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Clothing Industry is Taking Advantage of AI Featured

Clothing Industry is Taking Advantage of AI "Long Legs"

Technology is indeed changing many industries. With technological advances, all industries are doing their best to find ways to deliver better quality, attract more customers and make more profits. Artificial intelligence (AI) is leading the way in changing fortunes for many industries. One such area that is receiving massive backing from this technology is the fashion industry. Although this industry has lagged in the adoption of technology before, it is benefitting immensely from AI. Here are some ways the clothing industry is taking advantage of AI to offer competitiveness.

AI helps to promote and sell fashion products

The fashion industry is more about creating demand and brand awareness, just as it is the case in fashion industry. Clothing and fashion industry constantly looks for new ways to get their products to the buyers, create awareness and build demand in the market. The brands in this industry are increasingly using AI and machine learning to improve users’ shopping experience, enhance efficiency of sales systems through automation and use predictive analytics to guide sales processes and predict demand.

Customer support

Fashion brands are leveraging conversational assistants through chatbots. Voice assistants such as Amazon’s Alexa, Microsoft’s Cortana and Apple Siri are also key in customer support. Using these conversational interfaces allows fashion brands to understand what the customer wants, their trends, purchase patterns and suggest items they may want to buy. For example, instead of a customer interacting with a website when purchasing new products, they can have a conversation with the chatbot or intelligent conversational agent about the same. Through this dialog, the customer can find the fashion product or accessory that suits their needs. This interaction provides customer satisfaction and valuable information for a particular fashion brand.

Smart recognition

AI is making way into mobile applications. With these apps, customers are now able to take pictures of the cloths they want or styles they to imitate and match the photos with the available items that are sold. This eases the way customers find cloths or other products of their choice within a shop or store. AI-enabled shopping applications allows customers to take screenshots they see online and identify the same outfit in a shop before they can purchase them. 

Personalized shopping

Online shopping is challenging and has infinite choices that often overwhelms customers. This can sometimes leave them less satisfied and thus hesitant to buy items online or face countless challenges making buying decisions. The solution that AI provides for this challenge is personalization of shopping experience by offering more engaging and positive shopping experience to the customer. AI uses machine learning to analyze the shopping history and remember the customers’ likes, page clicks, purchases and the length of stay in a particular page. These parameters are used to gauge interest in certain products. With this knowledge, AI then provides recommendations to the customer on products that they may like.

Trend forecasting

Fashion trend forecasting entails predicting possible trends for fashion. Conventionally, fashion trend forecasters combined their knowledge in fashion, intuition and historical data to predict the possible trends in the industry. This approach was not effective and accurate and ended up providing wrong predictions. In the era of AI, this has changed significantly. Through machine learning, AI can capitalize of different types of data to predict trends. For instance, some modern AI-enabled apps can analyze millions of social media pages within a short time and provide patterns of demand and predict the possible direction in the future, this is a critical technology for the fashion brands, which can stock their stores of manufacture products based on the potential demands. This is a notable development that only AI can offer, minimizing losses that was the case when using traditional approaches.

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Scott Koegler

Scott Koegler is Executive Editor for PMG360. He is a technology writer and editor with 20+ years experience delivering high value content to readers and publishers. 

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