Data at Work

The world of data and its many applications. This blog will help you learn how visionary companies are utilising external data to enhance business operations.

What Google's enhanced data privacy framework means for publishers

In July 2021, Google announced that it would update the data safety section applicable to apps on their Play Store. The company stated that these policies would come into effect in late April 2022, and it followed through on that declaration. Last month, numerous apps were removed from the Play Store for breaching Google’s updated data privacy and data processing policies.  


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A comparison of POI solutions on the market

Point-of-Interest (POI) data is instrumental in facilitating the operations of businesses such as food and last-mile delivery companies, those that develop mapping and navigation software, ridesharing companies, and many others. In other industries, such data is harnessed to derive insights to inform decision-making around site selection and supply chain optimisation.  

However, procuring good quality POI data is a significant challenge.  

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Preview: The big book of Point-of-Interest data use cases

Point-of-Interest (POI) data is the digital representation of physical spaces that are of interest to individuals, businesses, and governments – such as malls, restaurants, train stations, residential complexes, hospitals, and schools. In other words, a POI can be anything that someone wants to find on a map. POI data acts as the lynchpin of operations in several industries, including ridesharing, last-mile delivery, logistics, real-estate, retail, marketing and the public sector. Even companies whose business model is not primarily built on POI data can still harness it to glean insights that offer a tangible, competitive advantage. Data scientists generate meaningful insights on the distinct characteristics of neighbourhoods, people’s movement patterns, and an area’s vulnerability to natural disasters by analysing POI data alongside mobile location data, demographics, purchase data, and environmental records.

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Dashboard: Footfall analysis for two competing fast-food brands in Charlotte City

Footfall analysis is a powerful form of business intelligence that allows brands to understand the visitation patterns around various POIs (Points-of-Interest). For retail stores, restaurants, and other POSs, footfall analysis can highlight important patterns such as the busiest time of day, competitor traffic analysis, and more. Whereas for government and public agencies, footfall analysis can highlight the consumption and demand of public services for the betterment of citizens’ lives.


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How retail banks increase their competitive edge with location intelligence

Similar to other industries, financial services have been leveraging mobile location data to improve its operations and services.

Investment firms analyse mobility data in conjunction with POI data to forecast revenues for various retail outlets. This enables these companies to determine which businesses will deliver a good ROI.

Retail banks utilise location data in a number of ways. An important application includes limiting or preventing fraudalent transactions. Retail banks compare the IP address of a Point-of-Sale (POS) with the GPS coordinates provided by a customer's phone to prevent credit card fraud.

Banks rely on location intelligence to drastically improve the experiences they provide their customers. Here are three examples of how retail banks can use mobility data to enhance customer service and increase competitiveness. 

In each example, anonymized mobility data around Downtown Los Angeles between 1 October 2016 and 31 October 2016 was used.

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