In order to market a product or service on digital platforms in a truly profitable way, it is important to consider not only the customer acquisition costs, but also the customer lifetime value, i.e. specifically: to focus on the actual margin over the course of the entire customer relationship. This means that marketing investments can no longer be viewed purely as a cost item, but their contribution to the company's success can be recognised. In marketing circles, this principle has recently come to be known as "margin-based marketing". In the following blog post, you can find out exactly what this means, how it works and what is "new" about it.
The margin-based marketing approach (MBM for short) has its origins in B2C business. This is because B2C marketing is much more competitive due to greater competitive pressure, which forces marketing managers to constantly search for optimised solutions and approaches - including MBM.
In "traditional" marketing, the focus is particularly on the costs incurred for acquiring a customer or a conversion. Customer acquisition costs (CAC) show how much money is spent on marketing measures, salaries and other services in order to acquire a customer. From a marketing perspective, the main focus is therefore usually on the question of how to minimise or reduce these costs. The problem here, however, is that digital advertising channels auction off advertising space. As a result, campaigns become more and more expensive as competition increases and the CAC rises steadily. (no matter how well they are designed and implemented). In order to optimise marketing, you should not only focus on the cost side. A different approach is needed to recognise further potential.
CAC in relation to CLV
In view of the increasingly rising costs of customer acquisition, another parameter must be found that puts these in a meaningful relation. A look at your own customer data helps to gain insights into the "most relevant" and "best" customers - i.e. customers with a high Customer Lifetime Value (LTV/CLV). Customer lifetime value refers to the value of what a customer realises for a company in terms of revenue over their lifetime. Basically, it represents the amount of money that an average customer pays before churning.
The recipe for success lies in the relationship between the two metrics CAC and CLV. If the ratio of CLV to CAC is calculated, different values can result that show whether further campaigns make sense or whether the "marketing burn" is too high - MBM is therefore defined as the practice of optimally allocating marketing capital in order to maximise profit or achieve a target profit margin:
Which customers should be addressed in communication?
The answer lies in a well-maintained customer relationship management system (CRM) with sufficient historical data. This contains specific information about the purchasing behaviour of all customers. It is important to be able to calculate average CLV values, but also to evaluate more specific questions and identify concrete customer clusters: Which customers initially buy expensive products but then ensure little future revenue? Which customers initially buy medium-priced items, but stay longer and generate more revenue over time? Which customers initially buy the cheapest product, but then become loyal fans and ultimately become the most profitable customers? These insights are important in order to calculate the profitability of all customers, but also of specific customers, and to derive options for action for marketing.
This analysis usually also reveals that existing customers often offer the greatest potential. A customer who has already made a purchase is much easier to persuade to buy again than to acquire new customers. There is also the advantage that direct contact means there are no high platform costs for campaigns. Marketing automation and communication with existing customers therefore pay off twice over and should ideally be linked directly to the CRM system.
One expansion stage of this is primarily used in large accounts. This involves additional data being added on the basis of customer information. With the help of third-party data and AI tools, existing information can be enriched to create better target groups in the top of funnel. As these are based on the customers with the best CLV, they have a higher potential than audiences that are formed using socio-demographic and interest-based criteria alone. It is important to note that a very large data pool must be available so that AI tools can achieve their full effect.
What can the B2B business learn from this?
Compared to B2C business, this optimisation potential has not yet been fully exploited in B2B business. This is mainly due to the fact that, on the one hand, the data source is smaller and, on the other hand, the competitive pressure in the digital environment is not yet as high as in B2C segments. Nevertheless, there are currently a few companies such as SaaS that are already actively utilising the MBM approach.
Looking at the identified parameters, it can be deduced that the CLV in the B2B sector is much higher than that in the B2C business. When attempting to determine CAC or CLV specifically, many fail due to a lack of overarching understanding of marketing, sales and customer management, as well as a lack of systems that cover and link these dimensions. After all, customer acquisition has always worked well in the past via traditional sales channels such as trade fairs or customer visits.
Of course, highly professionalised MBM can usually be safely neglected in B2B business, as there is often less customer data, less third-party data is available and AI therefore leads to less meaningful results. However, this does not mean that the basic principle behind MBM is not relevant. It is important to be aware of the two metrics CAC and CLV, to know their optimal ratio and to act according to the MBM principles. Especially in relationship-intensive and comprehensible B2B marketing, the values are often significantly higher than the 3:1 ratio of CLV and CAC.
