Fleeter serves as a pivotal solution in the construction and mining industry by offering a comprehensive B2B marketplace for heavy equipment rentals. Our platform plays a dual role, benefitting both equipment owners and businesses seeking rentals. For equipment owners, Fleeter provides an efficient avenue to showcase their inventory and connect with potential renters, thereby increasing the utilisation rate of their assets. On the other hand, for businesses in need of equipment, Fleeter simplifies the procurement process by offering a wide range of options in one centralised platform. This streamlines the rental process, enabling businesses to quickly and easily find the equipment they require for their projects. Ultimately, Fleeter’s overarching goal is to optimize the utilization of heavy equipment assets while simultaneously facilitating seamless transactions and rental experiences for all stakeholders involved in the construction and mining sectors.
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"Monthly Active Rentals" (MAR) is a key performance indicator (KPI) that measures the number of unique rental transactions or engagements that occur on Fleeter's platform within a given month. This metric helps assess the platform's activity and growth by tracking how many pieces of equipment are actively being rented out and utilized each month.
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​Monthly Active Rentals (MAR): The total number of unique rental transactions completed on Fleeter's platform within a calendar month.
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Fleeter has seen a dip in the monthly active rentals, one of the primary North Star metrics that directly corresponds to Fleeter's revenue. The MAR for May 2024 was 50 and it fell down to 25 for June 2024.
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May 2024
City | Total Users | Monthly Active Rentals |
---|---|---|
Chennai | 60 | 35 |
Namakal | 15 | 5 |
Thanjavur | 25 | 10 |
Total | 100 | 50 |
June2024
City | Total Users | Monthly Active Rentals |
---|---|---|
Chennai | 60 | 15 |
Namakal | 15 | 10 |
Thanjavur | 25 | 5 |
Total | 100 | 25 |
In June 2024, Fleeter experienced a significant decline in its Monthly Active Rentals (MAR), dropping from 50 in May to 25. This decrease in one of our primary North Star metrics indicates a potential issue impacting user engagement and directly affecting our revenue. Identifying and addressing the underlying causes is critical to restoring and improving our platform's performance.
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If we introduce city-specific targeted marketing campaigns and promotions, then the Monthly Active Rentals (MAR) in Chennai, Namakal, and Thanjavur will increase by at least 20% each month, because tailored campaigns will address the unique needs and preferences of users in each city, thereby driving higher engagement and rental transactions
The goal of the experiment is to increase the Monthly Active Rentals (MAR) across all cities, with a particular focus on Chennai, Namakal, and Thanjavur, by at least 20%. This aligns with the overall business objective of enhancing revenue and utilization rates of the platform. By addressing city-specific needs and preferences through targeted marketing campaigns and promotions, we aim to drive higher engagement and rental transactions, thereby contributing meaningfully to Fleeter's growth and revenue goals.
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This experiment is directly aligned with Fleeter's primary business objective of increasing revenue through optimized utilization of equipment rentals. By focusing on MAR, a key North Star metric, the experiment ensures that efforts are directed towards driving significant impact on the overall performance and profitability of the platform. This targeted approach avoids random metric optimization and concentrates on achieving a substantial and measurable improvement in a critical business area.
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To measure the success of our targeted marketing campaigns and promotions aimed at increasing Monthly Active Rentals (MAR), we will define both worst-case and best-case scenarios:
Worst Case Scenario:
Best Case Scenario:
We are testing the effectiveness of city-specific targeted marketing campaigns and promotions on increasing Monthly Active Rentals (MAR) in Chennai, Namakal, and Thanjavur.
To ensure sufficient statistical power, we will use the entire user base for each city. Since our total users are relatively small, using the entire user base ensures more accurate results.
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Sample Size for Experiment:
The experiment will run for a duration of one month, from July 1st to July 31st, 2024, or until we reach statistical significance, whichever is earlier.
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