In the current context, it is harder than ever attract and get loyalty the customers. You may have already had an amazing customer and thinking about it would be extraordinary if all the customers were like that. Maybe you have also meditate on how the differences in customer lifetime affect on your marketing strategy.
However, the customer lifetime value (CLV) can be rather complicated to study, especially because of the time that many small and medium sized enterprises employ to convert a lead into customer.
But don’t think that could be a problem. Following there is a way in which the products or the services that you sell allows to loyal customers adding value at your business.
Unify data to obtain an analysis of your best customers
For best customers I mean that with a more high lifetime value. You could describe some features about your more loyal customers, but how much of them are based on customer data?
If it isn’t so, unify customer data breaking down barriers, measuring all the customer journey and building dynamic user experiences. If you are unified all possible data, the next step is to start developing a customer lifetime value example.
Three steps to unify customer data:
- Breaking down barriers and reinforce customer data
- Perform measurements and analysis during all the customer journey
- Build dynamic user experiences
Use the available resources to determine the complexity of the Customer Lifetime Value modeling
The complexity of CLV modeling depends from the amount of funds and talents you can dedicate to the latter. After you defined the resources you can commit, you’ll be able to define more easily the complexity degree about modeling.
For example, there are so many companies that to estimate the customer value, use a lot of Markers as the product purchase pricing, demographic customer data and purchase data. This metric is called “Day One” and predicts a single customer value in a particular moment, and also the efficacy in helping to make decisions regarding the investment of some customers.
The companies which don’t have the same resources to analyze data can use simpler alternative methods, as purchase pricing or the customer lifetime value.
If you don’t have the resources for a more advanced model, you have to consider the average incomes for customer, the average outcome frequency and the amount of products or customer service request at your business. Gather these customers into as many segments as are your resources to perform the analysis, starting from the easiest sharing between customers below average, average and above average.
With all the information at your disposal, try the common features between data into every group. To prevent the potential customer lifetime value, compare all their data with those of these consolidated groups.
What really matters is the usage of new customer data
If you don’t have resources, you have to consider the possibility of cooperation with a data scientist or an expert agency to develop probability models about the behaviour of buyers.
Regardless the complexity of the model, develop it one effective for your business requires time and task.
The development of CLV modeling is the first step for a long term business sustainability, but the modeling is not enough to produce outcomes. What really matters is how you use new customer data.
Every journey is composed by more steps and that of CLV is not an exception. Every step allows you to reinforce the position of your company. Start letting your data show you the way to achieve the best customers.
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