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.
In the aftermath of a disaster, access to relevant, high quality and timely information can greatly enhance the speed of emergency response by agencies and the effectiveness of government policies. The rise of signals and sensing capabilities, such as through privacy-compliant cell phone and GPS data can provide rich and rapid information about human location, activity and mobility. In a disaster recovery context, analytics based on mobility data can underpin socio-economic impact analysis.
The activity heat map displays normalized activity profile of Ambon Island for an average 24-hr day in Sept. 2019. Data are aggregated into hexagons, which are colored based on the count of unique devices by hour in each cell. This method highlights the most and least used locations at any moment in time. In the map above, yellow cells represent areas of high activity, or locations with the greatest number of people over the averaged 24-hr period. Source: Derived from Quadrant’s mobile location data.
Mobile app development and maintenance is a resource intensive and time-consuming process – which is why the primary objective of publishers is maximising the revenue they generate from their apps. One of these is data monetization.
Data monetization, however, is not what usually comes to mind first. Since several successful platforms like Spotify, Tinder, and Netflix use subscriptions, one might be inclined to believe this is the most common monetization strategy. However, out of the $111 billion generated in mobile app revenue in 2020, subscription-based apps on both Apple’s App Store and Google Play collectively earned only $11.7 billion. This statistic offers a key insight: subscription models capture the imagination but only account for approximately 10% of all revenue generated from apps. Therefore, it is important to explore alternative models for generating revenue.
Cities worldwide are dealing with rapid urbanization, changing travel patterns, and most recently the aftermath of a global pandemic. As cities sprawl outwards to form low-density localities, it is difficult and expensive to serve these suburbs. Transit systems were also one of the worst-hit sectors by Covid-19, and post-pandemic recovery has been complicated due to remote and hybrid working.
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