Introduction
In today's competitive markets, B2B companies must constantly look for ways to outperform their competitors. Many companies are using AI in B2B e-commerce to gain a competitive advantage.
In fact, artificial intelligence is quickly becoming critical for business survival. According to IDC, global spending on #AI is expected to more than double over the next four years, rising from $50.1 billion in 2020 to $110 billion in 2024.
AI in e-commerce: Solving tough problems
To support customer loyalty and revenue growth, wholesale distributors and other B2B organizations are increasingly leveraging intelligent technology to interpret data at scale and identify real-world solutions to business problems.
In contrast to the mechanical feeling of traditional automation, #AI can help analytically, practically, or even creatively by leveraging machine learning.
#B2B organizations have a wealth of data about their products, their customers, and their interactions. Using these sources, machine learning technologies can adapt to new situations as they arise, learning from data in real time to make a positive impact on the business in ways that no human can.
#AI in e-commerce can help companies solve complex business challenges with greater ease and speed by allowing them to:
Enhance customer experiences
Make better business decisions
Reduce costs and increase efficiency
Accelerate time to value
1. Save the sale
In B2B e-commerce, a customer may discover that their desired product or products are out of stock and then abandon their purchase. As a result, the customer is dissatisfied and sales are lost, often to a competitor. #AI can offer timely and smart offers to save the sale when the original item is out of stock or not the right fit for the customer using product data, product context, interactions, and user context. This dynamic and ongoing loss prevention across all products improves the user experience and increases revenue.
2. Intelligent Comparison
B2B buyers prefer to do their research before buying the product. In fact, the ability to compare the price and features of products is among the top five reasons customers buy online rather than in-person. Not providing such a facility can frustrate the customers. In this situation, B2B shoppers can implement AI technology to provide intelligent comparison abilities from their sources of data to their products to attract buyers.
3. Smart Replenishment
When it comes to orders, modern B2B customers expect self-service, and repeat buyers have become increasingly reliant on B2C-centric capabilities like quick-order forms and automatic replacement.
In this case, AI uses data from interactions, user context, and firmographics to enable smart product replenishment.
4. Category Management
This is a common issue for many B2B purchasers. AI can assist category managers across hundreds of categories and attributes in balancing product performance, thereby increasing demand, profit, and more with the help of product context and interaction data.
Conclusion
These use cases provide compelling evidence of the value of AI in B2B e-commerce. Now is the time for businesses that have not yet begun to implement AI to support their B2B e-commerce strategy.
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