International consulting firm Accenture recently released a report: "Artificial intelligence in retail: Scale at speed" . Although there has been a lot of news in recent years about the potential of AI (artificial intelligence) to disrupt the retail industry, in fact the hype and hype of this technology has reached its limit. Accenture believes that it is imperative for retailers to turn experimental investment in AI into a truly viable solution to reap large-scale returns.
Accenture data shows that 86% of retailers are currently experimenting with the possibility of AI, hoping that it will change the industry to drive growth and set new benchmarks for financial and operational success. There is nothing wrong with this "experimental" phase, but only by going beyond the proof of concept and translating technology into solutions can the true value of AI in the retail industry be realized and large-scale returns for the entire business.
The problem is that most retailers are still experimenting. Many retailers' AI programs are just one-off trials within their existing businesses. When many teams buy AI solutions, they do not fully consider the foundation of the entire business and the impact it will cause. Due to the lack of organizational-wide cross-functional strategies or the necessary procedures, skills, and management structures to adapt to them, the return on AI projects is often smaller than expected. This creates an inertia that makes it difficult for retailers to turn their ambitions of "being a true data-driven organization" into reality.
Not only "testing", but also "moving real"!
Accenture said that as all competitors are using AI to find advantages, it is imperative that AI release value, not just prove value. Therefore, retailers should translate their great ideas and concepts into real-world innovations and use AI to provide further personalization, accuracy and profitability.
The value of personalization has been fully understood by the industry, but the question is whether the personalized strategy of fashion retailers can target the correct market segment ? Accenture data shows that usually 33% of profits come from 5% of customers. So retailers can use AI to first identify those customers with the highest value, and then focus on personalized information that best suits those customers. For example, Stitch Fix , an American fashion e-commerce company based on AI algorithms , combines the professional skills of AI and human designers to achieve large-scale personalization. This fast-growing startup has comprehensive insights into each user's preferences, lifestyle, and budget, providing scheduled apparel ordering services to more than 3 million customers.
AI can also help retailers accurately optimize the entire supply chain . By applying tools such as machine learning to massive omnichannel customer data, retailers can make more accurate predictions, including what consumers will buy, who will buy it, when, where and how. These are important factors that radically optimize inventory and reduce time to market. For example, French supermarket chain Intermarché is using machine learning, computer vision, and data visualization to help staff provide classifications based on the specific needs of each region. By creating a "data factory", Intermarché is rapidly transforming AI concepts into viable, large-scale solutions to rapidly increase productivity and growth.
The value of a new technology ultimately depends on its impact on profits. Accenture's research shows that companies using data analytics and AI technology are growing much faster than companies using backward technologies.
4 considerations for unlocking the value of AI
With the right AI strategy, fashion retailers can really begin to unlock value on a large scale. In this process, there are 4 points to note:
First, remember that people are the true driver of business value .
The senior management team should lead AI from the highest level to ensure that employees and intelligent technology work together. This includes integrating the right talent mix and supporting innovation across enterprise architectures. For example, creating a multidisciplinary center of internal and external data experts can help retailers maximize AI returns.
Second, the quality of AI tools and solutions depends on the data used to "train" them.
Therefore, having a data strategy that includes all currently available multi-channel data sources, including video, social information, geographic locations, and POS and inventory. This issue is often overlooked at the highest levels. In fact, Accenture research shows that half of retailers with more than $ 1 billion in sales have no specific measures to evaluate new analytical capabilities.
Third, choose the right platform to support the AI program.
Cloud platforms can scale quickly to support continuous AI innovation. Giant platforms provided by global technology giants excel at leveraging data insights to streamline processes and integrate new features. These platforms can also help retailers find partners and build collaborative ecosystems, especially in areas such as demand perception and predictive analytics.
Finally, the construction of the management system has been valued from the beginning.
This is not the most appealing part of AI, but it is critical to successfully transforming experiments into large-scale innovations. A good management model will help identify value, prioritize actions, and optimize returns. It is also essential in managing the necessary cultural change and the responsible use of artificial intelligence as organizations are shifting to AI-driven decision making.
The above 4 points can help fashion retailers get rid of endless testing, accelerate and expand the value of AI. With the rapid evolution of the competitive landscape, this is becoming a fundamental capability for any retailer looking to open new growth paths.
Use AI Responsibly
In addition, in this age of responsible retail, businesses need to operate ethically and fairly in terms of customers, employees, partners and investors, and the global environment. Retailers can use data security, privacy, and transparency to deliver value to customers, and AI technology is no exception. Responsible retailers are adopting AI to maintain user data privacy, use information and tools in a secure and transparent manner, while unleashing the benefits of data.
It's time to use artificial intelligence smartly and begin to translate it into true market value on a large scale.
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