If you want to be successful in retail, you have to use technology at an early stage and put the customer at the center of all decisions.
The digitization and technical progress, especially artificial intelligence (AI), are changing retail market in numerous industrial sectors, including tech, agriculture, studios, product testing, inspection, certification, insurance, and most important, retail. Customers are buying more and more online instead of from traditional stores, having a presence across all relevant sales channels has long been part of everyday life, and innovative business models are becoming increasingly popular. AI enables business models that were barely conceivable just a few years ago. Retail companies should use the changes strategically to get as close as possible to their customers.
Skepticism or a lack of know-how?
20% of the US consumer and retail companies surveyed have no plans to use AI.
As a 2019 survey by EY and Microsoft shows, the gap between companies that embrace AI and those that are hesitant is widening. So far, over 20 percent of the America consumer and retail companies surveyed have no plans to use AI.
This share is significantly higher than in other industries and shows that there is an urgent need for a change of heart in retail – especially with a view to the technical innovation of the market leaders. After all, AI solutions have the potential to revolutionize retail.
Four innovation areas for artificial intelligence in retail market
In total, four fundamental innovation areas for AI systems can be identified: customer experience, logistics, production and business model.
1. Sustainably optimizing
The customer experience AI can enormously improve the customer experience. Some retailers are already doing this: With the help of comprehensive data analyzes, customers receive individually tailored offers. When buying a flashlight, for example, the right batteries are automatically offered – provided the customer has not recently ordered a larger quantity.
With what is known as demand sensing, we look to the future, so to speak. The customer is offered products that he will probably need soon. This is very effective, especially with easily calculable everyday products. In this way, the need for shampoo, mineral water or toilet paper can be estimated well in advance on the basis of existing customer data. In the best case scenario, the products are also delivered automatically – a relief in everyday life and thus an enormous added value for the consumer.
2. Precise production processes and make them transparent
Information such as weather data, purchasing behavior and economic-political incidents can flow into the systems and make planning processes more precise. In addition, a consistent exchange of information leads to a previously impossible transparency. And it can be done even better: Through the intelligent use of customer data, articles could be produced in individual units.
3. Improve logistics processes
On this basis, in turn, raw materials could be delivered precisely – that is, only as much as necessary for the specific order quantity. In this way, farmers can use the sales data from their partner organic markets to harvest and deliver exactly the amount of fruit and vegetables that are expected to be sold. Accordingly, overproduction or capacity problems in the warehouses could be prevented.
4. Let new and innovative business models emerge
When AI optimizes production and logistics, new, data-driven business models can emerge that go far beyond what is common today. Fragrance manufacturers could orientate themselves on reviews of articles purchased so far. Skin cream producers could incorporate the individual characteristics of each individual customer into their production.
Retail companies remain skeptical
Despite all these advantages, many USA retail companies are still skeptical. This is mainly due to a lack of know-how about marketable and relevant AI technologies, but also to the lack of clarity as to how unstructured data can be used to create added value. Another challenge is likely to be the expected costs.
But retail companies in particular can be dearly for this skepticism. After all, the market leaders in the industry have already noticed the impulses of the new technologies and are pushing the limits of what is technically possible. They are making huge investments in developing systems that will enable them to provide customers with seamless shopping experiences well above the competition. For smaller-sized companies, even with substantial investments, it will be a challenge to keep up with this development.
Think from the customer perspective and clearly focus investments
You should think consistently from the customer’s perspective and clearly focus any technical investments. Traders who do not have the financial resources or know-how of the big companies should limit themselves and clearly define in their activities at which point they can achieve the greatest leverage.
A bifocal approach can help here: on the one hand, foreseeable and regular purchases should be handled as effectively as possible and the buying process from the proposal to delivery should be practically seamless. On the other hand, the best possible supply with suitable product offerings should be promoted.
If retailers apply this approach, this would enable significantly improved customer loyalty, which in turn increases the profitability of their business – and thus creates the basis for more extensive investments.
Conclusion
Artificial intelligence (AI – extended Super.AI) has the potential to revolutionize retail. Four fundamental innovation areas for AI systems can be identified: customer experience, logistics, production and business model. However, many US-based retail companies remain skeptical and thus miss the opportunity to increase the profitability of their business.
