The hotel industry faces a paradox: while the adoption rate of artificial intelligence (AI) in revenue management systems (RMS) is rising rapidly, confidence in the technology's decisions often remains low. Many hoteliers use AI but are not willing to release full control. The reason is simple: there is a lack of transparency.
The "black box" is blocking progress
AI systems often operate as so-called "black boxes." They take in large amounts of data and spit out an optimized price without explaining how they got there. For the revenue manager, whose responsibility is at stake with every pricing earror, this is an unacceptable situation: they have to implement decisions that they do not understand or cannot explain. The consequence of this lack of transparency is that the systems are often only operated at a low level of automation or merely serve as expensive data aggregators instead of exploiting their full potential for profit maximization.
This lack of accountability leads to three key problems:
- Lack of trust: The user intervenes manually because they cannot understand the recommendation. This often happens out of fear of unforeseen losses or a feeling of losing control over their own pricing strategy. Constant manual corrections undermine the efficiency and usefulness of AI.
- Missed opportunities: Automation is throttled or switched off. This prevents hotels from responding quickly enough to real-time market changes. Especially in times of strong demand shocks (such as major events or sudden weather changes), these hotels lose valuable revenue to their more agile competitors.
- Lack of learning: The revenue manager cannot use the logic of the system to improve his own strategic skills. The black box prevents understanding of complex relationships and hinders staff development in dealing with modern data-driven strategies.
Transparency creates trust
A modern, future-proof RMS must close this trust gap. At Hotellistat, it was clear from the very beginning that AI must not only recommend prices, but also explain them. Only then can technology become a reliable "right-hand man." ARIS, Hotellistat’s Automatic Revenue Intelligent System, reveals the basis for decision-making. The AI analyzes over 1,000 relevant data points and filters out the five most important factors for each individual price recommendation. In addition, hoteliers can adjust the weighting of the influencing factors themselves in the settings and decide whether the AI should focus more on market developments or internal PMS data.
How the "Price Explanation" works
Instead of simply stating the price of €189, the system transparently displays the factors that most influence the price: ARIS starts with a base price and then shows both graphically and numerically which external and internal data points cause positive or negative adjustments.
- Visual adjustment: Users can immediately see which five factors (e.g., events, weather, or competitor rates) have the greatest influence on the price and how these are weighted (as a bar chart with positive or negative values).
- Final calculation: Below there is a detailed breakdown of the final price components (e.g., market placement adjustment, volume vs. ADR) that lead to the final price. In addition to these five factors, ARIS visualizes the price development of the last ten days in a clear price curve, making the history of each rate recommendation traceable at any time.
More than just a prize: added value for hoteliers
This transparent presentation has two major advantages:
- Reliability and control: The hotelier immediately understands how the price was derived. They know that no arbitrary decision was made, but rather that a rational, data-driven calculation was made. This creates the necessary trust to run automation at a higher level and focus on strategic tasks such as guest service or optimizing sales channels. Constant review of recommendations becomes unnecessary, saving valuable working time.
- Learning curve: The system acts as a mentor. The revenue manager learns in real time which external or internal signals have the greatest influence on the market and can thus sharpen their strategic skills. This knowledge enables hoteliers to better interpret AI recommendations and, if necessary, override them with their own expert knowledge. This makes AI a powerful sparring partner.
The future of revenue management lies not in blind automation, but in intelligent collaboration between humans and technology. Transparency is the key to success here.
