In this paper, we proposed a new model to evaluate a customer''s lifetime value, considering non-financial elements such as the customer’s churn probability, cooperation capability, willingness to refer, willingness to recommend, and innovation. We tested our proposed model on customer data from a mobile phone operator to evaluate the effect of each element on the customer''s lifetime value. Four hundred and twenty questionnaires were distributed and 400 questionnaires were determined to be suitable for our study. We employed structural equation modeling using Smart-PLS software and we have found that the innovation, customer’s churn, willingness to refer, and cooperation elements have the strongest effect on the customer''s lifetime value.