Online recommendation services (widely known as recommender systems) can support potential buyers by providing product recommendations that match their preferences. When integrated into e-markets, recommendation services may offer important added value, since they can help online buyers to save time and make informed purchase decisions, as well as e-market operators to respond to buyer product’s queries in a more efficient manner, thus attracting more potential buyers. On the other hand, the variety of intelligent recommendation techniques that can support such services may often prove complex and costly to implement. Towards this direction, this chapter proposes a design process for deploying intelligent recommendation services in existing e-markets, in order to reduce the complexity of such kind of software development. To demonstrate the applicability of this approach, the proposed process is applied for the integration of a wine recommendation service in a Greek e-market with agricultural products.