Welcome to the Location Data Blog!

The ride-hailing industry is characterized by stiff competition and new businesses are entering the fray every year. By 2026, the market size for ridesharing services is expected to more than double compared to 2021. For companies to thrive in this fiercely competitive landscape, they must optimize their routing systems to expedite pick-ups, match demand, and deliver more rides per driver for maximum profitability.  

Ridesharing services need accurate and up-to-date POI data to function. However, the underlying maps that enable their operations are outdated, and changes in the physical world are not reflected nearly as quickly as needed. A lack of current and contextual information can cost rideshare companies in terms of lost driver productivity, rider churn, and overall operational inefficiency. 

Business Intelligence (BI) and data science companies harness location data to help their clients understand target audiences better. Insights derived from analyzing human mobility patterns can help retailers, FMCG, online services, and many other companies conduct effective marketing campaigns, expand to new areas, measure ROI, find underserved consumers, and more. 

A screenshot of Mapoteca’s analytics platform showing O-D analysis for specific POIs based on mobility data. 

Out-of-Home (OOH) advertising or outdoor media is integral to the multi-pronged marketing strategies adopted by consumer-facing businesses. Research has found that OOH drives more online activity per ad dollar spent than any other media. It is 382 percent more effective than TV, 200 percent more effective than print, and 63 percent more effective than radio ads in driving customers to an online platform. Outdoor media is instrumental for businesses to increase awareness of products and services - both online and offline. The market size is expected to reach US$ 33 Billion by 2027, exhibiting a CAGR of 13.41% during 2022-2027. 

POI data acts as the fundamental building block for digital mapping and navigation platforms. One of our clients – a prominent European mapping and navigation company – wanted to enrich their platforms by procuring a high-quality POI dataset covering several regions in Brunei. To help them achieve this objective, we launched a POI collection campaign in the city (without an already established presence) and successfully produced a dataset of 1500 verified POIs, all with photos. We reached a completeness level of 99.3%, far exceeding the industry standard.  

As users, we are not surprised to discover that a restaurant or a store on the map does not exist in the real world. It might have closed, moved, or never existed in the first place. Low quality POI datasets might be a mere inconvenience in our personal lives; however, this is a multi-million dollar issue for businesses.

Until recently, we couldn't even tell how big the problem is. After collecting and verifying 5,000 electric vehicle charging stations in Amsterdam in person, we have an answer: it is enormous.

We discovered that more than 14% of the locations in the city’s database were incorrect, and more than 11% of the data from a popular mapping platform was outdated. And this is just the tip of the iceberg.