Difference between revisions of "Analysis of User and Merchant Dropoff for Sugar App Methodology"
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| − | ==<div style="background: #95A5A6; line-height: 0.3em; font-family:helvetica; border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#F2F1EF"><strong> | + | ==<div style="background: #95A5A6; line-height: 0.3em; font-family:helvetica; border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#F2F1EF"><strong>Introduction</strong></font></div></div>== |
| + | The key aim of this project is to tackle the three problems above and increase the voucher redemption rate, customer retention rate and merchant retention rate. | ||
| − | ==<div style="background: #95A5A6; line-height: 0.3em; font-family:helvetica; border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#F2F1EF"><strong> | + | As the nature of our study differs in some ways to existing literature reviews, we will make adjustments to the pre-existing methods of survival analysis due to the limitations of our scenario. |
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| + | ==<div style="background: #95A5A6; line-height: 0.3em; font-family:helvetica; border-left: #6C7A89 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#F2F1EF"><strong>Limitations</strong></font></div></div>== | ||
| + | Our first limitation is, unlike subscription based services, Sugar provides the app to users for free. Users can use the app indefinitely or choose to uninstall it. However, at this present time, there is no way for Sugar to track their uninstallations. This means that Sugar has no way of telling when a user has dropped off for real. | ||
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| + | Our second limitation is that Sugar belongs on a two sided market. In a two sided market, users and merchant affect each other. As such, dropouts on the user end can cause dropouts on the merchant end, and vice versa. Thus, our survival analysis may be confounded by the network effects. | ||
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| + | Our third limitation is that Sugar is an ecommerce app, which takes customer through a sales funnel. There are a few main stages of a customer’s journey, and users can drop off at any point: | ||
| + | <div align="center">'''Installation > Skimming > First Purchase > Redemption > Second Purchase'''</div> | ||
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| + | Sugar’s aim will be to move as many users as possible from the start to the end of the funnel in order to earn profits. | ||
| + | |||
| + | Therefore, it is not a straightforward analysis like predicting churn for a fixed subscription, multiple survival curves are needed to have a complete picture of the customer’s journey. | ||
Revision as of 19:47, 10 January 2016
| Background | Data Source | Methodology |
|---|
Introduction
The key aim of this project is to tackle the three problems above and increase the voucher redemption rate, customer retention rate and merchant retention rate.
As the nature of our study differs in some ways to existing literature reviews, we will make adjustments to the pre-existing methods of survival analysis due to the limitations of our scenario.
Limitations
Our first limitation is, unlike subscription based services, Sugar provides the app to users for free. Users can use the app indefinitely or choose to uninstall it. However, at this present time, there is no way for Sugar to track their uninstallations. This means that Sugar has no way of telling when a user has dropped off for real.
Our second limitation is that Sugar belongs on a two sided market. In a two sided market, users and merchant affect each other. As such, dropouts on the user end can cause dropouts on the merchant end, and vice versa. Thus, our survival analysis may be confounded by the network effects.
Our third limitation is that Sugar is an ecommerce app, which takes customer through a sales funnel. There are a few main stages of a customer’s journey, and users can drop off at any point:
Sugar’s aim will be to move as many users as possible from the start to the end of the funnel in order to earn profits.
Therefore, it is not a straightforward analysis like predicting churn for a fixed subscription, multiple survival curves are needed to have a complete picture of the customer’s journey.
