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The CLV model is an indicator used to measure and evaluate the future value of customers to the company. But the CLV model is predictive where it will be more accurate if there are many supporting variables, one of which is customer motivation. Adopt the point of view of the Octalysis gamification framework, that behavior occurs because of an individual's motivation or drive. Therefore, it is important to explore what drives influence customer behavior, so that it can affect the customer's future value (Customer Lifetime Value). By using the K-Means clustering approach, CLV value weighting, and Octalysis framework, the study analyzes the relationship between CLV and 8 core drives to customer motivation to produce 3 contributions: (1) The results of K-Means analysis of customers based on variables L, R, F, M and CLV value weights have produced the best cluster k = 2 where segment-2 has a future value level (CLV) of the company higher than segment-1, (2) Likert scale comparison analysis and the relationship between the results of CLV segmentation on 8 core drives motivational resellers to produce similarity of ranking patterns on each core drive and its average, meaning that between the customer's future value (CLV) with 8 core drives the customer motivation is not interplay. (3) Comparative Octalysis analysis of the balance of 8 core drives resellers in the two segments results in a difference in the total Octagon score (segment-2 = 368, segment-1 = 419), and this means that the high or low future value of the customer against the company is inversely proportional to the high and low of 8 core drives reseller of companies.