Cracking the Code: GTV vs GMV

Recently, a friend challenged me, saying, "You finance folks have a knack for making simple things complex." We were ordering party essentials from Zepto and paid for the same through Paytm, leading us into a conversation about the difference between GTV and GMV.

In the startup world, two crucial metrics to measure a company's growth often get mixed up: Gross Transaction Value (GTV) and Gross Merchandise Value (GMV).📈

But what do these terms mean, and how are they different?

🔍 GTV represents the total value of transactions on a platform, including fees and commissions. It captures the overall monetary worth of all the transactions, regardless of whether they involve goods or services sold by the platform or its sellers. GTV is typically used by companies that facilitate transactions without holding inventory.

🔍 GMV on the other hand, represents the total value of merchandise sold on a platform, excluding additional charges like taxes, shipping fees, or discounts. It measures the volume of goods or services sold, regardless of the revenue generated. GMV is commonly used by companies that sell goods and maintain inventory.

💡 Companies that sell goods usually have a lower GTV to GMV ratio compared to those facilitating transactions. For instance, let's take Company A, an online retailer with a GTV to GMV ratio of about 0.7. On the other hand, Company B, a payment facilitator, might have a GTV to GMV ratio of about 0.9.

🌟 In the startup ecosystem, GMV and GTV are often used interchangeably, but the distinction matters. However, understanding these metrics is crucial for investors, founders, and anyone interested in the startup ecosystem. It enables us to evaluate the scale, revenue generation, and efficiency of the business, leading to better-informed decision-making. Remember, the company's business model ultimately determines whether it's GMV/GTV or actual revenue that prevails.

So, the next time you come across GTV and GMV in startup discussions, you'll be armed with the knowledge to decode these metrics! 💪🔍

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