Is offering differentiated hotel pricing based on the geographic location of the guest a viable revenue management approach?.

Recently, the San Francisco Chronicle (SFGate) conducted a research on the major OTA platforms to compare hotel prices for the same hotel rooms, during the same hotel stays, using different devices, browsers and while browsing from different geographic regions.

SFGate found out that the most popular hotel booking sites raise their prices substantially when people living in San Francisco and the surrounding Bay Area use these online booking platforms, compared to users browsing from less affluent cities, like Phoenix and Kansas City.

SFGate noted that "In one shocking case, the Bay Area test user was offered a nightly rate for a Manhattan hotel room that was $500 more per night than the rate offered to consumers in the less affluent cities for the exact same room and dates."

Obviously, the OTAs assume that people living in the San Francisco area can afford higher hotel rates, compared to people living in lower income areas of the country.

The question is, does offering differentiated hotel pricing based on the guest's geographic location constitute a smart revenue management approach?

Here is my take:

This is not the first attempt for an ill-conceived differentiated pricing by the OTAs. 15 years ago Orbitz was caught jacking up prices for Apple computer and laptop users under the presumption that Apple users were more affluent than PC users.

Now comes a rather shallow attempt by the OTAs for "one-to-many personalized pricing", based on income levels in the geographic area where the customer resides.

As for the $500 discrepancy, it may be caused by cached ARI (availability, rates and inventory). Though the OTAs work with smart cache, the zillion APIs to CRS, Channel Managers and manually managed ARI via the OTAs extranets can create such pricing discrepancies.

Luckily, with the help of AI, revenue management will be moving from the current "one-to-many" pricing approach to the "one-to-one" pricing, which will take RM to an entirely different level.

One-to-One Pricing, powered by AI and supported by CRM will allow hoteliers to automatically personalize pricing and product offering to the individual customer level and take into consideration dynamic factors such as customer's preferences, browsing behavior, influencer status, "intent to purchase" intensity, and of course the more mundane factors like RFM value, loyalty member status, past booking history and demographics.

Max Starkov
Hospitality & Online Travel Tech Consultant & Strategist

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