This platform for location intelligence helps companies make precise decisions by using customized AI

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If a restaurant owner doesn’t know that the students of the nearby coaching center frequent the establishment, the vendor could not profit from the potential. This isn’t a unique issue, but rather a problem that many companies, across sectors, have to face today – lack of access to accurate real-time information that isn’t available to their.

Companies seek solid data models that allow effective decision-making across different geographies and demographics of customers. But effective models require quality data in order to provide the desired outcomes. Much of the data is not stored in databases of companies and is dispersed, unorganized, and unstructured.

Researchers in data science Tusheet Shrivastava Ankita Thakur as well as Devashish Flororia recognized this gap in 2018, and put in place GeoIQ GeoIQ is a location intelligence platform that assists businesses make precise decisions by using customized AI for location.

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A wealth of data, topped by AI and ML

According to Bengaluru-based company, the foundation for its system is data. There are more than 3,300 attributes covering demographics income infrastructure, commercial activity rental, and more. Available at street-level detail, and with 100% coverage across the nation.

GeoIQ utilizes its own algorithms to layer data from more than 600 government and private information sources, satellite imagery and much more to produce extremely granular data sets that distinguish the users of one street from the next.

The machine-learning (ML) engine can identify the ‘why’ that lies behind the ‘where’ and thus uncovering patterns in data from business. For instance for example, the ML engine could reveal how the amount of guests at the hotel XYZ increased on the 12th of September because of music festival just 100m away. Also, it could demonstrate that sales of the XYZ Burger Joint doubled during the month of September because there was a new training centre that opened adjacent to it.

In addition, ML models can also assist businesses identify the user’s behavior, affluence as well as fraud and potential for business at an address level. This all aids businesses to make informed decisions about which customers to be targeting, when to target them and in what way.

Inception

Tusheet as well as Devashish are both graduates from IIT Kanpur. Their paths crossed several times which led them to become acquainted to each other on a professional level. In the meantime, Ankita and Tusheet, friends from their time at school were discovering real-world issues that were threatening market participants in Indian market. In the end, Devashish, Ankita, and Tusheet worked together on the fields of access to data and hyperlocal intelligence across industries and markets.

With their collective with more than 30 years working in deep tech Three of them have seen the negative consequences on data inaccessibility on business. They discovered that most Indian companies depend on internal data in order to come up with solutions to real-world issues. When third-party or public data sets were utilized in making crucial business decisions, companies noticed a 25% increase in the performance metrics that matter most to them.

This discovery inspired Devashish Ankita, and Tusheet to create a simple-to-use device that provides hyperlocal intelligence.

External data and attributes associated with ML

Devashish states “There is a need for externally reliable data that extends beyond the database of the company. There are a myriad of issues which could greatly benefit from this data.”

In addition to providing reliable data from outside sources, GeoIQ also offers more than 3,300 ML-ready properties through one API. Companies can play around with these attributes to determine the most relevant indicators to use for their specific needs.

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How does it work

GeoIQ collects data from over 600 sources–government-released data, public listings, open data, satellite imagery, surveys, and data partnerships. All of this data undergoes various levels of process, sanitation in order to verify its accuracy and reliability. The data is transformed to geo-centric information. It is then processed through GeoIQ’s ML engines, where the data is examined to identify anomalies, biases, and information that is missing.

The ML layer that is built on top of the algorithms that are proprietary converts the data into smart location attributes. This information is accessible via real-time APIs on the level of address (plot no street name, street name, building name pincode, city, state).

“Businesses can perform exploratory analysis, narrow down features, construct models using ML with various characteristics, and deploy the models as real-time APIs with just one click. The model that meets the criteria perfectly can be used to make a decision,” explains Devashish.

“Businesses can directly access our data APIs or our no-code platform for ML, which aids them in determining which aspect is most valuable to their business. It is possible to sign up with only an address and the behavioural element they want to anticipate and our no-code ML platform generates models.”

For instance, the profits of a burger establishment may be affected by factors like the the presence of coaching centres, brands as well as the typical price of meals in the area.

The team

Chief Executive Officer and Co-Founder of GeoIQ, Devashish Fuloria holds an undergraduate degree from the IIT Kanpur and a doctorate at Imperial College, London. He was previously co-founder of ZeLadder Sports, a consultant at TWI (UK) as well as a researcher in policy within the Royal Academy of Engineering (UK).

Co-founder and CDO at GeoIQ, Ankita holds a bachelor of engineering degree from Pune University. She is a professional in data science with more than 11 years of expertise in solving data-related issues in the retail industry, BFSI, and hospitality.

Co-founder and CTO for GeoIQ, Tusheet holds a bachelor’s degree in IIT-Kanpur. More than eleven years’ experience developing machine learning capabilities , as well as complete data development. At GeoIQ He is the head of innovation, technology along with product and technology development.

Revenue and growth

The startup provides users with an annual subscription that allows them to access APIs for data.

The company says it has achieved an increase of 10x in its annual regular revenue (ARR) over the past four quarters, and expects to record an additional 5X increase in ARR over the coming two quarters.

At present, GeoIQ has 30 clients that are mostly in the fields of fintech, insurance, and retail. GeoIQ has collaborated with some of the most fast-growing brands in India such as Lenskart, Zepto, DMI finance, Paytm, and Big Basket.

The funding process and the way forward

In May of this year the company raised $2.25 millions from Lenskart. Existing investors, like 9Unicorns as well as Ecosystem Ventures, took part in the round. In November, 2020 the location intelligence startup raised the sum of Rs 2.5 crore under the leadership of 9Unicorns.

The market for location intelligence is expected to grow to $51.25 billion in 2030, and is expected to grow at a rate of 15.6 percent, according to an analysis by Grand View Research Inc.

GeoIQ will set its sights on expansion across the globe, beginning with the US in FY23.

In terms of competition Devashish declares, “This is a niche and still a young marketplace in India. There are only a handful of players who can offer advanced capabilities through one platform.”

Devashish is considering the New York based Carto as a rival. Their platform lets businesses save, enrich, analyse and visualize data in order to make more spatially-aware choices. Our method is more data-science-based which means that we let our AI engines anticipate answers that are provided via APIs.

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