A Modern Approach to Private Company Taxonomy
Introduction to taxonomy and challenges in classifying private companies
Private businesses are always on the cutting edge, innovating and changing faster than the market can anticipate. Investing in private companies is exciting but also challenging due to the constantly evolving nature of their business models and the limited availability of information. To help investors make informed decisions that can lead to profitable ventures, taxonomy helps classify companies based on their unique characteristics, industry affiliations, and business models. With this tool at their fingertips, investors can quickly spot the right investments to deep dive into, pinpoint rivals to keep an eye on, and stay ahead of relevant competitors.
For instance, an investor interested in early-stage K-12 EdTech companies can utilize detailed classifications to quickly find companies that meet their specific criteria. This helps investors objectively compare and benchmark companies within the same industry.
Business taxonomy, therefore, becomes the bedrock of investment analysis, providing a structured framework to categorize and understand companies based on their unique characteristics.
The unique challenges with private company taxonomy
Because private companies operate in rapidly evolving industries with unique business models, the challenge arises in developing adaptable taxonomies that keep pace with frequent changes in private business models. Especially in the realm of startups, investors face obstacles stemming from limited information availability and the absence of global standards, as well as the subjectivity of classification, potentially leading to misrepresentations or under-representations of unique business models. For instance, classifying Stripe only as a specialized finance company fails to convey its core business proposition. Stripe has evolved from finance to a payment gateway and now also provides banking as a service.
Public companies are easier to understand because they must disclose their operational and financial information to regulators. On the other hand, private companies are not required to disclose the same level of information, leading to limited available data about their operations. Public investors have a smaller pool of companies to choose from, which allows for broader classifications. However, for private companies that are constantly evolving, this broad, sub-optimal classification could lead investors to miss important details when identifying investment opportunities.
Current taxonomy systems for private companies: We need to look beyond!
Private market investors often turn to popular classification systems followed by major industry players like Pitchbook, and CB Insights. These players focus on industries, verticals, and keywords to map a company by going up to 2-3 levels deep into their business models.
This is a great starting point for investment research. However, the following are needs that emerge from these systems:
Granularity:
Investors look for deeper classification models that help them with granular information about a company’s current and emerging business models.
Adaptability:
Startups operate across business models that are continually evolving. Investors want classification models that can be updated frequently and reflect these emerging business models with new industry tags.
Up-to-Date:
Investors seek the latest information on a company’s current line of business and industry affiliations. With startups rapidly changing their business models and operations, classifications need to be capable of promptly tracking and reflecting these changes in company tagging.
Connected:
Traditional taxonomies rely on a keyword-based approach that fails to capture the connected view of industries and sub-industries. Investors look for a connected approach to taxonomy.
Building the foundation for a modern taxonomy with Synaptic
At Synaptic, we deploy a proprietary taxonomy to overcome the challenges with the current systems. We allow you to go up to 10 levels deep into business models to capture all possible areas in which a company operates. Below are the core principles that underline our classification system:
#1 Dynamic business model mapping:
As private companies innovate and develop new business models, Synaptic refreshes itself to classify them into newer and more relevant categories.
#2 Multi-level classification:
Synaptic goes up to 10 levels deep into business model classification to provide granular information on a company’s area of operations, as illustrated in the figure below.
#3 One-to-many mapping:
One company operating across multiple lines of business is mapped to multiple categories instead of a single industry or vertical.
Let's comprehend the above principles using an illustration of the hierarchical taxonomy approach using Stripe.
Figure: Synaptic classification of business models mapped to Stripe.
Stripe was launched to simplify payment processing for businesses and individuals by providing an intuitive payment platform. The company's founders recognized challenges in the existing payment infrastructure and developed a platform that could be easily integrated into any website or mobile app using just a few lines of code, facilitating online payment acceptance.
Consequently, Stripe falls under the Payment Gateway category (Financial Industry > FinTech > Payments > Payment Gateway) in traditional taxonomies. As the company expanded its services over time to include invoice management and banking-as-a-service, Synaptic's modern approach allowed for multiple mappings to capture all five functionalities of Stripe in various categories.
Leveraging taxonomy as a competitive advantage
A well-designed taxonomy system enables investors to organize and prioritize potential investments, streamlining the process of identifying promising opportunities.
Deal sourcing:
By implementing comprehensive company classification, investors can quickly filter and sort through large amounts of data to focus on the most promising investment opportunities and save time. This ensures that they can identify and act on potential deals sooner.
Figure: Leveraging the Synaptic filters on comprehensive classifications to source edtech companies in North America
Competitive benchmarking:
A reliable business classification system provides the primary advantage of allowing investors to compare similar investment opportunities. With an inadequate classification system, investors may encounter comparisons that are either too broad or misaligned between companies with different business models.
For example, comparing Uber to a corporate taxi service is not an effective strategy for determining which company to invest in because their fundamental business models are different. Similarly, comparing Netflix to a traditional media company like Warner Media is inaccurate.
Figure: Similar companies suggested by Synaptic for competitive benchmarking
Market intelligence:
A comprehensive business classification system also aids investors in recognizing patterns and trends within the market. In-depth analyses of industry hierarchies can reveal emerging business models and trends, increasing the chances of investment success.
Figure: Employee counts for major companies in the online streaming services to evaluate hiring trends
Conclusion
In conclusion, Synaptic taxonomy can benefit investors seeking investment prospects in private companies. The use of detailed and comprehensive classification standards helps investors gain a deeper understanding of company business models, allowing them to tailor their investment plans accordingly. This valuable resource has a direct impact on the success of investment firms and leads by allowing them to make better-informed decisions.
Synaptic is a prominent player in the alternative-data-based investment ecosystem with a far superior taxonomy. It not only saves investors hours of effort but also offers them a considerably more diverse and informed choice of companies for each sector.