Artificial intelligence is being applied in multiple areas, from a more strategic area such as forecasting the results of new hotels, which helps in the decision-making process for new acquisitions, to solutions that help optimize the business.
An example of this is the forecasting of key indicators, or KPIs, for hotels, helping to integrate the global and local management of the business, facilitating the estimation and fulfillment of these KPIs, and having an analytical layer that allows for more accurate forecasting of these indicators.
Another highly demanded case is the increase of the digital conversion rate thanks to the analysis of large volumes of navigation data and identification of relevant patterns with higher propensity to purchase, with diverse purchase motivations, and the possibility of real-time decision making based on those patterns.
All this facilitates the improvement and personalization of the digital shopping experience. In this sense, very interesting projects are being carried out with good results, both in the customer acquisition phase and in the conversion phase, thanks to adopting the service, campaigns, and even prices to each user.
Many companies are working on the integrated exploitation of data captured in digital and physical interactions, either in the hotel or through the contact center, to make forecasts of the behavior or preferences of potential and current customers. In this way, it is possible to optimize the response “to the specific needs of each of them, facilitating the purchasing process and increasing their satisfaction”.
Top 3 uses of artificial intelligence in hotels
The top 3 uses of artificial intelligence with the greatest impact on a hotel chain’s bottom line are:
- Comprehensive demand forecasting, allowing proactive management of availability by adapting prices and resources based on forecasts.
- Optimization of the digital funnel, thanks to a better knowledge of the needs and preferences of current and potential customers.
- Forecasting of management indicators in a business where occupancy is key and the optimal management of resources can be the differentiating element between making a profit or incurring significant losses.
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