Wholesale as a Success Factor: Modern Customer Relationship Management
Wholesale distribution plays a critical role in the modern economy, linking manufacturers and retailers.
Successfully capturing markets and retaining customers is, therefore, central to the growth and stability of a wholesale business. Although the market is highly competitive, there are innovative strategies that companies can use to capture markets and retain customers for the long term.
This article focuses on the key factors that have become essential to success in wholesale distribution, such as well-managed customer relationship management, its importance and what it entails.
It answers why modern customer relationship management is necessary, what systems and alternatives midsize wholesalers need, and why implementing an entirely new CRM system can disadvantage midsize wholesalers.
In addition to the well-known pricing strategies, you will also learn about the role of predictive analytics in pricing, especially for mid-sized wholesalers, why these companies can also reduce their churn rate through predictive analytics, and why AI is necessary.
Customer Relationship Management – What is it?
Customer Relationship Management is a strategic approach to improving a company’s and its customers’ relationship. It involves using technology and data to collect, analyze, and use customer information to provide personalized and tailored experiences.
Customer relationship management – CRM systems
An effective CRM (Customer Relationship Management) system enables organizations to understand their customers better, anticipate their needs and preferences, and offer relevant products or services. Companies can develop targeted marketing campaigns and build customer loyalty by leveraging customer data. A well-implemented CRM system can help companies build long-term, profitable customer relationships and provide intensive customer care.
It is important to note that a system like CRM is not just a software solution but a holistic strategy encompassing all aspects of customer interaction. It requires close collaboration between sales, marketing and customer service departments to ensure a seamless customer experience.
On the one hand, a well-implemented CRM system can provide many benefits. It can increase efficiency by automating the sales process and improving employee productivity. It can also enhance customer satisfaction by enabling personalized communications and handling customer inquiries quickly and effectively.
On the other hand, it should be noted that CRM is not a silver bullet, and its effectiveness depends on careful planning and implementation, as well as continuous monitoring and adjustment to ensure that it meets customers’ changing needs and expectations.
In addition, it is not always necessary to implement an entirely new CRM system, which is especially important for midsize distributors to know. New CRM projects usually take much longer than planned and always cost more than budgeted. The longer a project takes, the higher the risks. Depending on the complexity, replacing a CRM in a mid-market company can take anywhere from a month to a year. There are many disappointed customers of CRM vendors because they were promised a lot, and the reality is very different. Many companies buy programs without clear and measurable expectations. So, what is the alternative to a whole new CRM project?
Analysis and Forecasting Software (Predictive Sales Software) for medium-sized Wholesale Companies.
Analysis and forecasting software, such as predictive sales software, uses data from existing ERP and CRM programmes to gain valuable insights. Such software supports profitable growth.
Predictive sales software offers a shorter time-to-value (amortization time). Its implementation requires significantly shorter cycles than implementing an entirely new CRM. Predictive Sales Software is like taking an elevator. Planning and implementing CRM software is more like climbing Mount Everest because ¾ of all implementations of new CRM systems fail due to the enormous amount of work involved. Management should carefully consider investing in a completely new CRM system or alternative software tools to reduce costs and increase revenue. Predictive Sales is a forward-looking software. It includes cross-selling, churn, and pricing analytics across traditional and digital channels. Let’s take a closer look at two critical aspects.
1. Price Management – Dynamic Pricing
Pricing and terms and conditions are critical to a company’s success. Different strategies can help determine the optimal price for products or services while promoting customer loyalty and profitability.
One “well-known” strategy is the market-based pricing strategy.
Market-based pricing is based on the prices of products in the marketplace. You observe what other vendors charge for their products and then set your price higher, lower, or at the same price as the competition. That depends on the quality of your product and how it compares to the competition.
Dynamic Pricing and the Use of Predictive Analytics
In addition to these well-known strategies, there are also AI systems for pricing. Dynamic pricing is a strategy that companies use to adapt their selling prices to current market conditions.
In today’s data-rich world, dynamic pricing refers to the immediate adjustment of prices as new information (in the form of new data) emerges. Many methods and technologies are available for this purpose.
In particular, algorithms based on machine learning (a branch of artificial intelligence) significantly increase the performance of price optimization. The most advanced pricing solutions predict the impact of price changes before they take effect.
Successful wholesalers such as Sonepar have adapted their pricing. They use powerful and expensive business intelligence programs to generate automatic price recommendations per customer and product. These price recommendations are based on individual customer behaviour or the customer’s situation. Of course, the previous pricing strategies are not thrown overboard, but the customer-specific recommendations are also considered.
For example, a manufacturer’s price increase is not passed on 1:1 to all customers but targets those most likely to accept it. Wholesalers that move to AI-driven pricing solutions have been shown to achieve higher profits and outperform their competitors.
But how can mid-market wholesalers and B2B companies keep up?
Is dynamic pricing even financially viable for mid-market wholesalers? Yes, high-quality, affordable alternatives exist, such as standardized AIbased sales forecasting software like Qymatix. The software-as-a-service provides a price range for each customer and product most likely to be accepted. The forecasts are based on historical sales data. That makes pricing inconsistencies visible and gives the sales team an additional basis for pricing decisions. Historical sales data also shows customers’ past buying behaviour. These are all transactions that customers have already agreed to. That allows the AI algorithms to find similarities between customers and their buying behaviour and predict price ranges for each product.
That means there is no need for valuable IT specialists to use such a tool, as the opportunities are sent directly to the sales department. Thanks to predictive sales software vendors, artificial intelligence for dynamic pricing is now affordable for mid-market wholesalers.
2. Customer Loyalty – Churn Forecasts with Predictive Analytics
Retaining loyal customers and actively preventing customer churn are two of the most important tasks of a wholesaler because loyalty takes years!
Nobody builds loyalty overnight. It has been proven for some time that retaining existing customers and preventing them from churning is far more effective, efficient and cheaper than spending all your energy on acquiring new customers.
Surprisingly, customer loyalty studies have shown that the company with a loyalty strategy and its customers are often better off with lower churn rates. The financial benefits of a B2B loyalty program come from suppliers and buyers rewarding each other’s trust.
Customer Loyalty Programs – Churn Prediction Software.
Predictive sales analytics can predict which customers are likely to churn because the key to retaining customers is to act before they churn – not after they churn.
Successful sales teams use churn prediction software. When key account managers identify a customer at high churn risk, they deploy such programs.
And once you have operationalized churn prediction, you can develop a dedicated B2B loyalty program. Building customer loyalty means treating customers with loyalty, respect, and the right level of priority. A successful B2B loyalty program makes each customer feel special while employing a range of dedicated retention activities. Any good loyalty analytics software is only the beginning of a successful B2B loyalty program.
CALCULATE NOW THE ROI OF QYMATIX PREDICTIVE SALES SOFTWARE
Wholesale as a Success Factor: Modern Customer Relationship Management – Conclusion
Forecasting and analysis programs such as predictive analytics, which are easy to fund and relatively quick to implement, can help wholesale companies in many ways. For example, they enable accurate prediction of future trends and demand, leading to improved sales planning. They allow companies to accurately predict future trends and demand, leading to enhanced sales planning and the ability to identify sales patterns and customer preferences better to target marketing and sales strategies.
Efficient wholesale distribution without automation and modern digital technologies is no longer competitive. Conquering markets and retaining customers requires a comprehensive strategy based on clear principles and continuous adaptation. That is why forecasting and analysis programs such as predictive analytics are appropriate for wholesalers in today’s retail world.
I WANT PREDICTIVE ANALYTICS FOR B2B SALES.
Further Read:
Thomas Johne(2011): Customer loyalty through customer orientation
Svenja Szillat(2022): Is Dynamic Pricing Optimization in B2B Wholesale Financeable?
