How to reduce customer churn in B2B distributor sales: 4 AI-powered use cases
B2B distributors lose up to 15% of their annual revenue due to customer churn. New AI-enabled tools help sales reps break the cycle.
Looming above all the day-to-day business pressures that wholesale distributors face is one overarching strategic requirement: Find ways to grow profitably — without increasing staffing levels.
To meet that challenge, distributors must attack it from multiple angles:- Get creative in developing new revenue streams around high-value services
- Sharpen pricing
- Optimize management of inventory and logistics
- Deliver faster, more personalized service to boost customer retention
That’s a lot to tackle, especially during a labor shortage. In fact, in a 2023 report from the industry association MHI, supply chain executives identified recruiting and keeping qualified workers as their company’s most formidable supply chain challenge.
Here’s where intelligent technologies — business AI, generative AI, machine learning, etc. — can play an important role. By starting small with AI and ML capabilities, then branching into other use cases as comfort with the technology grows, companies can begin to optimize, extend, and transform key facets of their distribution business, and in doing so, increase margin and revenue.
Getting started with AI in wholesale distribution
How and where to begin? Because the insight AI models produce is only as good as the data that feeds them, the first step is making sure your data is clean — standardized, trustworthy and fresh.
Due diligence when evaluating AI applications and developers also is a must. Choose intelligent tools with a proven ability to solve a business problem internally or for a customer or business partner.
Having identified areas of your operation where AI and ML can help you solve a problem and capture new value, try solutions from multiple providers. Some may be general in application, others tailored to a specific vertical use case. The possibilities are many, and they’re increasing rapidly as these models continue to learn.
AI in wholesale distribution: 4 use cases
Distributors are putting AI to work in a variety of ways to streamline processes, increase efficiency, and improve customer experience. Here are some examples of AI in distribution:- Optimize pricing. One critical area where wholesale distributors can put AI to work today is in optimizing pricing. With its ability to quickly and deeply analyze a wide range of customer and operational data, AI can produce highly segmented pricing recommendations that increase revenue and margin.
- Improve logistics. Those optimization capabilities extend to logistics, where AI can recommend optimal delivery routes taking into account changing parameters and priorities related to the customer, the product, the route and the vehicle/driver. The benefits in terms of customer and driver satisfaction, as well as fuel efficiency and emission-reduction, can be substantial.
- Personalize customer experience and accelerate service delivery. As generative AI apps grow more powerful, chatbots become more viable for automating and enhancing the customer journey, with the ability to make intelligent product recommendations and resolve more complex customer inquiries than in the past.
- Workforce management. As much as labor shortages hamper areas like fulfillment, distributors are using AI-driven robots and cobots (collaborative robots) to help fill the labor void in the warehouse. AI-driven tools can automate processes, and also can simplify and even eliminate process steps via intelligent process analysis. Essentially, in a labor-constrained industry like ours, it’s about doing less (as in fewer process steps) with less (labor) by, for example, automatically converting emailed orders into digital transactions.
Additional AI opportunities for distributor growth
Once you’re comfortable with use cases like these, then you can explore more transformative possibilities with AI, such in preventing customer loss. By analyzing customer buying patterns and behavior, it can alert sales reps to customers they’re at higher risk of losing and recommend the best counter (price, promotion, rebate, service adjustment, etc.).
For example. AI’s predictive powers can help a wholesale distributor identify and configure new value-added services to maximize their profitability to the provider and the appeal to customers. AI could, for instance, suggest how to configure and price a warehouse robot-by-subscription service that includes the robot (fully maintained on a turnkey basis), the intelligent software to operate it, plus analytics of the data it collects.
Bringing AI into your distribution operation not only will help you create new value for your company and its customers, it will give your people new tools to do their jobs better. Because when it comes to the working relationship between human beings and intelligent technologies, as the adage goes, “It’s a duet, not a duel.”