Management
Accounting
Performance
Management
Measuring
Customer Performance
Introduction
Individuals in the United States, on average, hold 16.6 loyalty program
memberships of which 7.6 are actively utilized. This underscores the importance
of customer relationship management and the attention businesses devote to such
programs. This focus arises from the pursuit of a sustainable competitive
advantage, prompting companies to differentiate their product offerings by
emphasizing customer engagement and enhancing communication. Companies
continually seek strategies to improve the customer experience, such as
providing better product and service quality.
However, the challenge lies in the fact that a satisfied and loyal
customer, who repeatedly purchases a company’s products, does not necessarily
translate into increased profits. Thus, strategies aimed at improving customer
loyalty do not inherently lead to higher profitability.
Both measuring the improvements in quality and the profits from
different customers or customer groups require performance measurement
techniques. In this article, we will focus on the aspect of customer
profitability and how customer profitability analysis, such as customer
lifetime value, can guide companies in their customer loyalty efforts.
Profitability
Analysis
In this section, we will introduce the idea and concept of the customer
profitability analysis (CPA). A customer profitability analysis is an
evaluation process which focuses on assigning costs and revenues to segments of
the customer base, instead of assigning revenues and costs to the actual
products, or the units or departments which compose the corporate structure of
the producer. The term “profitability” is often understood in terms of a
percentage, while “customer profitability” usually describes the absolute
profit made from a customer.
Approaching profitability from this angle can sometimes provide valuable
insights into how each step of the process of designing, manufacturing, and
ultimately selling goods or services incurs cost and generates revenue. Many
businesses use a customer profitability analysis as a means of streamlining
processes to provide the highest degree of efficiency and return while
generating the lowest degree of cost.
In general, customer profitability analysis can help companies to make
better decisions in the following areas:
a)
Customer
dependency
b)
Balance
between customer retention and customer acquisition activities
c)
Payback
period to customer acquisition
|
Pareto
principle The Pareto principle is a general rule of thumb which
states that for many outcomes roughly 80% of consequences come from 20% of
causes. In other words, a small percentage of causes have an outsized effect. |
Customer
dependency
A customer profitability analysis can also help to identify factors
which could have a negative impact on the future of the company. For example,
customer profitability analysis allows determining what percentage of revenue
is generated from a given customer or group of customers. There are cases when
analysis makes it clear that the company depends on two or three large
customers to generate half or more of its business volume. With that type of
information, steps can be taken to diversify and expand the client base, often
by attracting more small- to mid-sized customers. As a result, the business is
less likely to be at risk should one of those major clients decide to withdraw,
since an increased bank of smaller customers (who are less likely to opt out of
the business relation) account for a larger share of revenue.
Balancing
customer acquisition and retention
Quoting the so-called Pareto principle, it is often assumed as a rule of thumb that 80% of profits are
generated by 20% of customers, while only 20% of profits come from 80% of the
customers. While this may seem intuitive, it remains a purely theoretical
concept, as it assumes that each customer generates a small amount of profit.
In reality, a proportion of customers are unprofitable, meaning they are not
contributing a small profit but a loss instead. Gaining more of such unprofitable
relationships will ultimately reduce the total profit of the company. Knowing
which customers are not profitable based on a customer profitability analysis
can be a very useful tool in selecting the right customer relationships that
should be terminated and the ones that should be expanded. Loyalty campaigns
and other marketing activities can be aimed at the appropriate customers
instead of spending marketing dollars on unprofitable customer relationships.
Payback
period to customer acquisition
Because of various factors, such as costs for sales and market, a new
customer is rarely profitable from day one. That is why the payback period of a new customer
relationship is defined as “the length of time (usually measured in months)
that a newly acquired customer starts to become profitable”.
The payback period can be very long in some industries or for complex
business-to-business transactions. In some cases, it can even exceed the entire
annual revenue from a customer relationship. If payback periods tend to be
long, this can have a significant impact on the cash flow of a company, as it
has huge initial outlays with limited or no revenue for some time. An
understanding of customer profitability analysis can assist in finding the right
balance between acquiring new customers and retaining existing ones. It can
also explain why some customer relationships may not be profitable. This issue
arises when excessive emphasis is placed on acquiring new customers rather than
maintaining existing relationships, at least until the payback period is
surpassed.
After discussing how customer profitability analysis can assist
companies in making better decisions, we will next consider the basic method
for calculating customer profitability for an individual customer or customer
segment using the following formula:
|
Customer profitability = |
|
customer revenue – (cost of
goods sold + costs to serve + customer-specific overheads) |
More specifically, the customer profitability (CP) in a year or a certain
period t equals
the revenues obtained from that customer (CR) during that time less the total
customer-specific costs. The total
customer-specific costs are made up of three types of costs: the cost of goods
sold (COGS), the costs to serve (CTS), and the customer-specific overheads
(CSO). COGS include direct product costs and/or the costs of
delivering a service. CTS typically include costs for sales, marketing,
customer service, and customer management costs. Examples for CSO are the cost
of providing a dedicated warehousing space for a customer. CSO are usually only
incurred for large customers or when considering customer segments rather than
individual customers. The described approach can be summarized as follows when
calculating the customer profitability for a specific period t:
|
CPt = |
CRt – (COGSt
+ CTSt + CSOt) |
Let us illustrate the calculation based on an example, assuming there
are two customer segments, A and B. At a high-level segment A appears to be
less attractive than segment B, with an average revenue per transaction of $150
for segment A compared to $200 for segment B. Let us, however, assume that
customers from segment B have special fulfilment requests which are double the
cost in labour and fulfilment fees than for segment A as shown in the following
table:
|
|
Segment A |
Segment B |
|
Labour, fulfilment, and restocks |
$24 |
$50 |
|
Shipping costs |
$20 |
$60 |
|
Customer service costs, marketing |
$12 |
$24 |
With this information, we can calculate the customer profitability as
follows:
|
|
Segment A |
Segment B |
|
Average revenue per transaction |
$150 |
$200 |
|
Customer revenue
(CR) |
$150 |
$200 |
|
Labour, fulfilment, and restocks |
$24 |
$50 |
|
Shipping costs |
$20 |
$60 |
|
Costs of goods
sold (COGS) |
$44 |
$110 |
|
Customer service costs, marketing |
$12 |
$24 |
|
Costs to serve
(CTS) |
$12 |
$24 |
|
Customer
profitability (CP) [CR – (COGS +
CTS)] |
$94 |
$66 |
After conducting a customer profitability analysis, it turns out that
segment A is actually more profitable than segment B.
The most difficult challenge in the calculation is how the individual components
can be derived from accounting-based information. A tool often used to allocate
revenues and costs to customers is Activity-based
Costing (ABC). The success of any customer profitability
analysis hinges on the capabilities of the underlying ABC calculations.
Briefly, ABC consists of the following four steps:
1.
Identify activities: The first step involves identifying all the activities involved in
producing a product or providing a service.
2.
Assign costs to activities: Next, the costs associated with each activity are determined. This
includes both direct costs, such as materials specific to an activity, and indirect
costs, such as overhead costs.
3.
Determine cost drivers: Cost drivers are the factors that cause costs to be incurred in an
activity. For example, the number of setups, machine hours, or time spent on a specific
service can be cost drivers for various activities.
4.
Allocate costs to products/services: Once the cost drivers are identified, costs are allocated to products
or services based on their consumption of the activities. This provides a more
accurate picture of the resources consumed by each product or service.
With that approach, ABC differs from traditional costing models that
typically group costs in specific accounts, but do not allocate these based on
the activity that causes the costs. The following table provides a more
comprehensive comparison between ABC and traditional costing methodologies.
Comparison of ABC and Traditional Costing
|
|
ABC |
Traditional Costing |
|
Cost Pools |
ABC systems accumulate costs into activity cost
pools. These are designed to correspond to the major activities or business
processes. By design, the costs in each cost pool are largely caused by a
single factor – the cost driver. |
Traditional costing systems accumulate costs into
facility-wide or departmental cost pools. The costs in each cost pool are
heterogeneous – they are costs of many major processes and generally are not
caused by a single factor. |
|
Allocation Bases |
ABC systems allocate costs to products, services,
and other cost objects from the activity cost pools, using allocation bases corresponding
to cost drivers of activity costs. |
Traditional systems allocate costs to products using
volume-based allocation bases. |
|
Hierarchy of Costs |
Allows for nonlinearity of costs within the
organization by explicitly recognizing that some costs are not caused by the
number of units produced. |
Generally estimates all the costs of an organization
as being driven by the volume of product or service delivered. |
|
Cost Objects |
Focuses on estimating the costs of many cost objects
of interest: units, batches, product lines, business processes, customers,
and suppliers. |
Focuses on estimating the cost of a single cost
object—unit of product or service. |
|
Decision Support |
Because of the ability to align allocation bases
with cost drivers, it provides more accurate information to support
managerial decisions. |
Because of the inability to align allocation bases
with cost drivers, it leads to over-costing and under-costing problems. |
|
Cost Control |
By providing summary costs of organizational
activities, ABC allows for prioritization of cost management efforts. |
Cost control is viewed as a departmental exercise
rather than a cross-functional effort. |
|
Cost |
Relatively expensive to implement and maintain. |
Inexpensive to implement and maintain. |
|
Granularity
of calculation When performing a customer profitability analysis, calculations
can either be done on the level of individual customers or an aggregate of customers.
This is referred to as the granualarity (the quality of including a lot of small
details) of the calculation or the analysis. |
While it has many advantages, the biggest downside of ABC is that it is
a time- and resource-consuming exercise. Since customer profitability analysis
is usually based on ABC, it also makes it a long and arduous exercise. Because
of its complexity, it is suggested to determine the level of required granularity as the first step of a customer profitability analysis. The highest
level of granularity is the calculation based on individual customers, and the
lowest level of granularity is the consideration of the entire customer base of
the company. While a high level of granularity may sound advantageous, it has
to be considered that this will not only result in high expenses of obtaining
this information, it can also get into the way of looking at the bigger
picture. If, however, the level of granularity is too low, the results will
likely be insufficient and not allow drawing meaningful conclusions from them.
To find the right balance and level of granularity, companies will need to
consider factors such as the nature of their business, their customer base,
customer types as well as the targets and objectives of the customer profitability
analysis.
To make the customer profitability analysis meaningful, a six-step
approach for implementation, as shown in the figure below, may be adopted.
A
Six-step Approach for Effective CPA Implementation
From a practical perspective, the team carrying out the analysis part
should consist of at least a marketeer and a management accountant, but can
also contain operations managers and information specialists.
If implemented properly, customer profitability analysis will enable
managers to understand and answer the following questions:
a)
Which
customers are the most and least profitable ones?
b)
How
dependent is the company on the most profitable customers?
c)
What are
the costs involved to serve the customers, and how are resources allocated to different
customers?
Based on the insights gained from the customer profitability analysis,
managers can develop strategies with the goal to maximize revenue from the most
profitable customers or how the company should deal with low profitable or even
loss-making customers. Depending on the level of data available, it might even
be possible to simulate the consequences of reducing services and increased
marketing activities.
We will conclude this section with a visual (the whale curve) that has
sometimes been called “the single best picture from an ABC model” that can also
be used in customer profitability analysis.
Cumulative
Customer Profitability (Whale Curve)
The whale curve ranks customers from the most profitable to the least
profitable on the horizontal axis. The vertical axis displays the cumulative
profitability of the customers. It is often assumed in practice that sales
follow the Pareto 20–80 rule, meaning that 20% of customers provide 80% of the
total sales. The whale curve violates the Pareto rule. Often, 20% of customers account
for 150 to 300% of total profits. The middle 70% break even and the least
profitable 10% of customers can lose anywhere from 50 to 200% of total profits,
explaining combined 100% of the company’s total profits. Identifying which
customers are in which group can be extremely valuable in tapping into
unrealized profit potential.
Customer
Lifetime Value
While the customer profitability Analysis (CPA) gives a comprehensive overview
of how profitable a customer relationship was in the past, it does not provide
any forward-looking guidance. There is no guarantee that the same customers or
customer segments will achieve the same results in the future. That is the
starting point for the customer lifetime value (CLV) analysis, which is
designed to address the following simple, but complex question: What is the
value of a customer? Customer lifetime value (CLV) in this context may be defined
as “the sum of cumulated cash flows – discounted using weighted average cost of
capital (WACC) – of a customer over his or her life-time within the company”.
With the view on cash flows generated from a customer relationship, the
customer lifetime Value indicates the future profitability of a customer. That
makes it a prospective customer profitability measure, whereas the customer
profitability analysis discussed is a retrospective measure. Additionally, the
customer lifetime value focuses on results and the profitability over several
periods. Also, it is based on the economic concept of profit (net present value
of future cash flows) in contrast to the customer profitability analysis, which
is based on the accounting concept. The accounting concept is more designed for
reporting purposes and not so much for decision support. In the light of this,
it can be said that the customer lifetime value is the “best metric to manage
customers profitably” and future investment decisions. That does not mean customer
lifetime value should be the only tool to be used. Customer profitability as
illustrated in the previous section is still valuable from an analytical point
of view, as long as its limitations are considered.
Different approaches exist to calculate the customer lifetime value. In
its simplest form, it can be calculated using the following equation for a specific
customer:
|
CLV = |
∑(t
= 1 to T)CMit{1 ÷ (1 + d)}^t |
Where,
|
CLV = |
Customer Lifetime Value |
|
CM = |
Contribution Margin |
|
T = |
Specific period for which CLV is measured for an
individual customer |
|
i = |
Customer Index |
|
t = |
Time period of a particular contribution margin from
the customer |
|
d = |
Discount Rate |
In this formula, CM is the contribution margin or contribution of
customer A, and CLV is the lifetime value of customer A measured for a specific
periods T. The contribution of customer A is the contribution margin (CM) from customer
A in future time period t and d is the discount rate. Typically, the weighted
average cost of capital (WACC) is used to determine the discount rate. The WACC
is typically defined in its basic form as:
|
k
= |
kE{VE
÷ (VD + VE)} + kD(1 – TC){VD
÷ (VD + VE)} |
Where,
|
k = |
Weighted average cost of capital (WACC) |
|
kE = |
Cost of equity |
|
kD = |
Cost of debt |
|
VE = |
Market value of the firm’s equity |
|
VD = |
Market value of the firm’s debt |
|
TC = |
Corporate tax rate |
In
this formula, VE is the market value of the firm’s equity, VD
the market value of the firm’s debt, kE the cost of equity and kD
the cost of debt. TC is the corporate tax rate to account for the fact
that interest on debt capital reduces the tax on profits.
As mentioned, the formula above is the most basic definition of the
customer lifetime Value. A more systematic approach to the CLV measurement is
schematically shown in the figure below.
An
Approach to CLV Measurement
|
Acquisition
costs While the customer life value calculation does
typically include acquisition costs, there are also sources that argue that
these costs should not be included in the calculation. |
This approach expands the basic formula by providing a more detailed
explanation to the calculation of the “contribution of customer” component,
which is the “net margin” in this scheme. It consists of the recurring revenues
minus the recurring costs reduced by the marketing costs. The net margin is
then calculated over the next three years, but could also be calculated for a
longer period to get to the sum or accumulated margin. The proposed calculation
should better be limited to 3 years, since this often reflects the product lifecycle,
customer lifecycle and assumes that 80% of profit can be realized in the first three
years of a customer relationship. Additionally, acquisition
costs can also be introduced to the calculation, since often there are costs involved in gaining and
setting up a new customer relationship.
While the basic formula of the CLV measurement focuses on an individual
relationship, another approach looks at the aggregate of a group, segment, or
cohort (a group of people who share a characteristic, usually age) of
customers. In one approach, this leads to the calculation of what is called the
customer equity (CE) and is defined as follows:
|
CE
= |
∑(i
= 1 to I)∑(t = 1 to T)CMit{1 ÷ (1 + d)}^t |
Where,
|
CE = |
Customer Equity |
|
CM = |
Contribution Margin |
|
T = |
Specific period for which CLV is measured for an
individual customer |
|
i = |
Customer Index |
|
I = |
Number of customers in the group |
|
t = |
Time period of a particular contribution margin from
the customer |
|
d = |
Discount Rate |
It is the aggregate of the individual Customer Lifetime Values with i
being the customer index.
In another approach, the average CLV of a customer is based on the lifetime
value of a customer segment or a cohort (a group of people who share a
characteristic, usually age) as follows (Kumar, 2008):
Average
CLV of a customer
|
Average CLV = |
∑(t
= 1 to T)[CMt{1 ÷ (1 + d)}^t(r^t)] − A |
Where,
|
CLV = |
Customer Lifetime Value |
|
CM = |
Contribution Margin |
|
T = |
Specific period for which CLV is measured for an
individual customer |
|
t = |
Time period of a particular contribution margin from
the customer |
|
d = |
Discount Rate |
|
r = |
Rate of retention |
|
A |
The average acquisition cost per customer |
This formula introduces the following two new elements: A, which is the average acquisition cost per customer, and r the rate of retention. CM reflects
the average gross contribution margin per customer in time period t. The rate of retention is a factor that expresses as a percentage term
the number of customers who stay with the company from one period to the next.
In this formula, the rate of retention is assumed to be static over the periods
considered, but in reality may change over time. This is because customers may
choose to discontinue their relationship at different times.
Case
Study of Customer Lifetime Value Calculation
To illustrate the customer lifetime value calculation, let us consider
the following simple case study. The company Brand New Limited plans to extend
its services to a new customer segment based on the following data:
1.
The
planning horizon is three years. It is expected to gain 20,000 new customers with
the service provided.
2.
The
expected rate of retention is 70%.
3.
Moreover,
it is expected that the customers make 1.8 orders on average in the first year.
This is expected to increase to 2.6 in year two and 3.6 in year three.
4.
The average
order size in year one is $2,980. In year two it is expected that this increases
to $5,589 and in year three to $9,106.
5.
The direct
costs are available as a percentage of the total revenue. They are 70% in year
one, 65% in year two and 63% in year three.
6.
To win new
customers, the average acquisition costs for marketing and other activities per
customer are $630.
7.
The
weighted average capital costs (WACC) are 13%.
The following table shows the calculation of the customer lifetime value
based on the above information and following the steps of customer lifetime
value calculation.
|
|
Year 1 |
Year 2 |
Year 3 |
|
No. of Orders per year |
1.8 |
2.6 |
3.6 |
|
Average order size |
$2,980 |
$5,589 |
$9,106 |
|
Total revenue |
$5,364 |
$14,531 |
$32,782 |
|
Direct costs percentage |
70% |
65% |
63% |
|
Direct costs (Variable costs) |
$3,755 |
$9,445 |
$20,653 |
|
Contribution margin |
$1,609 |
$5,086 |
$12,129 |
|
Discount rate (WACC) |
13% |
13% |
13% |
|
Discount Factor [1/(1 + WACC)t] |
0.8850 |
0.7831 |
0.6931 |
|
Rate of retention [(r)t] |
0.7 |
0.49 |
0.343 |
|
Annual NPV |
$997 |
$1,952 |
$2,883 |
Average acquisition cost per customer = $630
Therefore,
Average CLV = $997 + $1,952 + $2,883 − $630 = $5,202
Customer Equity (with the assumption of 20,000 customers)
= $5,202 × 20,000 = $10, 40, 40,000
It is important to note that the customer lifetime value calculation is
not a one-off exercise. Parameters and circumstances can change, and that is
why it has to be treated as a dynamic analysis. Three key factors that
influence the lifetime value of a customer are:
1.
Customer
relationship management (CRM)
2.
Customer
circumstances
3.
Actions and
responses of competitors
Each of these three factors is dynamic and change over time, and, as a
result, make the CLV a dynamic metric. Only one of these three factors is under
the control of the company or can be directly influenced by it. Through its
products or services offerings which are part of customer relationship
management, the company can make an impact on the CLV. The two other factors
are external and cannot be directly influenced by the company. Actions of
competitors are beyond its control, and also the customer’s own circumstances
cannot be directly influenced by the company. Since CLV is a prospective or
predictive metric, it is highly dependent on the ability of a company to
accurately forecast revenues, costs, and customer behaviour. The accuracy of
the forecasting of these variables matches the degree of accuracy that can be
expected from the company’s CLV analysis.
One point that is discussed in the literature is whether acquisition
costs for new customers should be included in the CLV calculation or not. Some
sources suggest that the acquisition costs for new customers need to be
considered to obtain an accurate picture of the CLV. They give an example of a
company that had spent millions of dollars to attract new customers, while only
very few customers ended up making low value purchases in the first period, the
period in which the acquisition costs were incurred. Excluding such significant
acquisition costs will distort the CLV calculation and give a positive CLV to
all customers, which is not necessarily true.
Some sources provide a very different interpretation of the acquisition
costs and the CLV. They do not include acquisition costs in the CLV calculations.
Instead, they suggest that the CLV should be understood as the maximum value
the company is willing to pay for the acquisition of the customer, and that
acquisition costs exceeding the CLV indicate that a customer relationship is
unprofitable. Irrespective of the specific way of calculation of the CLV and if
acquisition costs are included or not, it can be concluded that the CLV is a
good managerial decision-making tool that can accomplish the following points:
1.
It can be
used to allocate the company’s limited resources in those existing customer relationships
that bring maximum returns to the company. Additionally, existing customer relationships
can be classified and grouped into key and non-key accounts.
2.
It can help
to identify new individual customers or segments of customers which, based on
their future value, have the highest importance for the company. Based on this knowledge,
a marketing strategy can be developed to attract these potential customers.
We will conclude this section with a comparison of the customer
profitability analysis (CPA) and the customer lifetime value (CLV). Both
concepts have proven to be valuable metrics that can drive companies to a
customer-centric management approach. However, both come with their own
advantages and disadvantages, as well as possible applications. A big advantage
of the Customer Profitability Analysis (CPA) is its generally greater certainty
about the data used, resulting in a higher reliability of the analysis.
While the CLV calculation relies on forecasts and assumptions about the
future, customer profitability Analysis uses historic data that can usually be
obtained from accounting and customer relationship management software. While
this can be seen as an advantage of the customer profitability analysis, it is
also a significant disadvantage, since there is no guarantee that the future
will be like the past, especially when the company operates in a very dynamic
environment. This has sometimes been called the “rear-view mirror problem” of
the customer profitability Analysis. Robust decision-making is about the
future, and that is why “looking out of the front windscreen” is needed and
where the CLV calculation comes into the picture. The CLV calculation tries
exactly that and allows managing a customer relationship much like an asset in
which the company should or should not invest. In other words, the CLV concept
does a better job in estimating the future potential of a customer.
However, accurate forecasting and predictions of the future are very
difficult and uncertain. In addition to their advantages and disadvantages,
both concepts come with a number of pitfalls. One risk of customer
profitability analysis is that managers get carried away with the outcomes of
the customer profitability calculations and decide to either end or reduce the
involvement with customers that have been identified as low or unprofitable. This
can have drastic consequences, especially when these low-value customers cover
a significant portion of fixed costs that may need to be reallocated to other
customers, making them in turn less profitable, starting a downward spiral.
That is why any results from customer profitability should not be implemented
in an overly hasty manner. The CLV does not share this pitfall, but has
challenges of its own. Some sources suggest that one major weakness of CLV is
that indirect effects are not sufficiently considered, which also includes the
effect of word of mouth marketing and the resulting sales. As a result, the CLV
may understate the “true” value of a customer relationship.
In summary, it can be said that both customer profitability analysis and
customer lifetime value are both valuable tools. The customer profitability
analysis seems to perform better in circumstances where customer behaviour is
predictable and more stable over time. The CLV has its main strength in its
ability to adapt to dynamic environments with high customer churn and unpredictable
behaviour.
Key
Differences between Customer Profitability Analysis (CPA) and Customer Lifetime
Value (CLV)
|
|
CPA |
CLV |
|
Perspective |
Past |
Future |
|
Single-/multi-period |
Single period |
Multi period |
|
Based upon |
Accruals |
Cash flows |
|
Concept of profit |
Accounting profit |
Economic profit |
|
Objective |
Analysis |
Decision support |
|
Market conditions |
Stable |
Dynamic |
|
Important constraint |
Indirect cost allocation |
Forecasting |
Summary
In this article we introduced the concept of customer profitability
analysis (CPA), emphasizing its departure from traditional revenue and cost
allocation methods. Instead of focusing solely on product or departmental profitability,
CPA evaluates the profitability of customer segments. By assessing the absolute
profit derived from individual customers, businesses gain insights into the
efficiency of their processes, enabling streamlined operations and enhanced
returns.
Customer profitability analysis aids decision-making in several key areas.
Firstly,
it helps identify customer dependency, highlighting the risks associated with overreliance
on a few major clients. By diversifying the client base, companies can mitigate
such risks and ensure sustainable revenue streams. Secondly, CPA facilitates the
balance between customer retention and acquisition efforts, challenging the
notion that all customers contribute equally to profitability. By identifying
unprofitable relationships, businesses can allocate resources more effectively,
focusing on high-value customers. Finally, CPA evaluates the payback period for
customer acquisition, recognizing that acquiring new customers often involves
initial costs with delayed profitability.
The calculation of customer profitability involves deducting customer-specific
costs from revenue. These costs encompass expenses related to goods sold,
service delivery, and customer-specific overheads. Through this calculation,
companies gain insights into the profitability of individual customers or
segments.
Activity-based costing (ABC) serves as a vital tool for allocating costs
accurately to customers. ABC involves identifying activities, assigning costs
to these activities, determining cost drivers, and allocating costs to products
or services based on consumption. Contrasting with traditional costing methods,
ABC offers a more nuanced (slightly different) understanding of cost drivers and
resource consumption.
Despite its benefits, ABC is resource-intensive, prompting companies to determine
the appropriate level of granularity for CPA. While detailed analyses provide
valuable insights, they also incur higher costs. Balancing granularity with
practicality ensures meaningful results without overwhelming resource
allocation.
In this article we have also discussed customer lifetime value (CLV)
analysis as a forward-looking complement to CPA. CLV assesses the cumulative
cash flows of a customer over their lifetime, aiding in prospective
profitability assessment. However, CLV calculations rely heavily on forecasting
and assumptions, posing challenges in dynamic environments.
Ultimately, both CPA and CLV offer valuable insights into customer
profitability, each with its advantages and limitations. While CPA provides retrospective
analysis based on historic data, CLV offers a forward-looking perspective,
aiding decision-making in dynamic market conditions.
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