SEA LIFE Helsinki is the first Finnish company to adopt an artificial intelligence-driven solution for ticket sales. “Starting in August, SEA LIFE’s customers will have the ability to name their own ticket price for the park admission, getting personalized discounts according to their willingness to pay, weather forecast, the day of the week, the time of visit, and other variables”, says Mikko Riistama, SEA LIFE’s Managing Director / General Manager and the one responsible for bringing the innovation to the Finnish audience.
Convious is the company working behind the scenes. According to Kevin Westermeijer, co-founder and CCO at Convious, “With the Convious solution everybody benefits. As a B2B2C platform, our AI-driven technology analyzes huge amounts of data in real-time just to make sure that both the merchant and the customers will get what they want, within an acceptable price range, and maximizing sales and customer satisfaction. It’s also very important to mention that the merchants always have full control of their pricing strategy.”
Convious and SEA LIFE are currently working together in 3 locations: SEA LIFE Blankenberge, SEA LIFE Helsinki, and SEA LIFE Scheveningen, and have plans to adopt the technology also at SEA LIFE Istanbul by December 2018.
The Convious solution
Convious is an Amsterdam based startup company that uses machine learning to understand the customer’s buying intent in real-time and increase the chances of conversion by personalizing the entire customer journey, from the messages to the prices. As a B2B2C solution, it all starts with the merchant defining their pricing targets (minimum, maximum, and average ticket price). From this point on, the algorithm tracks the merchant’s website audience, recognizes patterns, predicts different buying intents, and adapts the entire sales funnel to maximize sales and revenue.
From a customer perspective, personalized deals are offered for different visitors, including the ability to name their own ticket price that will be evaluated in real-time and accepted depending on a wide range of variables that can include real-time demand, weather forecast, and behavioral patterns.