This is the concluding article to the series on Customer Life Stage Model. It is coming after a long time from the last article. Some medical issues in the family had taken me away. Hopefully, things have stabilized for the future.
A quick recap of the articles so far in this series:
Part 1: Introduced the concept of Customer Life Stage Model. http://analyticsindiamag.com/part-1-customer-life-cycle-a-misleading-term/
Part 2: Detailed the steps to define the dimensions for creating the Customer Life Stage model. http://analyticsindiamag.com/part-2-creating-the-customer-life-stage-model/
Part 3: Identified the path customers traverse through their relationship. http://analyticsindiamag.com/part-3-traversing-the-customer-life-stage/
Part 4: Detailed the definition of each cell in the Customer Life Stage. http://analyticsindiamag.com/part-4-detailing-cell/
The Customer Life Stage model plays a key role in the customer relationship management. In the absence of such a model, the visibility of the marketing personnel is just to the next step. A good example is the brief prepared for each campaign. The objective is mentioned as either cross sell, up sell, acquisition or retention. If we apply the “five why’s” test to the campaign framework, almost all of them will fail at the second or third why. So what happens after we cross sell the customer successfully? Very, very few marketing managers will be able to answer this query.
The Customer Life Stage model comes to assist the marketing managers. One can trace the path of a customer across the model right from the moment of customer acquisition. As described in part 4, each cell of the model has a detailed entry and exit criteria. The objective of the marketing manager is to move the customer across the cells as soon as possible to get the customer into the desired cell. If a customer moves into a cell that is not along the preferred path, the marketer can design course correction campaigns and communications. The series of communications or campaigns right from acquisition to getting the customer into the desired cell can be charted out.
We can now draw up a roadmap of communications for each customer segment. Depending on the industry, this roadmap may span anywhere from 6 months to 6 years or even longer.
Home » Part 5: Applying Customer Life Stage model to Customer Relationship Management
A far fetched idea is to organize the consumer marketing based on the Life Stage path. One can see companies having marketing teams managing high value customers. Using the life stage model, the company can define a cell owner. This is useful for critical cells along the path of customer life stage. This team can be responsible for the percentage of customer who transition out from the cell into the desired cell along the life stage path. The team will be measured basis how they drive the customers to the next stage of the path.
From a competitive angle, the customers in the critical cell are key to the future growth of the company. It will be key to ensure that the customers in this cell are protected. At the same time, the cells that lead to undesireable stage can be managed for exit.
Kenichi Ohmae wrote one of the first books on business strategy titled “The Mind of the Strategist”. In the book, he had defined strategy as the plan which impacts the three C’s – Customer, Company and Competition. The Customer Life Stage Model impacts all three C’s. Hence, it also forms the basis of customer relationship management strategy.
If you intend to pilot the Customer Life Stage Model, I will be happy to work out a joint activity plan.
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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.