The Power of Data for Marketplace Growth: A 10-Year Retrospective
The Secret to Marketplace Growth: Unit Economics and the Power of Data
After spending a decade building four different marketplaces, spanning from FMCG, hospitality, commercial real estate, and healthcare, I have noticed a common theme in terms of growing a marketplace business: it all boils down to achieve healthy unit economics and to find the right levers influencing it.
Unit economics is the profitability of a single transaction. In order for a marketplace to be sustainable, the revenue from each transaction must exceed the cost.
This may seem obvious, but it is important to remember that unit economics are not always fixed. There are a number of levers that marketplace businesses can use to improve their unit economics, such as increasing average order value, reducing costs, and improving take rate.
Data-Driven Decision Making
The key to improving unit economics is to make data-driven decisions. This means using data to understand what is driving revenue and costs, and then using this information to develop and test strategies for improvement.
One way to do this is to identify the primary, secondary, and supporting metrics for your marketplace. Primary metrics are the most important metrics for your business, such as revenue, cost, and profit. Secondary metrics are metrics that are correlated with your primary metrics. Supporting metrics are metrics that can help you understand and improve your secondary metrics.
For example, one of your primary metrics might be average order value. Secondary metrics that could be correlated with average order value include number of SKUs per order, average price per SKU ordered, sold quantity per SKU per order, and weight per SKU per order. Supporting metrics that could help you understand and improve your secondary metrics include product descriptions, customer reviews, and promotional offers.
Once you have identified your key metrics, you can use data to understand what is driving them. For example, you could use linear regression to measure the correlation between your secondary metrics and your primary metrics. This would give you a better understanding of which supporting metrics have the biggest impact on your average order value.
Once you know which supporting metrics are most important, you can start to develop and test strategies for improvement. For example, if you find that number of SKUs per order has a strong correlation with average order value, you could test offering product bundles or discounts on multiple SKUs.
Case Study
In one of the marketplaces we built, we were able to reduce logistic cost by 71% by leveraging data to optimize our shipping process. We started by doing a deep dive into our data to identify the factors that were impacting our logistic cost the most. We found that weight and take rate per shipment had the highest influence.
Once we had identified these factors, we started to develop and test strategies for reducing them. For example, we onboarded more lightweight SKUs and offered volume-based pricing for buying more quantities. As a result of these changes, we were able to significantly reduce our logistic cost and achieved positive contribution margin.
Conclusion
Leveraging data is a powerful tool for improving unit economics and growing a marketplace business. By understanding what is driving revenue and costs, marketplace businesses can develop and test strategies for improvement.