When hotel managers determine the prices associated with room revenue, they apply a rigorous approach that draws on industry and market data. This allows hotel managers to optimize room pricing for their market, balancing supply, demand, services, and brand.

Considering the rigor applied to room revenue pricing decisions, it is remarkable that the approach to hotel F&B pricing is comparatively underdeveloped at most hotel properties. F&B managers typically opt for a safe-bet strategy of pricing F&B based on the average prices for similar products offered by the competition. Instead, there are simple, inexpensive processes and tools to help managers determine how to improve value at the point of sale for F&B pricing at their property.

We review those limitations, processes and one of those tools here.

Where competitive set F&B pricing fails

The standard strategy to benchmarking versus the competition for hotel F&B pricing incorporates potential weaknesses that can lead to inappropriate product valuation. It

• assumes the competition’s pricing decisions are correct and
• ignores the price sensitivity/insensitivity of the property’s own guest in their F&B spending choices.
• presumes their F&B product is comparable or superior to that offered by the competition

Figure 1: The pricing and value spectrum includes the competitive set anchor and the guest’s willingness to pay based on perceived value, and reveals opportunities to unlock value with site-specific F&B pricing. From: Dilip Soman and Sara N-Marandi. 2010. Managing Customer Value: One Stage at a Time. World Scientific. Pp. 245–248.

Two steps to finding the pricing “sweet spot” on the pricing-value continuum

To determine how to best price F&B offerings to unlock maximum value, a hotel F&B manager must look carefully at the assumptions that underlie current pricing decisions, then accurately determine guests’ sensitivity to price.

Step 1 – Question assumptions

Operators must examine the assumptions that currently inform their pricing decisions. When they do not scrutinize these assumptions, hotel F&B operators tend to over-estimate their guests’ price sensitivity, relying too heavily on intuition and opinion during the decision process. In the absence of hard data, an overly cautious F&B pricing approach can also be exacerbated by what F&B leaders consider high prices in other areas of the hotel. Managers might think, “The guest rooms already cost so much to begin with, we can’t have outrageous F&B prices as well.” So instead of recognizing the high average daily rate as an indicator of relative price insensitivity, managers may take it upon themselves to compensate – by “creating value” by arbitrarily depressing F&B prices when little evidence suggests this is necessary.

Step 2 – Analyze the effect of price on popularity

Once an F&B manager identifies and understands the assumptions underlying the hotel’s F&B pricing approach, the opportunity to refine that approach may emerge. A simple Excel regression analysis will reveal the high-level relationships between menu item prices and their effect on the quantity of items sold. The “R-squared” value on the analysis output provides a basic understanding of how strong the relationship between price and popularity is: An R-squared value of 1 means price is the sole determinant of menu item popularity whereas a value of 0 means price has no measurable effect on what people order. The R-squared value will typically fall somewhere between 1 and 0.

In a wide sampling of hotel F&B outlets, an R-squared value below 0.25 is common. This suggests that price accounts for less than 25 percent of the variability in the sampled menu item popularity. In other words, 75 percent and more of the time, customers weigh other factors more heavily when deciding what to eat and drink. Those factors may include, instead, how delicious the dish or drink looks, the server’s recommendation, whether the dish or drink meets the customers’ need for convenience at time of ordering, or if the customer will be claiming the meal or drink as a business expense.

No hard and fast rules exist for what makes an R-squared value “good” in these kinds of analyses. In fact, F&B managers would benefit from exploring the rest of the regression analysis output for additional clues as to what affects a product’s popularity. If they have time and resources, they can then use this information to investigate their guests’ price sensitivity / insensitivity further using other methods.

Conclusion

Food and beverage pricing at many hotels is too often determined by what the competition is doing, not by what guests are doing at the hotel itself, despite pricing accounting for the guest decision process. By challenging both the known and unacknowledged assumptions that underlie their pricing decisions and using the simple statistical approach suggested above, F&B managers can gain valuable insight into F&B pricing opportunities available onsite at their own hotels. By shining a light on possible disconnects between perceived guest price-consciousness and the evidence those guests are providing with their wallets, these two key steps help to increase the rigor of hotel F&B pricing decisions.