In this chapter, we discussed how to create association rules, what all factors determine the rules' existence, and how rules explain the underlying relationship between different items or variables. Also we looked at how we can get most compressed rules based on minimum support and confidence value. The objective of the association rules model was not to come up with rules but to implement the rules in business use cases for generating recommendation for cross-selling and upselling products, and designing campaign bundles based on association. The rules would provide necessary guidance for the store managers to place products and merchandising design in a retail setup. Having said this, in our next chapter, we are going to cover various methods of performing clustering for segmentation, which would provide more insights into product recommendation using clustering methods.