Optimising customer lifetime value: A competitive strategy for specialised wholesalers
Every company is made up of countless logical decisions. And these decisions are rational, aren’t they?
Every successful managing director or sales manager of a component manufacturer or specialized wholesaler should know how valuable their customers are. Depending on their value, you can decide how to invest, prioritize or retain them.
Especially for specialized wholesalers in Germany with a customer base of between 5,000 and 10,000 and a product portfolio of between 20,000 and 100,000 items, the term “customer lifetime value” (CLV) has become a key metric in sales.
This article uncovers the deeper meaning and challenges of CLV. Our aim is to inspire sales managers and managing directors of specialist wholesalers to adjust their prices based on customer behaviour and historical ERP sales data to withstand increasing competitive pressure.
Customer lifetime value: more than just a key figure
A customer’s value cannot be expressed in just one number. But who cares about that? Successful business people still need numbers and indicators to make their decisions.
CLV is a complex key figure that represents the total net value of a customer over the entire duration of the business relationship. This key figure is not easy to calculate as it takes into account various variables such as customer acquisition costs, order values, purchase frequency and customer retention rate. Why is CLV so important?
Interestingly, acquiring a new customer can be up to five times more expensive than maintaining an existing customer. Or was it seven times more expensive? No matter. Understanding and optimizing CLV is, therefore, essential for specialist wholesalers. This will enable them to maximize the profitability of their customer relationships and make informed decisions about marketing and sales strategies.
Challenges in calculating the customer lifetime value
Calculating CLV is challenging because it requires a long-term perspective and a precise analysis of customer behaviour. To summarise, most of the customer benefit still lies in the future.
One of the most considerable difficulties is accurately predicting future customer behaviour and spending. This requires a deep analysis of historical data and an understanding of how various factors, such as customer service, product quality, and pricing, influence customer loyalty.
A study by Bain & Company shows that an increase in customer loyalty of just 5% can increase profits by more than 25 %.
A price increase of 1% can increase profits by 10 to 20%. That underlines the importance of accurately calculating and optimizing the CLV for specialist wholesalers.
But here’s a request from me: Do the maths yourself. How valuable are your customers?
How differently valuable are they? What would halving the churn rate mean for you? More cross-selling or more price?
Strategies for optimizing customer lifetime value
To maximize overall customer lifetime value (CLV), specialist wholesalers need to develop strategies for acquiring new customers and maintaining existing customer relationships. One approach could be personalized sales campaigns based on customers’ specific needs and purchasing behaviour.
Another important aspect is pricing, which should be adjusted based on customer behaviour and historical ERP sales data. And if you sell thousands of products, there is no way around AI-supported product recommendations.
AI-supported analysis tools can play a decisive role here by providing precise forecasts and recommendations. These tools enable specialist wholesalers to better understand their customers, respond to them individually, and thereby increase CLV. Successful companies use AI to optimize sales.
In summary, wholesale companies can take three valuable measures to increase CLV:
1) Cross-sell or up-sell recommendations: Give out recommendations to your customers on which of your products could still fit their interests.
2) Targeted customer retention measures: Identify customers with a high risk of churn in good time. This allows your sales team to act in good time and initiate targeted, personalized measures.
3) Dynamic pricing: Include the price acceptance probability of your customers in your price calculations. You will be more successful this way than with the watering can principle!
AI-based predictive sales software can support you with all of these measures and make corresponding data-based recommendations to your sales teams.
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Conclusion: The path to a profitable future
Customer Lifetime Value (CLV) is more than just a metric; it reflects the relationship between your business and your customers. An effective strategy to maximize CLV can help differentiate your wholesale business from the competition and make it successful in the long term. It’s not just about numbers; it’s about creating sustainable value for your business and your customers.
Would you like to learn more about maximizing CLV in your specialist wholesale business? Download our detailed whitepaper or contact us for a personalized consultation. Let’s work together to strengthen your sales and deepen your customer relationships.
