Automation in Travel: Innovation at the heart of Experio
As a technological company in the travel industry, have the responsibility of making use of the latest innovation tools in order to provide a helpful, intuitive and user friendly service that adds value and that makes a positive impact to travelers around the world.
Additionally to the use of distributed ledger technology which allow us to build a tool that grants access to decentralized financial instruments like payment services, we strongly believe that the use of machine learning features and algorithms in our ecosystem will be a key differentiation that will set experio.at apart.
“The complexity of the pricing in the travel industry requires more advanced techniques”
With the aim of helping travelers and companies to interact in our ecosystem, our approach to AI and automation has three main pillars; recommendation engine, dynamic pricing and intelligent travel assistants.
In the following blog I will make a summary of the different technologies that will be key in the future of our platform.
Our plan is to build algorithms that allow us to create a personalized geo-location recommendations of travel experiences based on social media data, browse and search history. This allows us to provide a more accurate and personalized offering of our experiences and will help hosts reach out more travelers that will be likely to engage.
The complexity of the pricing in the travel industry requires more advanced techniques that helps us handle all the different challenges such as seasonal price changes, prices variations based on availability, increase in the demand and other recurrent problems related currency exchange. We plan to solve these issues by implementing dynamic pricing tools that will make life easier to our users to buy travel experiences using not only crypto-currencies but also with fiat money like EUR or USD.
Intelligent travel assistants
Last but not least, we have developed a chatbot based on Facebook messenger, which is able to send relevant notifications to the users directly to their Facebook inbox. This is way more effective to deliver relevant information to the users, as the open rates on messenger platforms are around 88%, compared to the open rates on emails which are in average 24.79%.
This chatbot can be fed with information or data entered by the users, as soon as an users inputs a word that the chatbot has never “heard of”, the word is automatically sent for human review and update of an appropriate response, meaning that the more interactions an user have the “smarter” it becomes, it is also possible to automate the feedback mechanism when the amount of users in the platform increases.
Finally, we can conclude that companies are realizing that innovation like distributed ledger technologies and the latest machine learning trends are helping them to add value in their services, it is obvious that by implementing such tools will certainly help grow their business, after all the most successful companies in Silicon Valley have been the ones that use automation and user feedback in order to offer a better and seamless user experience.
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