Online consumer ratings provide essential information to users and valuable feedback to businesses. Especially a long-term perspective of an item’s ratings (e.g., covering several years) is highly relevant as it is expected to give a robust view of the item’s true quality, strongly influencing purchasing decisions, sales and pricing. While users should follow their own quality perception, previous research has shown that prior ratings can influence the next user’s rating decision in the short term, either following them or differentiating from them. We advance this research by analysing the long-term influence of initial ratings with respect to true quality, bandwagon, and differentiation effect. To do so, we leverage eight extensive real-world rating datasets from various domains and employ regression models and statistical tests. Our analyses of six hypotheses reveal that initial ratings significantly influence long-term ratings regarding the mentioned effects, which needs to be considered by users, businesses, and platforms.