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About Mabrian

The 10 keys to Tourism Intelligence 

At Mabrian we have been developing our technology and services for 10 years to make it possible for destinations and tourism companies to make more efficient and sustainable decisions based on relevant information. In this process to transform data into actionable information, we have faced multiple challenges: from identification, acquisition, and harmonization…all the way throughto the interpretation and presentation of the results. 

Now, with a robust and reliable system and methodology that we already offer in 40 countries, we want to share what for us are the top 10 most useful tips when starting a Tourism Intelligence project. We hope you find them useful: 

  1. Data alone is not the answer. Having data means only having the raw material to be able to generate information. Without expert aggregation, normalization and structuring work we will not get the information that really makes a difference in our decisions. 
  1. Know the questions. One of the great challenges of data intelligence projects is knowing what questions we want to answer. Specific objectives must be identified and you must know what information can support their achievement. We will not find answers in the data unless we clearly know the questions. To do this, it is key to have a deep knowledge of the sector in which we operate. 
  1. The dose, the moment and the format. For decision making based on data and information, momentum, precision and clarity are key. The information must reach the decision-making team at the right time, as up-to-date as possible, in a concrete manner and in the necessary format. There is little point in investing efforts in a very detailed and complete dashboard if the information is not going to be consumed through it. The different audiences for the information must be identified and the indicators and format adapted to their needs. 
  1. Start from within. All organizations have many internal sources of data that they do not exploit adequately. Making an inventory of all the data collection points available to an organization (PMS, CRM, RMS, Channel Managers, OTAs, etc.), validates the quality of the collection, the potential of the information and prioritizes the incorporation of those that can help make better operational decisions aligned with objectives. 
  1. Beware of ‘Bad Data’. Knowing the nature, limits and implicit biases of each of the datasets you work with is vital. Everyone contributes, but none is perfect. Information based on erroneous data can lead us to erroneous decisions (insufficient sample, partial data, low updating, etc.) 
  1. Data privacy & security. It must be certified that the methodology for collecting, storing and processing the data collected strictly complies with  personal data protection laws. Regulations may be different if data in different countries is used. The storage of information containing personal data should be limited as much as possible, if possible. In most cases, anonymized data is just as relevant and makes management much easier. If personal data is stored, the inviolability of the system must be ensured. 
  1. The cross analysis. Overlaying data from diverse sources on the same reality, in addition to enriching the result, avoids falling into erroneous conclusions. Cross-referencing helps us complete and validate results, adding a lot of light to the analysis. Most of the time, we do not aspire to have absolute certainty about one element, but rather, increasing the probability of success and the efficiency of a decision is enough. 
  1. Contextual data. Incorporating information about a destination or destinations, where for example there are interests and about global tourism trends, offers a key competitive advantage at both an operational and strategic level. The more agile we are when we adapt to changes in an environment, the more efficient we will be. To do this we need updated information based on data (Big Data) that is currently available from various sources. 
  1. Measure the return. Allocating resources to data intelligence should be seen as an investment, not an expense. The best way to argue an investment is to identify performance metrics that help us measure its return. Metrics can be direct and transactional (ADR increase, RevPar, occupancy, etc.) or indirect and non-transactional (brand value, perception, competitiveness, etc.). 
  1. Trust experts. Data intelligence projects are very complex at a technical level: identification, validation of sources, data acquisition, normalization, structuring, security, etc. Furthermore, in the case of Tourist Intelligence, knowledge of the sector and the tourism business to be able to efficiently implement the technical challenges. We need to have a mixed profile between a data scientist and a business consultant, something that is not easy to achieve internally. Trust those external experts who can contribute the value of their know-how to facilitate, accelerate and advise on the implementation of data culture in the organization. 

You want to know more? Contact our team here:

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