Judging by Amazon’s success, the recommender system works. Adopting such a system to the automotive aftermarket poses many challenges. Association analysis for vehicles is much more complicated than for simple consumer goods. Normally a recommender system is tailored towards the users’ subjective preferences whereas in the aftermarket the user follows an objective search approach. TecAlliance implemented a recommender system in its spare parts catalogue – known as TecDoc Catalogue – based on a simple association analysis and web analytics data that overcomes this challenge. Workshops don’t have to search interrelated articles manually anymore and get a suggestion of similar articles that are related to the viewed one. Overall, this leads to a massive time saving and better process design.