Review summary: Why do cash loan products fail in operation?

This article is a review and summary of the failure of a cash loan product that the author operated. The author discusses the reasons for the failure and areas for improvement from the summary.

Product Project Background

Loan Supermarket (abbreviated as Loan Supermarket) is an APP that provides traffic diversion services for cash loan products. Its target group is users with borrowing needs, and its customers are the cash loan party A.

The project was officially launched in May. In the early stage, its own users came from the diversion of users who were rejected by its own cash loan products. The daily goal is to find as many Party A products as possible to cooperate with our platform. Starting from August, the daily income can occasionally reach 100,000 in turnover. The number of daily online products remains at 50, and an average of 5 products are online and offline every day. Because the user base of its own cash loan products is unstable, in order to maintain a stable level of loan excess, some of the volume will be supplemented by sending text messages.

After September, in order to reduce the dependence of Daichao app on the traffic of its own cash loan products, the team started to buy traffic from outside, mainly based on registration via SMS. At this time, because of the growth in revenue, they saw the sweetness and became self-inflated. They thought that as long as their own scale was large enough, their income would be higher and they could gradually grow bigger and stronger.

After October, the scale of buying traffic began to increase, not only based on SMS, but also from other loan supermarkets (such as Pineapple Loan). In order to increase revenue during this period, we even started to involve agency services, that is, outsourcing the products of our platform to other loan supermarkets for promotion, and we earned the difference in promotion ourselves.

As of the end of December, the project operation failed, with the highest peak daily turnover reaching 180,000. The net profit was positive from May to October, but negative from November to December, indicating a loss-making stage, and the project operation failed.

Cause of failure

1. Blindly buying traffic without evaluating the channels

With the goal of improving its own scale and increasing revenue, it blindly carried out volume-buying activities through SMS and other loan supers. On the surface, the daily turnover increased, but the increase in turnover could not cover the cost of buying volume. It did not distinguish between good and bad channels, and promptly eliminate the inferior and retain the superior. Instead, it bought all at once, laying the groundwork for later losses.

1. Lack of control over user behavior and psychology leads to serious loss of user retention and activity

Starting from user registration, users will form the following series of behaviors:

When the users we buy traffic from register, they are initially considered as our potential effective users only after they log in to the app. And only when the users click to apply for the product (settled by UV) or register for the Party A product (settled by A) will real revenue be generated and they are truly effective users for us.

However, not only will users be lost if they log in, but even lagging active users will produce different results due to different subsequent behaviors: users browse many products but rarely click into the detail page to learn more; or users click into the detail page but rarely click to apply, but directly exit and uninstall; or users rarely register for products after clicking to apply; or some users only apply for one product, while other users may apply for 3-5 products. These users are different and their value to us is also different.

By tracking and analyzing user behavior, we can not only understand how users are using our products and optimize them, but we can also understand the user base of the channels that buy traffic and screen the channels.

1. About product release

Although some people in the team will attribute the failure to externalization, I don’t think externalization is the main reason for the loss. Because we sell our products outsourced, we act as an intermediary and make profits by earning the price difference at zero cost, which will not affect losses. The impact of selling products outsourced on us lies in the loss of the brand.

When promoting Party A's products here, we focus most on the user's payment rate, that is, the cost. The higher the loan approval rate, the lower the customer acquisition cost, the more beneficial it is for Party A, and the more willing they will be to deepen their cooperation with us. However, outsourcing products, especially to some channels whose quality is unknown, will lead to a low product payment rate, making Party A feel that our product user quality is poor, which will damage our impression with Party A, and then cause Party A to cancel cooperation or reduce the scale of promotion, which is a loss of intangible assets.

1. Analysis based on product data

The above figure shows the relationship between the average number of click applicants’ contributions and ROI every day from August 1 to November 30. It can be seen that the two are moving in the same trend, that is, the more average contributions per person, the higher the ROI. Therefore, when buying traffic, the first thing to consider is the average number of times the buying users contribute to their own loan and how to improve this data indicator, which is directly related to whether they can make a profit.

Ideas for future product improvements

We differentiate each volume-buying channel, and at the same time, we track the users of each channel, and track a series of behavioral data from the beginning of registration to determine the average user contribution rate and ROI of each channel.

From now on, for Party A's products, we will only cooperate with UV and design a background similar to Rong360. Party A will make the payment and fill in the payment information in time. When the payment amount is used up, the system will automatically go offline and come back online after recharging.

Analyze user behavior and retention data within the app to improve products and increase user contribution and activity.

The most pressing issues

Why has the per capita contribution rate of users dropped so drastically? User quality issue or product design issue? What measures can be taken to improve the average contribution rate of users?

Finally, this is the first time I write a review about a product. There may be many things I haven’t thought of and many mistakes. I welcome your comments.

Source: Black Rabbit