Why hyperlocal intelligence is crucial for smart business planning

Traditionally, location has always been a mainstay of some of the biggest industries – whether it’s retail, real estate, or banking. But, with the onset of the COVID-19 pandemic, spatiality has started to take center stage like never before. Whether it’s creating containment zones or planning vaccination campaigns, the only way to fight the pandemic has been to quickly understand the reality on the ground and take decisive action. But that’s not all. Today, companies across industries are able to tackle some of the toughest business and operational challenges with a lot of help leveraging location-based intelligence, specifically hyper-local intelligence.

Despite its relevance, hyperlocal intelligence has not received its proper meaning until now. This is especially true in the Indian context, where prior to the pandemic, many companies in all industries had not fully realized the need for technology such as hyperlocal intelligence, with the retail sector being seen as a major concern. ‘exception. Even there, the use cases were limited to helping companies identify the right locations for their expansion plans, trying to figure out what products needed to be stocked based on use in the region.

Why the universal nature of data helps promote hyperlocal intelligence

The data that hyperlocal intelligence relies on is industry independent; the ideas or information that is generated may be sector specific. For example, while the attendance data point does not change regardless of what industry you want to mine the data for, that data point has different but equally important implications for different industries – from retail to retail. mobility through real estate.

As a startup that works at the intersection of Artificial Intelligence (AI) methodologies such as Optical Character Recognition (OCR) and Natural Language Processing (NLP) to discover raw data sources and calculate socio parameters -economic, we were able to take advantage of this universal nature of data to feed our B2B location data engine.

Data Sutram’s data engines cleanse, process, and geolocate data from multiple sources and combine it with AI and ML methodologies to create actionable and accurate data and insights for every location. Our data engines have the ability to process data in any form, collected from any unstructured repository, and convert it into payload forms. It further combines the platform’s 200+ multiple data fields interactively to bring out over 150 insightful indexes applicable to any geography at a fine and granular level, making it very comprehensive to understand and to read. Its granular data and custom industry-specific verticals help reduce the time it takes for organizations to adapt to data-driven decision making. The product architecture allows for end-of-the-mile customization, meeting business needs. Additionally, our engagement with NetApp Excellerator further helped strengthen the platform by exploring some of NetApp’s key snapshot and security offerings.

Today, businesses around the world increasingly realize the need for hyperlocal intelligence with restricted movement and lockdowns, challenging the deployment of field workforce to leverage hyperlocal data. for all business decisions. However, one of the less talked about use cases for hyperlocal intelligence has been in the merchant lending space. With the pandemic putting an end to all non-essential trading activities, the memory became a huge puzzle for financial lenders to understand exactly which traders were most likely to default. They were forced to revisit the age-old issues they had traditionally relied on to process loan applications. This is where location intelligence became relevant.

Armed with granular spend capacity, footfall, precise location of merchant data, and more, financial lenders were better equipped to make informed decisions. In addition, financial companies were also able to track and acquire traders virtually based on location indicators with little loan history and a non-intrusive control process. As a startup that today has expertise in hyperlocal intelligence, we have been able to work with financial institutions, especially those focused on lending money, to use location scorecards to assess and approve loan applications in minutes. Merchant payment companies were able to integrate high potential merchants based on the business activity of the location.

How hyperlocal intelligence works

The answer lies in understanding the two parts of hyperlocal intelligence – granular location data (DNA locations) and geospatial intelligence.

In today’s world, we are constantly monitored by the various devices around us, from cell phones in our hands to satellites in the sky. These devices capture information about our movements, our behavior and the evolution of life. Creating location data involves working with these multiple data sources such as satellite, mobile mobility, places of interest, etc., processing and blending them to create metrics of consumer activity at granularity. of 100 m. The next part is to develop business insights and actionable insights by modeling key business performance indices like monthly store sales, loan risk, etc. depending on the use case.

As a business, one of the benefits of using hyperlocal intelligence is the limited reliance on end customer data. For example, in most use cases in merchant acquisition that seeks to identify demand or demand detection as we call it, end customer data is only used to model location metrics. so that the bank or NBFC can start with little or no data.

This is why today, hyperlocal intelligence presents itself as a tool that can answer some of the most common questions that arise in running a business. By aggregating multiple sources of information, it is now possible to understand what is present in a place: human behavior, supply bottlenecks, operational issues at a hyperlocal level, all within a framework of anonymization and of security. This helps answer a number of questions. This includes such a question as the ideal location for my business – whether it is a bank planning to install an ATM, a food delivery service planning its cloud kitchen; is my field workforce knocking on the right doors – as in the case of an NBFC looking to target traders? am I targeting the right people – as in the case of brands that seek to identify consumers and determine their buying trends.

A long overdue change

In an age when resources like hospital beds, intensive care units, and even services like ATMs must be planned for the reality on the ground, hyperlocal intelligence has a more important role to play than ever before. . But this is true for businesses across the board, as they seek to strategize to survive and thrive in a very difficult business environment. The pandemic has only catalyzed this change, but it is long overdue. And hyperlocal intelligence is poised to drive the next big wave in the digital transformation narrative.


About Geraldine Higgins

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