Part 1: Customer Life Cycle &#8211; A Misleading Term
CYCLE: noun: A series of events that are regularly repeated in the same order. The above is how the term “cycle” is defined by the Oxford Dictionary. In the biological arena, cycle is defined as: “A recurring series of events or metabolic processes in the lifetime of a plant or animal.” The key phrase in the definition is repeated or recurring events. So, when we refer to the term cycle, we mean repeating activities. But when one uses the phrase Customer Life Cycle, the reference is to the stages in the customer life. So examples of customer life cycle speaks of birth, earning, marriage, children, retirement and so on. Companies try to build customer life cycle models across the life of the customer. This is where the flaw exists. The life of the customer is a irreversible process. A stage once achieved is not entered again. A customer only moves to the next stage at a future point of time. This is not a typcial definition of the cycle. A cycle could be a set of repeating activities in a particular stage of the customers’ life. For example, during his working years, the regular credit of salary in his account at the end of the month could be termed as a cycle of events. Customer Life Cycle modelling should aim at analysing these repeating events. Each stage will have one or more such repeatable events or cycles. However, these cyclical events are not interdependent or sequential. They are good on their own or as a stand alone event. Business owners try to define a customer life cycle by stringing these events together. This is where the exercise fails. Because, these events are not milestones on the customer life. They form or constituent or define stages in the customer lifetime. This brings us to the term Customer Life Stage. The term Customer Life Stage can be defined as the series of stages that a customer achieves throughout his life time. The next few articles will focus on developing the Customer Life Stage model. The first step is to define the Customer Life Stage. The most common example of a life stage is birth, infancy, student, youth, marriage, children, retirement, death. But this just forms one dimension of the life stage definiton. There are many more dimensions along with life stages can be identified. Thus, a true customer life stage would be a multi-dimensional structure identifying the stages across various dimensions. A customer life stage can be defined across the following dimensions. I have also stated sample values for some dimensions. 1. Human Dimension: Birth, Childhood, Student, Youth, Active Life, Maturity, Seniority, Death 2. Product Dimension: Introduction, Growth, Maturity, Decline 3. Market Dimension: Innovators, Early Adopters, Early Majority, Late Majority, Laggards 4. Decision Dimension: Knowledge, Persuasion, Decision – Accept, Decision – Reject, Implementation, Confirmation Other business specific dimension could be: 5. Product Holding 6. Product Value 7. Customer Vintage 8. Calendar In the next article we will look at defining a customer life stage landscape using the above dimensions.
CYCLE: noun: A series of events that are regularly repeated in the same order. The above is how the term “cycle” is defined by the Oxford Dictionary. In the biological arena, cycle is defined as: “A recurring series of events or metabolic processes in the lifetime of a plant or animal.” The key phrase in […]
CYCLE: noun: A series of events that are regularly repeated in the same order. The above is how the term "cycle" is defined by the Oxford Dictionary. In
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Feroz has close to two decades of experience in customer relationship management. He has consulted businesses across the globe in their CRM strategy and processes. He was instrumental in setting up the Customer Intelligence practice for SAS India, the leader in analytics. He loves experimenting with adoption of practices and principles from fields such as theology, philosophy, mythology to the statistical processes. His strong belief in the "keep it simple, stupid" paradigm has helped his customers gain benefits from adopting analytics in a comfortable and controlled manner. He is a graduate in Statistics and a MBA in Marketing.