How can we effectively improve ROI if we don’t do monitoring and analysis for app promotion?

Local promotion is an effective way for App to acquire customers. Compared with online promotion , monitoring of local promotion data is more difficult. How to monitor the traffic of App’s local promotion channels and discover high-quality channels, high-quality regions and high-quality promoters is a problem that all App marketing and operations need to solve.

This article takes a certain operator as an example to introduce the channel monitoring problems it encountered in App promotion, the solutions it adopted and the final value generated, to help more App marketing and operations improve work efficiency.

1. Problem

A provincial operator plans to promote an app through offline marketing, hoping to seize online traffic. Currently, there are three main offline promotion channels , namely, promotion by business hall service staff, campus promotion , and ground agent promotion. Regardless of the channel, the promotion scenario is very similar: the sales staff asks the target users to scan the QR code, the users go to the landing page to download the App, and then register and activate it.

Figure 1: Goals, channels and scenarios of offline marketing

How to conduct channel monitoring and performance management in this process, that is, to count the promotion effects of each city, each business hall, and each staff member, is a huge test. Taking the iPhone as an example, we only have one app download page, the App Store. Faced with the local traffic coming from all directions, how can we identify them one by one?

Prior to this, the operator monitored the channels manually by recording them manually, and then entered them into the system for reporting step by step. This is a very traditional approach and has many problems:

• Manual recording is prone to errors and the recorded data is incomplete.
• The phenomenon of false reporting of performance data occurs frequently in order to embezzle promotion funds.
• It is impossible to measure the quality of customer acquisition ( AR PU, retention rate ) of each channel.
• The statistical summary process at each level is complex, lengthy and inefficient.

So do we have a good way to solve this problem?

2. Solution

I have previously shared a UTM traffic monitoring mechanism that can be well applied to advertising scenarios. So how can we apply it flexibly in the process of ground promotion?

1. What is UTM?

By adding UTM parameters after the link URL corresponding to the QR code, publishers can monitor the corresponding channel traffic effect. Parameters are also called "queries" and begin with "?". Different parameters do not affect the content of the page that the user arrives at.

Figure 2: UTM parameter interpretation

The table above details the 5 common parameters of UTM and their meanings. Because UTM was originally used for advertising monitoring, many of its names are still about advertising, but now we can apply it to various content, activities, and promotions to monitor channel traffic.

2. How to use UTM?

Assuming that the landing page URL promoted by the operator is "www.xxx.com/landingpage", we can add UTM parameters with information such as the city, business hall number, promoter employee number, etc. after the URL. This method can be used to monitor how much user traffic is brought by promoters in various places and whether registration and activation are completed.

Figure 3: UTM example

For example, this is a URL after adding UTM parameters. So what does this long string of parameters mean? Let's use the following table to analyze it.

Figure 4: Parameter interpretation

In this link with parameters, we can find that this is traffic brought by offline campus promotion , specifically by staff member numbered 00001 at campus a during the spring semester of 2017. In actual work, we can convert the delivery link with parameters into a QR code, which is very convenient for on-site scanning and promotion.

3. Value

With this information, the problem of counting the performance of each region, channel, and staff member can be solved.

Figure 5: Offline marketing performance statistics

In the above figure, the workload (number of users visiting the landing page) and actual effect (number of successful registered users) of each field promotion staff member are clear at a glance. The performance of staff member No. 00003 who promoted on campus a is significantly better than others.

Furthermore, we can combine indicators such as downloads, registration activation, and paid conversions to evaluate the effectiveness of different ground marketing channels and different ground marketing methods, so as to continuously improve operational efficiency. Compared with the previous manual recording method, this UTM mechanism connects online and offline data, and records the quantity and quality of work of each channel and each field salesperson in real time.

This is such an efficient method of field data monitoring, you should try it too!