in their design and merchandising processes. Otherwise, they cannot onboard new customers and they will not be able to enter new markets.

(To be continued…)