Data intelligence is the process of analysing and transforming large datasets into intelligent data insights that can be utilised to improve services and investments using AI and machine learning methods. The use of data intelligence tools and techniques can assist decision-makers in gaining a better understanding of acquired data in order to improve business processes.
The industries have seen a great leap in their businesses with the help of data intelligence.
AI in the Textile Industry
Garment and textile production has traditionally been a labour-intensive industry, as evidenced by the fact that many of the world's major fashion, clothing, and apparel firms appear to manufacture a significant amount of their products in Asian countries.
Textile manufacturing enterprises with exposure to past and real-time operational data may use AI to increase productivity and supplement the skills of their human workers, thanks to the growing use of industrial automation within that industry.
We'll look at how artificial intelligence can be used in the textiles sector today, as well as what AI might be capable of doing in the next two to five years.
Ways to Conduct Textile Market Research with the Help of Data Intelligence
It's critical to be relevant and competitive in the fast-changing textile market if you want to survive and develop. And apparel and textile businesses frequently require fresh ideas to meet the changing demands of the industry and consumers. But, all too often, innovative ideas fail due to a lack of market research.
To match the market, market research is essential for any textile and garment company. Businesses must improve their products in order to engage with the appropriate customers at the right time. And you'll need the appropriate data to connect with the right customers.
Types of Research
Apart from the collection of primary and secondary data, research analysis of the data collected is an important step. Market analysis is used to build an innovative business model and implement the proper market strategy. Understanding your consumers' behavioural responses, assessing competitor operations, and so on are some of the other applications.
The Data History
Data intelligence is a long-term commitment. Data collecting must be done over a long period of time. This enables a company to have a large number of data sources. When needed, these data points (usually stored on the web) can be referred to.
Data is not all created equal. Businesses can squander time sifting through large amounts of data. As a result, data hierarchies should be considered when creating a database. To put it another way, the crucial areas should be easier to find.
To fulfil market expectations, businesses must study the data and adapt their present marketing plan. And in order to design and test plans that capitalise on emerging consumer needs, decision-makers must prioritise their organisation's aims and objectives.
To capture and track the developing market, the garment and textile industry requires a solid plan and strategy. To be competitive in the market, they must refresh their data and strategy on a regular basis. Short- and long-term business strategies must be prepared by businesses. They must also be willing to change their strategy if needed.
Data intelligence technologies should be integrated into a company's online activities whenever possible.
Thus, using data intelligence, the garment and textile industry can conduct effective and smart research. For more such insights and updates from the world of fashion, connect with Fashinza.