Business problem

Real estate search portals are consistently trying to offer the best, most unique information to their users and search engines. As the 5th largest portal in the US, collects a massive amount of anonymous data from on-site user behavior, however data at the scale of hundreds of millions of interactions is challenging to aggregate and summarize. With a comprehensive understanding of both the demand and supply sides of real estate availability, can offer more personalized recommendations that better address user needs and inventory targeting.

Dribia's solution

We used data from user site searches as a proxy for housing demand, geo targeted to specific locations and cross referenced with listing availability (almost 3 million records) in each US market. Using this data, we created an adequate but valuable KPI that defines areas where housing demand might lead to fluctuations in pricing, and the velocity of those prices changes, based on the anticipated inventory of listings versus the real-time search behavior.

"Our partnership with Dribia has provided valuable tools that can empower key customers with accurate timeframes of the potential risks and opportunities in their real estate markets."

Grant Simmons

VP of Search Marketing @


Business problem

So far, destinations without an established direct and regular connection have been diffcult to reach with collective transport. Yet, technology and the availability of major data sources provide an accessible tool to assess the real demand for such off-schedule routes without coverage.

Dribia's solution

For our UK client, Zeelo Ltd., a start-up offering “pop-up” coach services to specific events, we are designing, training, and validating an intelligent algorithm that predicts general demand for collective transport. It crosses different geo-localised data sources (e.g., traffic control, social media, search engines) and generates a ranking of profitable routes and their optimal trajectory.

"Dribia managed to turn our high level ideas into concrete algorithms that address our needs. Their commitment, thoroughness, and transparency have convinced us from the outset."

Daniel Ruiz

CTO @ Zeelo


Business problem

Newcomers to a city often have to go through a cumbersome research to find a neighborhood to live in that suits their interests and needs best. Now, most relevant data is publicly available. However, users actually look for easier and more straightforward ways and tools that help them in making that decision.

Dribia's solution

For our Lithuanian client,, we designed a recommender algorithm that suggests a neighborhood in New York City on the basis of users’ responses to nine short questions – about, e.g., security, rent, noise level, orcommuting time. This matching system has been featured in the New York Times and is to be applied in other cities.

"Dribia has excelled with their transparence, commitment, and outstanding quality work."

Sarunas Legeckas



Business problem

Users of digital sales outlets (websites or applications) only turn into buying clients if they find the product they look for within a reasonable time span. The question is, then, how to guide them to the right kind of product. One way to achieve this, is to create algorithms that incorporates their interests and search history.

Dribia's solution

For our client, Bkie – a Barcelona-based collaborative e-marketplace 2nd hand bikes – we have designed and implemented an algorithm that increases the visibility of relevant products. It does so on the basis of a client’s connectedness with other users, their preferences and their search history. This has increased their interaction and retention rate.

"Working with Dribia has opened our eyes about the possibilites of working with data. Their involvement has been key for the success of this project."

Minty Ascención

Project manager @ 500 markets


Educational problem

Today´s youth has to develop an interest in science, technology, engineering, and mathematics (STEM) to cover tomorrow´s need for talent in a technological and digital society. Given its importance, initiatives are needed that present STEM – and its consequent applications, such as data science – in an appealing, concrete, and engaging manner.

Dribia's solution

Dribia is a founding member of an educational project called “Beepath”. It allows students to conduct experiments involving human mobility through an mobile application that tracks human mobility. Dribia accompanies the analysis of the accumulated data. Various private foundations have so far financed the project.

"Without Dribia's team this project would have been impossible. We really appreciate their commitment and professionality."

Josep Perelló

professor @ University of Barcelona