





- an AI-powered app which allows the user to find an event and the organiser to find the customer

How the idea came about


Event postings and aggregators suggest random events. Social media platforms full of unwanted ads, increase the search time for the user and do not always deliver the expected spin-off for the organiser
Typical aggregators











Currently there is no single service which takes into account the users’ leisure preferences
The app which works for both the customers
and the organisers
We conducted a study among potential users of the application
Our recent survey reveals 90% of users turn to multiple channels for event search: websites, social media, e-mailing, bloggers’ tips, word of mouth, etc
83% report that without following the theme communities it is hard to find information on low-keys events while the customised selections are either not provided or do not satisfy the user’s tastes
Users’ problems
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No single information platform on different events including local tourism
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Time-consuming search
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No tailor-made offers based on tastes
Solution
AI-powered event metasearch engine generating tailor-made solutions based on:
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Tastes
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Locations
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Price
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Time
75% of organisers want to cut their event promotion costs since they do not always get the expected result
Own websites or public pages are more sales-effective than the aggregators or social media platforms. The ad costs on the outside platforms are considerably higher especially for the organisers of low-price or free events
Organisers’ problems
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High competitiveness and target customer acquisition costs
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Aggregators’ commission
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Lengthy ticket sales
Solution
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The benefit of “own visitors” flow thanks to a special selection algorithm for users
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Free information posting about the upcoming events on the platform
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Customised offers and the information on the city map speed up the ticket sales





Based on the gathered information recommends the events which the users with the similar tastes have queried about, but not yet the current user

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The most relevant results (similar preferences, tastes)
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Week picks (low-key events which might appeal to the user)
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New events radar (new events which might appeal to the user)
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Exploration (try something new and unusual)