Over the past decade, an increasing number of firms across sectors such as travel, entertainment, retail, and platform-based services, have transitioned to algorithmic pricing mechanisms. These mechanisms involve the deployment of software that automates price setting and are mainly used by firms aiming to optimise pricing decisions in response to evolving market conditions. Pricing algorithms may combine data and assumptions on factors such as prices, volumes, inventory, and customer responsiveness to forecast market demand and elasticity; they may assess the potential impact of different pricing options on business goals like revenue, profit, and market share, factoring in expected competitor responses, and then apply the optimal price in real or near real time. Thus, their use may require vast amounts of granular data.