How can AI be used in wholesale e-commerce to update prices?
AI in wholesale distribution.
Meet Karl, a sales manager at a specialist wholesale company in Germany. Like many in his industry, Karl is under significant pressure from the rapidly evolving e-commerce landscape.
With a customer base of 7,000 and an inventory of 50,000 items, he struggles daily with pricing complexities.
His competitors, from Amazon Business to the garage wholesaler next door, are agile and tech-savvy, using the latest technologies to optimize their operations. Karl knows that to stay ahead, he needs to adapt, and he needs to adapt quickly. Yes, e-commerce in wholesale is both a blessing and a curse. You can sell more and expand your market and your competition.
B2B is not B2C, but updating the prices of Karl’s thousands of products every week is a mammoth task. How can he update his wholesale e-commerce prices quickly and securely?
Enter AI, a transformative technology that promises to revolutionize how wholesalers like Karl update prices. We are talking about AI as ChatGPT and AI as Autopilot.
The Growing Need for AI in B2B Wholesale E-Commerce
First, some basic concepts. The wholesale industry, which has traditionally relied on manual processes, intuition, and personal relationships, is undergoing a significant transformation. With the rise of e-commerce giants, customers now expect dynamic and competitive pricing. Static pricing strategies are no longer viable.
According to a study by McKinsey, companies that use AI to inform their pricing strategies see a 2-5% increase in margins. This is a compelling statistic for wholesalers looking to stay competitive. Of course, not every distributor has the same proportion of online sales, and some still rely mainly on bricks and mortar. I believe the danger threshold is around 35% for Germany. If your sales are above that level, it’s time to say goodbye to Excel and hello to AI!
For Karl, the challenge is to make sense of the vast amounts of data his company generates. Historical ERP sales data, customer behavior, and market trends are invaluable assets that are often untapped because of their complexity. Remember, he indirectly knows everything he needs to know about his customers and products. He could use many offline sales transactions to identify trends before online sales. But how?
This is where sales analytics and predictive sales software come in. These AI-driven tools can crunch huge amounts of data and uncover insights that would be impossible to find manually. There’s no chance that he could update 300,000 prices every week using a spreadsheet. So, why not use AI and predictive sales instead?
The Power of Predictive Sales Software in Wholesales and Manufacturing
Predictive selling software uses machine learning algorithms to predict future trends. For Karl, this means he can anticipate customer demand, adjust stock levels, and, crucially, set dynamic prices that reflect real-time market conditions.
By uncovering hidden patterns in ERP data, AI software can identify which products are likely to see increased demand, when, at what prices and in what quantities.
A fascinating application of AI in B2B sales is the ability to segment customers granularly based on their buying behavior, including predicting their individual prices.
And Karl does not need to understand exactly why AI is suggesting what it is suggesting, just how to use the AI-based predictions. With these insights, he can tailor his pricing strategies to each segment, maximizing profitability and customer satisfaction. Have you recently bought an airline ticket or booked a hotel? Who decided on the price you paid?
Real-World Success Stories Using AI in Wholesale
Take the example of a German family-owned wholesaler, a company like Karl’s. A real customer whose name remains anonymous. By integrating AI-driven sales analytics software from Qymatix, the third-generation company has improved and transformed its pricing strategy.
Using AI with three years of ERP sales data, the company uncovered trends and patterns that had previously gone unnoticed. As a result, they implemented dynamic pricing in a few weeks, which adjusts prices based on real-time market conditions and customer behavior. Within six months, the wholesaler saw a 13.7% increase in margin and nearly a 10% increase in revenue. AI also improved customer satisfaction.
Another compelling case study is that of a large mechanical components distributor with half a billion euros turnover. This company used predictive sales software to price its vast inventory of 80,000 items. The software enabled the company to predict which products would be in high demand during certain seasons and adjust prices accordingly. This foresight enabled the company to optimize its inventory levels and pricing, reducing waste and increasing profitability.
Implementing AI: A Step-by-Step Guide for Wholesalers and Components Manufacturers
For Karl and other sales managers who are considering applying AI to their pricing strategies, the process can be broken down into manageable steps:
• Collect and prepare data.
Collect historical ERP sales and customer behavior data. Clean and organize the data to ensure accuracy. Talk to potential vendors about their experience with ERP data.
• Choose the right tool.
Use sales analytics and predictive sales software that meets your business needs and has proven experience in your industry. Consider scalability, ease of integration, and ease of use.
• Pilot project.
Test the AI tools on a small scale with a pilot project. This will allow you to assess their effectiveness and make necessary adjustments before a full rollout. Consider how AI will change your sales team and current sales processes.
• Integration and training.
Integrate AI tools with your existing systems and train your team to use the new tools effectively. Consider AI vendors that already offer online training.
Implementing AI has its challenges. Data quality is a common obstacle. The underlying data must be clean and comprehensive for AI to provide accurate insights. That may require investment in data cleansing and integration processes. However, for wholesalers, data quality is never a showstopper.
Resistance to change is another challenge. Employees accustomed to traditional methods may be skeptical of new technologies. It’s important to clearly communicate the benefits of AI and provide adequate training and support. Experienced vendors and their enablement teams usually support this.
The Future of AI in B2B Wholesale
The potential for AI in B2B wholesale is significant. As technology evolves, AI will become more sophisticated, offering deeper insights and more accurate predictions. For wholesalers like Karl, this presents an exciting opportunity to stay ahead of the competition and meet the market’s ever-changing demands.
Gartner forecasts that by 2025, AI will be responsible for 95% of all customer interactions in B2B sales, emphasizing the crucial need for businesses to adopt these technologies now. Wholesalers who embrace AI now will be best placed to flourish in the future. When will you start?
CALCULATE NOW THE ROI OF QYMATIX PREDICTIVE SALES SOFTWARE
How can AI be used in wholesale e-commerce to update prices? Conclusion.
Karl’s journey symbolizes the wider transformation taking place in the wholesale industry. By leveraging AI, he can navigate the complexities of pricing in a dynamic marketplace, ultimately driving profitability and customer satisfaction. The message for wholesale sales managers and executives is clear: “The time to embrace AI is now.”
The benefits of AI in B2B sales are too significant to ignore, and the risk of being left out is too high. From dynamic pricing to cross-selling, AI offers many opportunities to optimize online operations and stay competitive. By following a structured implementation plan and overcoming common challenges, wholesalers can unlock AI’s full potential.
As Karl looks to the future, he knows that AI is not just a tool but a strategic asset that will shape the success of his business. For wholesalers everywhere, the journey to AI-powered pricing begins with a single step: “The decision to innovate and adapt.”
Contact us to learn more about how our solution can help you stay ahead in a competitive marketplace.