Designing decision support system for revenue optimization in retail marketing using social networks data constrained to maximizing customer satisfaction. Proposed effective graph pruning strategies and a greedy-based heuristic for computing a satisfiable good-enough solution in polynomial time. Proposed model is flexible, generic and adaptable to address similar data-driven user-oriented problems and tested on different SNAP datasets like Facebook, CollegeMsg and some randomly generated graphs.