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Define Your Buyer Persona According to Profitability

by Beonprice

                                                                                                                  Define Your Buyer Persona According to Profitability

                                                                                                                  “Data is the light that illuminates our business’ road to success.”


                                                                                                                  This could be the romantic phrase of some timeless philosopher-mathematician trying to synthesize the value that data and the interpretation thereof can offer any given business. We define the concept of value not only in terms of profitability but also in terms of market adaptation. It’s important to analyze the information we have around us in order to make better decisions. While it’s often very hard to know where travelers are coming from, or how difficult it will be to win customers, or how each reservation can impact profitability, these questions are easy to answer if we adequately study the relationship between traveler and hotel.


                                                                                                                  When harnessing the power of information, which is in turn linked to different traveler types (often defined as buyer persona or personalized, humanized profiles of demand), we must understand the importance of how we define value, in business terms, and how we map booking data to traveler profiles. This way, we can ground approximations of traveler profiles on real demand and understand how these behave at a consumer level.


                                                                                                                  Following a defined traveler profile and linking it to demand helps us to better understand behavior patterns (e.g. by analyzing booking curves, identifying how timeframes affect bookings, checking the location of cancellation policies, noting typical expenditure in a restaurant or even observing how climate can influence the length of a stay). It’s a matter of compiling and cross-referencing data in order to draw conclusions, a dynamic process in real time which enables us to make decisions and increase profitability.


                                                                                                                  To lay the groundwork, we can begin by defining four buyer personas and, from this, personalize them in more detail and, if necessary, include new profiles. We can make use of information from our co-branded website with Google Analytics, obtain interesting information from our direct traffic and even define a buyer persona using the client profile that we receive from Booking.com. This information should be “drawn” on our PMS as the basis from which we can start working. For example, for a hotel on the Costa Blanca with specific features and facilities, the buyer personae could be the following:


                                                                                                                  1. María. Agent Mice.

                                                                                                                  2. Ana. Family mother.

                                                                                                                  3. Raul. Team Leader cycling team.

                                                                                                                  4. Marío and Lucía, a young couple.


                                                                                                                  These are just a few examples that could be adapted to a specific coastal accommodation and on which we could begin to disaggregate information, define content strategy and articulate product.

                                                                                                                  In order to connect these buyer types to the reservations on our CRM, it’s wise to consider data such as the following:



                                                                                                                  • Average stay.

                                                                                                                  • Reserve Curve.

                                                                                                                  • Net income.

                                                                                                                  • Rates with which you book.

                                                                                                                  • Number of people associated with the reservation.

                                                                                                                  • Channels linked to the reservation.

                                                                                                                  • Costs associated with channel capture (CPA).

                                                                                                                  • Repeat bookings.


                                                                                                                  Synthesizing as much as possible the information we have at our disposal has a direct relationship with the knowledge of reality, from an effective and direct point of view. Historically, hotels have operated by an intuition more or less related to reality. The day-to-day life of today's hotel is very different, decisions are based on data, results and affordable technology, economically speaking, and with increasingly shorter learning processes.

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