How Location Data Can Inspire Entrepreneurs in Small Towns

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Startups in Tier II and III cities have mainly focused on solving local problems through local solutions. Some of these can be replicated and extended to work on global problems. Such patterns have encouraged the startup ecosystem in these cities to survive, scale and thrive. According to the recent data released by the Department for Promotion of Industry and Internal Trade (DIIPT), 555 districts of India have at least one new startup. These numbers are expected to grow and unlock possibilities beyond the metros. Recognizing the opportunities in such cities, industry leaders are now looking for effective entry points into these untapped domestic markets. But there are some challenges which hinder this.

Major Challenges: Lack of awareness, infrastructure, incubators and accelerators for the startup ecosystem has been a hindrance for startups in Tier II and III cities. As these challenges are resolved over time, the immaturity of these markets in terms of data constraints, changing customer behavior and viable entry points still remains a challenge.

The major barriers to entry in these markets are as follows:

One, it’s hard to get a good understanding of customer behavior.

Two, cosmopolitan data, insights and trends are generally inappropriate for these new markets and organizations’ internally generated data for such markets are often devoid of real-world insights.

Third, the available data is scarce, inaccurate, incomplete, non-conforming, duplicated or of poor quality.

Fourth, traditional methods of obtaining data are cost-intensive; For example, field survey.

Five, markets are new, untested and driven by gut-based decisions.

Overall, the lack of data in Tier II and III cities reduces investment prospects and significantly increases the risks and costs of entrepreneurship.

There are many questions and obstacles that can be resolved if businesses and investors have access to quality data and sophisticated analysis capabilities. Access to data is not enough, it is important to gain insights from it to solve business problems. Data solutions providers are developing sophisticated artificial intelligence (AI) and machine learning (ML) capabilities to enable real-time analytics on petabytes of data.

Furthermore, most real-world data is unstructured and therefore not directly consumable. This data needs to be collected, stored, processed and transformed into a usable form from multiple sources. After all this, the data is ready to feed to the prediction model for insight.

Location data and intelligence can be a major investment accelerator: Access to reliable, effective and actionable market intelligence for all stakeholders is the key to fueling entrepreneurial ambitions in Tier II and III cities. To enable this data-based approach, provide answers to complex problems and reliable predictions for location analysis and intelligence and logic-based decisions.

Location data can help provide important insights to entrepreneurs and investors alike. For example, they can gain a better understanding of market size, target audience presence, and competition. Entrepreneurs can gain actionable insights on customer behavior, manufacturing prospects and capabilities, existing businesses and how they are performing, and effective business models, among others. Sophisticated AI/ML capabilities enable forecasting models to assess risk and forecast revenue and profits based on the characteristics of a specific location.

With a large level of location information, businesses can anticipate the risks and opportunities associated with being present in that specific location. They can also identify important user behaviours, patterns and richness in these new areas. Businesses can identify the exact catchments where their target audience is present, rather than targeting their efforts to the entire urban area of ​​the city within a geographic range.

Today, there are data solutions providers in India that provide custom solutions equipped with AI capabilities for businesses across all sectors. These data solutions can provide better foresight and enable quicker market adjustments while reducing overall risk and research costs.

Location data can therefore be a game changer in solving some of the pressing problems in the analytics and intelligence industries and achieving prediction accuracy. Some of the big issues being addressed by Location Intelligence are credit risk and fraud prediction, site selection and retail expansion, lead prioritization, hyper-local digital and out-of-home targeting, and more. The application of real-world data with ML capabilities can help investors, entrepreneurs and other stakeholders accelerate business growth as they enter Tier II and III markets.

Ankita Thakur is the co-founder and CDO of JioIQ.

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