Hotels Face New MarTech Measurement Challenges

The industry of hotels is faced with the challenge of increasing the cost of acquiring them with changing MarTech systems and data quality due to privacy regulations.

The hotel industry is quite experiencing a significant MarTech disruption in which privacy laws, data control through consent and platform change limit the amount and dependability of promotional cues. According to hotel tech company Cendyn, the increasing media prices and the limited access to guest conduct are driving the prices of acquisition higher, revealing flaws in traditional MarTech bundles constructed to offer high-signal operations.

Current analytics, attribution and automated bidding systems rely on clean and consistent event data. Nevertheless, the declines of tracking by guests result in bookings but cannot be properly registered in the dashboards, leaving incomplete measurement structures. Some hotels have been performing better than competitors, Cendyn observes, with AI-supported campaigns and solid data pipelines, as a fact that MarTech maturity is currently pitting best-performing hotels against others.

Measurement uncertainty is on the rise at an industry-wide level as consent affects identity resolution and attribution models. The new regulations, like the FTC of the U.S.'s proposed regulations on pricing disclosure, also make digital journeys more challenging and demand closer data alignment between brand sites, metasearch platforms, and OTAs.

Experts suggest that to enhance the resilience of MarTech, hotels should make consent a layer of optimization and train on first-party data approaches, such as integration with the CRM, authenticated sessions, and permissioned communication. Besides, SEO and organized content are to be handled as calculated acquisition channels, and reliance on weak signals of the paid media is to be minimized.

Cendyn says that the thriving hotels will re-establish measurement of a low-signal world and unleash AI strategically in order to transform weaker data into stronger decisions.