Despite fierce competition from global and local rivals, Kyiv’s Uklon Internet taxi service is doing just fine – and even expanding into more major Ukrainian cities. How? By smart use of Microsoft Azure-powered Machine Learning, which delivers unique service pricing that customers love, and nobody else in the market can offer.
Kyiv-headquartered Uklon gives citizens and business travellers to major Ukrainian cities fast and convenient taxi services. Facing intense competition in this sizeable (42 million citizens) local market from established international brands like Uber, as well as new entrants from neighboring Russia, the 150-strong company says its battle for market share has started to get a little easier.
That is thanks to innovative use of leading edge big data analysis technology. There are no standard fares for Ukrainian cabs, so customers needing a ride sometimes need to ‘bid up’ at busy times to secure a driver. This can take time and needs the customer to guesstimate the best new tariff they want to offer a driver – it was in effect a “lottery,” in the words of co-founder and Chief Technology Officer, Vitaliy Diatlenko.
Uklon has automated that process, working with the help of local Microsoft Gold tech partners SMART Business to use data science to suggest the optimal fare price to bid. As a result, suggested fares the customer is offered – based on factors like time of day, traffic, distance and previous fares accepted – come from a customized Uklon algorithm running on Microsoft Azure developed by SMART Business. The approach takes full advantage of Azure’s extensive range of Artificial Intelligence (AI), Machine Learning and data analytics services.
Using AI to beat the competition
“We needed to increase the number of completed bookings our drivers see at even the busiest times of the day,” says Diatlenko. That is good news for Uklon’s vital taxi partners – and is definitely helping the bottom line, confirms his colleague, Chief Marketing Officer, Daniel Vakhovskyi, who confirms that customers immediately accept the suggested fare 75% of the time, while “use of analytics and Machine Learning has directly boosted average successful taxi bookings by 18% at peak times.”
Just as importantly, exploitation of Microsoft Azure-delivered algorithms has caused a significant increase in customer interest and loyalty in the Uklon brand. This is shown in the company’s marked increase in Net Promoter Score (NPS) rankings, he adds, with its biggest competitor’s NPS score dropping from 43 to 22 while Uklon has climbed to 30.
“By turning our data into a real business asset, we made our service more attractive for our market, while our internal operations based on the latest and most relevant performance metrics,” confirms Diatlenko.
Next steps for Uklon including extending this successful data-backed business model to other cities, he states, concluding that this is definitely a story “about using AI to beat even the strongest competition!”
By turning our data into a real business asset, we made our service more attractive for our market.
Vitaliy Diatlenko: Founder and CTO
Use of analytics and Machine Learning has directly boosted average successful taxi bookings by 18% at peak times.
Daniel Vakhovskyi: Chief Marketing Officer