How to optimize marketing strategies through advertising data?

Advertising monitoring can track the real effect of advertising and optimize marketing strategies in a targeted manner based on advertising data. If you want to obtain accurate and referenceable advertising data, you must first have a good understanding of advertising detection, otherwise your money will be wasted. In this article, the author systematically interprets the relevant concepts, hoping to provide a reference.

1. What is advertising monitoring?

In the 19th century, John Wanamaker, former U.S. Postmaster General and father of American department stores, once proposed the Gottbach conjecture in the advertising industry: "Half of my investment in advertising is useless, but the problem is that I don't know which half."

Another Mr. Philip Kotler also mentioned: "Most of the promotional expenses are wasted. Only 1/10 of the promotional activities can get a response rate higher than 5%, and this pitiful number is decreasing year by year."

However, with the advent of the digital age and the rapid growth of online advertising, everything is becoming clearer. You spent a large budget on advertising and promotion, but what was the effect? How to adjust and optimize marketing strategies based on the data from each advertising campaign? These can all be quantified, and how to quantify them requires advertising monitoring.

2. Why do we need to monitor advertising data?

Although advertising data can be quantified today, today's digital advertising still faces the same problem: a large amount of false data is still generated. With the temptation of money, online advertising channel operators deceive advertisers through a large number of false clicks and activations, which invisibly increases the advertisers' costs.

Therefore, advertising monitoring has the following main purposes:

1. Monitor and measure the effectiveness of advertising;
2. Through anti-fraud measures, false data from various channels can be identified;
3. Provide data support for marketing personnel, refine operations, and optimize the delivery of advertising materials.

3. Why choose a third-party advertising monitoring company?

1. Monitor advertising results

Conducting objective and impartial third-party monitoring of advertising results is an effective way to assess the effectiveness of corporate advertising.

Monitor whether the media used for advertising is effective, whether the time of delivery is correct, how often the advertisements appear, whether the advertisements are complete, etc.; or issue a series of data reports on the channels used by competitors, the frequency of delivery effects, etc.

Form strategic plans based on advertising results, conduct objective analysis and suggestions, and compare results to determine which times and media are more suitable for the target audience, and which advertisements can receive good market feedback - these third-party advertising monitoring companies can effectively help companies make decisions on their next steps.

2. Prevent data falsification

The main purpose of channel inflating is to earn money from advertisers. During the advertising period, you will hardly find any suspicion of inflating the volume based on regular data. However, once the settlement or cessation of delivery, the income and retention from the channel will immediately drop to the ground, and the hard-earned money will be defrauded by the unscrupulous channel.

3. Targeted delivery, avoid blindly following

Provide reports and tracking results to third parties, effectively formulate promotional plans suitable for enterprises, enable advertisements to effectively reach target audiences, maximize their effects, help enterprises with sales, avoid blind competition with peers, and reasonably arrange advertising budgets and delivery.

All in all, there is only one answer: ensure the authenticity and validity of the data .

There are thousands of marketing strategies, but effectiveness is the most important. If you are not careful in your marketing, you will shed tears when you review it.

4. What data does advertising monitoring monitor?

Advertising monitoring is generally divided into three types:

1. Exposure monitoring: also known as "display monitoring", usually the channel partners send data back to advertisers.
2. Click monitoring: monitors the number of clicks. The data can be collected by the advertiser themselves or transmitted back to the advertiser by the channel operator.
3. In-app monitoring: refers to the monitoring of behaviors/events within the APP, such as basic PV, UV, APP activation/registration/login, etc., users' next-day retention, 7-day retention, 30-day retention, payment rate, ARPU value, etc.

This data is generally collected through the SDK provided by a third-party monitoring company integrated into the app, and the interfaces provided by different apps will be different.

5. Which participants are involved in advertising monitoring?

Advertising monitoring generally involves the following participants:

process:

1. Advertisers place ads to advertisers, and after users click on the ads, the advertising channel providers upload data to the advertising monitoring platform;
2. After the user downloads and launches the APP and completes a series of operations, the APP will upload the user data to the advertising monitoring platform through the corresponding interface;
3. After attribution through a certain method, the user's relevant data will be associated with the channel operator.

6. How to attribute channels?

How to determine whether the user is brought by this channel involves how to attribute the channel volume. Attribution refers to determining that mobile app installation or post-installation events are the result of the channel. Accurate attribution is crucial for optimizing user acquisition and channel selection.

Currently, common App activation attribution methods include device number attribution, channel number attribution, IP+UA attribution, etc.

1. Device number attribution (exact match)

Device number attribution is mainly used for promotion in third-party apps, and the main application scenario is information flow advertising.

In most cases, third-party apps can obtain the device number of the user's mobile terminal, such as the IDFA of iOS devices, the IMEI and Android ID of Android devices. Therefore, in advertisements such as information streams, the click data that third-party platforms feed back to advertisers usually includes the user's device number information.

After the user downloads the App and activates it, the obtained device number can be matched with the device number fed back by the third-party advertising platform for attribution to evaluate the effectiveness of the delivery.

This method of attribution is relatively accurate. However, it should be noted that in order to obtain more accurate analysis conclusions, we will use multiple attribution methods at the same time. Generally speaking, device number attribution has a higher priority.

This brings up a problem. Activations brought about by other forms of promotion are likely to be matched first with the device number attribution method. For example, after a user clicks on a news feed ad, they do not have the desire to download the app, but later clicks on an HTML5 ad, which prompts them to complete the behavior of downloading and activating the app.

According to the industry’s common Last Click calculation method, it should actually be attributed to HTML5 advertising. However, the HTML5 channel cannot obtain the user's device number information, so this behavior will most likely be attributed to a higher priority information flow, resulting in errors.

2. Channel number attribution (precise matching)

"Channel number" refers to the channel identifier written into the Android installation package. Generally, the channel number will be written into the APK installation package in advance and then distributed to different channels. The channel number will accompany the installation package throughout its entire usage cycle.

After the user activates the App, the channel number identification information can be obtained from the installation package for matching, so in theory the attribution is relatively accurate. However, this method may be blocked by mobile application manufacturers and may be easily used by unscrupulous channels to cheat on data, making it impossible to effectively evaluate the actual online promotion effect.

3. IP+UA attribution (fuzzy matching)

IP+UA refers to attribution analysis achieved by associating and matching the IP and User-Agent (UA for short, used to extract the user's operating system, version number, mobile phone model, and other information) when the user clicks on the ad with the IP and UA at the time of activation. Generally speaking, short links are used to collect these two pieces of information, and there is no need to connect to channels.

IP+UA attribution is mainly used in Web site traffic diversion, SEM promotion, and some advertising scenarios that cannot be attributed through device numbers and channel numbers. Such as HTML5 advertising, WAP advertising, etc. Therefore, although IP+UA is also a major attribution method, it is essentially a fuzzy matching attribution.

Because this method cannot directly obtain accurate information such as the device number of the user client, and the user's IP and UA parameters are prone to change and repeat with the environment, its priority is also lower.

For example, in an office environment, when multiple users use the same IP, or when multiple users who activate the App use exactly the same mobile phone brand and model, it is difficult to achieve accurate attribution.

What’s worse is that the IP address of the user clicking the ad is likely to be inconsistent with the IP address at the time of activation. For example, the user clicks and downloads the App in a Wi-Fi environment, but activates it in a 4G environment; due to changes in the network environment, the IP address will also change accordingly. For example, in the same network environment with the same IP, user A clicked on the ad but did not download it; user B did not see the ad, but downloaded the App directly through the App Market and activated it, and the mobile phone brands and models of these two users are exactly the same, that is, the UA is the same. In these cases, IP+UA attribution is completely invalid.

Due to these problems with IP+UA, this method has a lower priority, but it will also cause the HTML5 advertising promotion mentioned above to be matched to the information flow advertising channel.

Author: Zhang Lun

Source: Zhang Lun (ID: woshipm123)