Consumer insights are vital to a successful business model in apparel manufacturing. Fortunately for manufacturers, customer spending habits are now being recorded in the form of big data. Big data enables apparel manufacturers to forecast trends for future clothing lines as it allows them to track consumer behaviours such as their style, preference, likes and dislikes. Manufacturers can also profile their customers based on a number of different variables such as preferred communication channels, geographical location and demographic analysis.
To analyse and transform this data into useful, meaningful insights, manufacturers need a system that can process vast amounts of data quickly and efficiently. For many, ERP software has offered this solution.
Collecting the Data
When using an ERP, data is recorded and collected from each and every aspect of the business, from orders, production, delivery, supply chain, purchasing, sales and just about any other operation that is part of the manufacturing process. The more data manufacturers can capture, the higher degree of accuracy they can achieve when using forecasting or reporting tools to achieve meaningful insights for future business.
Making the most of your data is important and for apparel manufacturers it’s vital to their success. Apparel manufacturers must keep up with current trends and understand real-time changes within the market to provide the best possible product and remain competitive.
ERP utilises technologies such as AI and machine learning to make sense of this data and provide a basis for better decision making and greater accuracy. This then enables manufacturers to operate with the knowledge they need to meet consumer demands and preferences.
Demand forecasting is an essential task used to determine the variety and number of products manufacturers need to produce for a given period or season. This is typically based around a variety of factors including previous sales history, popular items sold, previous dead stock items and inventory history.
Demand forecasting allows manufacturers to adapt their production schedule and planned product development to meet predicted demand. By understanding the needs and requirements of their customer base, manufacturers can also reduce the amount of wasted materials, products and resources created from over purchasing and over producing items that don’t sell.
Being able to collect and analyse all of this data also allows apparel manufacturers to segment their customers based on different criteria including:
Customer segmentation is a process utilised by many businesses to divide customers into groups that have common similarities or features. Using this information, apparel manufacturers can then tailor their products to attract those who are more likely to buy them.
Understanding consumer buying habits also means more effective marketing for retailers as it allows them to target customer groups based on personal preferences and demographic analysis. Information derived at point-of-sale can then be fed back to manufacturers for future product development.
By using a size, colour, style matrix to profile consumers, apparel manufacturers increase the likelihood of customer retention and brand loyalty, which ultimately increases yearly growth and sustains regular revenue.
Interested to find out how your apparel manufacturing business can understand your customers’ needs better?
Without the correct software many apparel manufacturers struggle with analysing vast amounts of data to generate consumer insight. If you’re having difficulty managing your data, then Syscom can help. We work with apparel manufacturers and provide them with the tools they need to succeed.