We went through standard clustering algorithms and selected some conventional algorithms, i.e., k-means method, CAST and hierarchical method, establishing the drawbacks of the mentioned algorithms. We highlighted the computational drawbacks, including optimization, time and space requirements. We then introduce a hybrid clustering algorithm based on the three mentioned clustering methods, with an inbuilt validation. The hybrid algorithm overcomes the major drawbacks of the listed clustering algorithms, and proved to be 25% more efficient than the individual clustering algorithms listed above. © Research India Publications.