<p>Effective participation requires intelligence in any market. This is particularly true in private markets, where information about investors, companies and transactions is scarce and not easily available for research. Investors use market intelligence for many use cases including building a solid deal flow pipeline, developing a view of the market, and benchmarking other investors.</p>.<p>Consider an investor with an interest in SaaS (Software-as-a-Service) sector: 1) looking for growing startups in the sector above Rs 1 crore of Average Recurring Revenue (ARR) and growing at more than 50% annually - a base list; 2) finding competition of these companies to understand their general growth, models and valuation - a market map; 3) comparing investments and returns in the sector based on deals that are made in the recent past - a deals and returns reference; and 4) getting a reasonable view of the market on performance metrics, entry valuation range in the sector and further shortlisting from the list of companies to consider for investment - an informed market view.</p>.<p>This intelligence need is there for companies that are seeking investments as well. Founders in active fund-raise mode will need a base list of investors to reach out to, understanding their own market (potential size, competition and substitutes) and building their projections and models accordingly from that understanding, and getting to a reference value for their own business and initiating conversations with only the high probability investors who are active in the market currently.</p>.<p>Such research, for both investors and companies, will of course be constrained by data availability and the quality of the data available. Adding more people to research is one inefficient way to develop broad intelligence. Relying on a Google search or an expert go-to person or network always adds biases and there is always a potential to miss out on large chunks of the market in the process.</p>.<p>Even if the data quality problem is solved somehow, coverage of the intelligence is the next challenge. The key question is: How can one be sure all companies/investors/deals are considered for the research?</p>.<p>Therefore decisions made with such intelligence are standing on flaky data foundations and can be detrimental to portfolio performance.</p>.<p>The second set of challenges takes the form of risks and compliance. For example detecting fraudulent behaviour, understanding complex company/deal structures, uncovering competing investments made by an investor etc can turn out to be show-stoppers.</p>.<p>If investors pursue some form of due diligence at the time of investment, they are in a way covered for the risks. But the same is not true for companies looking at investors, when full portfolio information, general investment behaviours like preferred cheque sizes, stage of entry into companies, time taken for decision-making and investment propensity are not available broadly. Without such information, founders end up spending way too much time with investors and finally find them to be irrelevant or not-so-suitable partners, given their needs. This, unfortunately, takes away time from tasks like product and business development, which are critical in the early stages.</p>.<p>Just like how retail investors have terminal access to public market data around stock prices, volume-traded and fundamentals of the company, there are services available for accessing private company data as well. These go a long way in addressing the challenges especially if coverage and access are guaranteed. Seasoned investors rely on such technology where data flow and processes are automated and quality checked. Imagine a system with 100+ data sources to be crawled, quality-checked, and cross-referenced for consumption by investors.</p>.<p>Clearly, the technology itself is not trivial and the automation required for building and maintaining the data is complex. But such intelligence through technology allowing screening and filtering can go a long way in better decision-making. This enables them to quickly pass through the first three steps and get to judge the market opportunities better, with sufficient intelligence.</p>.<p>As India's startup ecosystem grows rapidly, market intelligence acquisition and its integration into investment processes will become the norm. This is necessary for the ecosystem to both de-risk and scale deal discovery and deployment effectively.</p>.<p><span class="italic"><em>(The writer is the founder of PrivateCircle.co)</em></span></p>
<p>Effective participation requires intelligence in any market. This is particularly true in private markets, where information about investors, companies and transactions is scarce and not easily available for research. Investors use market intelligence for many use cases including building a solid deal flow pipeline, developing a view of the market, and benchmarking other investors.</p>.<p>Consider an investor with an interest in SaaS (Software-as-a-Service) sector: 1) looking for growing startups in the sector above Rs 1 crore of Average Recurring Revenue (ARR) and growing at more than 50% annually - a base list; 2) finding competition of these companies to understand their general growth, models and valuation - a market map; 3) comparing investments and returns in the sector based on deals that are made in the recent past - a deals and returns reference; and 4) getting a reasonable view of the market on performance metrics, entry valuation range in the sector and further shortlisting from the list of companies to consider for investment - an informed market view.</p>.<p>This intelligence need is there for companies that are seeking investments as well. Founders in active fund-raise mode will need a base list of investors to reach out to, understanding their own market (potential size, competition and substitutes) and building their projections and models accordingly from that understanding, and getting to a reference value for their own business and initiating conversations with only the high probability investors who are active in the market currently.</p>.<p>Such research, for both investors and companies, will of course be constrained by data availability and the quality of the data available. Adding more people to research is one inefficient way to develop broad intelligence. Relying on a Google search or an expert go-to person or network always adds biases and there is always a potential to miss out on large chunks of the market in the process.</p>.<p>Even if the data quality problem is solved somehow, coverage of the intelligence is the next challenge. The key question is: How can one be sure all companies/investors/deals are considered for the research?</p>.<p>Therefore decisions made with such intelligence are standing on flaky data foundations and can be detrimental to portfolio performance.</p>.<p>The second set of challenges takes the form of risks and compliance. For example detecting fraudulent behaviour, understanding complex company/deal structures, uncovering competing investments made by an investor etc can turn out to be show-stoppers.</p>.<p>If investors pursue some form of due diligence at the time of investment, they are in a way covered for the risks. But the same is not true for companies looking at investors, when full portfolio information, general investment behaviours like preferred cheque sizes, stage of entry into companies, time taken for decision-making and investment propensity are not available broadly. Without such information, founders end up spending way too much time with investors and finally find them to be irrelevant or not-so-suitable partners, given their needs. This, unfortunately, takes away time from tasks like product and business development, which are critical in the early stages.</p>.<p>Just like how retail investors have terminal access to public market data around stock prices, volume-traded and fundamentals of the company, there are services available for accessing private company data as well. These go a long way in addressing the challenges especially if coverage and access are guaranteed. Seasoned investors rely on such technology where data flow and processes are automated and quality checked. Imagine a system with 100+ data sources to be crawled, quality-checked, and cross-referenced for consumption by investors.</p>.<p>Clearly, the technology itself is not trivial and the automation required for building and maintaining the data is complex. But such intelligence through technology allowing screening and filtering can go a long way in better decision-making. This enables them to quickly pass through the first three steps and get to judge the market opportunities better, with sufficient intelligence.</p>.<p>As India's startup ecosystem grows rapidly, market intelligence acquisition and its integration into investment processes will become the norm. This is necessary for the ecosystem to both de-risk and scale deal discovery and deployment effectively.</p>.<p><span class="italic"><em>(The writer is the founder of PrivateCircle.co)</em></span></p>