Advances in technology have increased interest in indoor positioning services as they represent a high business potential. However, implementing them did not have the expected success rate for businesses because users did not see enough value in using the indoor positioning services and perceived them as being intrusive. Thus, companies have developed highly advanced technological solutions that cannot be applied to the current business world due to poor user adoption rates. This problem can be fixed by rewarding customers for sharing indoor location information that can be used by businesses to gain precious user knowledge. This creates extra utility for both businesses and customers. Customers have privacy issues when it comes to sharing private indoor location data but these are eliminated for a certain monetary reward. However, customers value their privacy differently and thus they need different amounts of compensation for the same indoor location information. Businesses consider user indoor location information valuable and are willing to pay for it. Similarly, the benefit of the businesses is variable and based on this they can afford paying a higher or lower fee for the indoor location information. There was no system that could mediate the interaction between these stakeholders and our objective was to create one. We limit our research to the retail industry, more precisely the supermarket sector and we use simulations to validate our research. The proposed system is based on any type of indoor positioning technology and is mostly applicable in United States and Western Europe We propose a platform model to mediate the interaction between businesses and customers. This mathematical model is in equilibrium for any input data set and the challenge was to find the equilibrium points. We use concepts from game theory and mechanism design and apply a method based on a three stage Stackelberg game in order to create this model. Our input variables are the benefit of the businesses and the privacy cost of the customers and based on this we want to find out the correct amount of reward offered by businesses and the correct amount indoor location information to be shared by customers. Additionally, the interactions of these stakeholders with the platform are modeled. All the three players participating in the game have a utility function modeled which is mathematically solved, such as the outcomes of the three parties are maximized. At each stage of the game we find out which businesses and customers are participating and what their best response strategy is using a MATLAB implementation. We perform simulations on a standard set of parameters and see what the impact is if players deviate from the equilibrium strategies. We validate the model through a discussion about the assumptions, how does the model fit with existing economic theories, how can results be influenced and what are real life risks of the implementation.