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How to establish a data analysis logic system for information flow advertising?
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I believe everyone is familiar with information flow advertising . Any friend in the Internet advertising circle can easily tell you the daily active users, advertising display forms and delivery strategies of the current top information flow delivery platforms, but do we really know how to optimize information flow advertising? Do we really know what the causes are when the data changes differently? I work in a Party B company, responsible for the information flow advertising operations of various advertisers and various media. Recently, I encountered a distressing thing that I would like to share with you. In the daily delivery process, we will encounter situations where the delivery data is not ideal. At this time, we will find that many people will habitually lock the "murderer" as CPC and CTR, adjust the price if there is a disagreement, change the material if the price adjustment is ineffective, and then continue to build plans for repeated testing. Of course this method is effective sometimes, but is it necessarily correct? Can it be applied to all data situations? Don’t get excited yet. Let’s find a quiet environment, calm down, and go over this logical system from the beginning together. I believe that our thoughts will be clearer after reading it. First, assume that the final evaluation KPI of ad group S is the number of new paying users and cost on that day, and the bidding method is CPC. The data we can obtain during the delivery include four indicators: daily display volume , click volume , activation volume , and new paying users. Now let's start to analyze them one by one. 1. Display volume The display volume is easy to understand. It is the number of times the advertisement is exposed. It serves as the denominator in data analysis and is the basis for all data changes. Maintaining a stable display volume is a prerequisite for the entire delivery. Unlike other types of advertising, the display volume of information flow advertising is greatly affected by the advertising plan budget. The media will pre-allocate traffic based on the budget value. For example, if the daily budget of Plan A is 1,000 and that of Plan B is 100,000, the media will predict that Plan B has a greater traffic demand and will allocate more traffic to Plan B to give it enough space to display advertisements. Another important influencing factor is the change in the media's distribution of traffic to different industries. During the recent 618 promotion, students who are not in the e-commerce industry should have a deep understanding of this. They have personally experienced the trouble of having money but not being able to spend it. This is because the media will allocate more traffic to the e-commerce industry during the e-commerce promotion period. The display volume part introduces a concept called CPM (cost per thousand impressions). Currently, the information flow advertisements of mainstream media all use CPM to measure the competitiveness of an advertisement. The higher the CPM, the more competitive the ad is, and vice versa. The specific factors that affect CPM will be explained in detail in the click volume section. 2. Click volume The click volume brings up two concepts, CTR (clicks/impressions) and CPC (consumption/clicks). The most frequently used concepts in daily data analysis are as follows: in this part, advertisers hope to obtain the highest CTR with the lowest CPC. First, let’s look at CTR. The CTR of information flow advertising is a system estimation mechanism, that is, before an advertisement is released , the media will estimate its CTR in advance. The evaluation standards given by the media are relatively official. Based on our previous optimization experience, there are three main factors: the attractiveness of advertising creativity, the relevance of creative content to the product, and the clarity of image materials. The copy and pictures in the creative should not be too official. After all, it is placed on a news information platform, and an information style will not disgust users. But we should also pay attention to relevance. Even if the content of the copy is very novel, but the relevance to the invested product is very low, it will affect the CTR estimate. Image clarity means achieving the highest possible clarity within the size required by the media, which is beneficial to user experience. In addition, the accuracy of the advertising audience is also an important factor affecting CTR. Although it has little impact on CTR estimation, it has a huge impact in later delivery. For example, if the product being promoted is women's cosmetics, and we set the audience to be unlimited in gender, then the overall CTR will be low because male users will not be interested in it. At this time, we need to set the audience to filter out irrelevant people, reduce invalid losses and improve the overall CTR. The main factors affecting CPC are industry competition, bid price and CTR. When the number of competitors increases, everyone will inevitably increase their advertising bids in order to grab more traffic. At this time, the competition from competitors and the increase in their own bids will lead to a significant increase in CPC. Another factor is CTR. At this time, we need to quote the CPM concept mentioned above. CPM = CTR * CPC * 1000. The media will comprehensively judge the competitiveness of an advertisement based on CPM, and will automatically balance the CPM value to ensure the competitiveness of the advertisement. Therefore, when CTR shows a significant decline, CPC will increase accordingly to ensure CPM; similarly, if CTR increases significantly, the corresponding CPC will also decrease. From the above, we can see that advertising materials are a very important factor in terms of click volume. Good materials can greatly increase the CTR of an advertisement, thereby effectively reducing CPC. 3. Activation Here we define activation as the user opening the APP after downloading it and having an internet connection, and the activation volume is the number of users who activate the APP. In the activation part, we introduce two concepts, activation cost (consumption/activation volume) and activation rate (activation volume/click volume). Everyone is familiar with activation costs. Almost all APP products need to be evaluated for marketing and promotion . Of course, the lower the activation cost, the better. We often hear customers say, "As long as the activation cost is lower than the budget of xx yuan, there is no upper limit." It's really a mixed feeling. So what is the most thorough way to analyze activation costs? We come up with a new idea. The algorithm is activation cost = consumption / number of activations = consumption / (number of clicks * activation rate) = CPC / activation rate. The data is the most thorough at this step. From this formula, we can clearly analyze that the activation cost is affected by two factors, CPC and activation rate. When the CPC is lower and the activation rate is higher, the activation cost will be lower. The factors affecting CPC, click volume, have been analyzed. Now let’s focus on the factors affecting activation rate. Through the summary of daily optimization, we found that the factors affecting the activation rate mainly include the matching degree between creativity and undertaken content, landing page design, network environment, operator, and platform settings. The first is the match between creativity and the accompanying content. The accompanying content is divided into two types: direct download after clicking the ad and entering the landing page, but the logic is the same. When the user clicks on the ad and finds that what is presented to him is inconsistent with the creativity, the user is likely to be lost. For example, our creative copy is "What fruits to eat in summer to avoid getting tanned easily", but after clicking the ad, the landing page shows a comprehensive e-commerce platform, and the first screen is all 3C products, which is not the same content that users want to see, so users are easily lost. Therefore, we should also pay attention to this when designing advertising creatives. We should not fall into the trap of high CTR and need to consider it comprehensively. The second is the landing page design. With the maturity of mobile Internet , there is basically no situation where advertisers cannot find the download button on the first screen of their landing pages. However, the button color matching, position design and copywriting still need to be explored. A good landing page can effectively improve the overall activation rate. The third is the network environment. Mobile users are different from PC users. They are very sensitive to mobile data traffic, especially when placing advertisements for APP downloads. When placing advertisements, you must set up a wifi environment, otherwise a lot of clicks will be wasted, especially for large-scale game products. The fourth is the operator, which is a setting for individual products and activities. For example, some advertisers’ products are only suitable for China Unicom users, so the plan needs to filter out other operators in the settings, otherwise the activation rate will definitely be low. The fifth is the platform setting, which is easy to understand but easy to make mistakes. For example, the product is mainly for Android in the group, but the planned platform setting is selected as unlimited, which means that both Android and IOS can see the advertisement. This will greatly affect the final activation rate data. Now that the data change logic of the activation rate is clear, the analysis logic of the activation cost will also be very clear, and all the relevant content of the activation volume has been GET. 4. Number of new payment users The number of new payment users is the number of users who successfully completed payment after activating the APP on the same day. The logic of this part is consistent with that of the activation volume part. We also introduce two concepts, payment cost (consumption/number of new payment users) and payment rate (number of new payment users/activation volume). After calculating the payment cost according to the same formula, payment cost = activation cost / payment rate, that is, the lower the activation cost and the higher the payment rate, the lower the payment cost. The activation rate has been comprehensively analyzed in the previous section. In this section, we will focus on analyzing the factors affecting the payment rate. As a third-party staff member, let me make a few comments about the payment rate. When the payment rate of a product drops significantly, 80% of the reasons are due to the product itself. Advertisers should never deny all previous investments and efforts and then stop the plan because of a disagreement. At this time, if the data we analyzed earlier are OK, then what we need to do is to carefully experience the product's own process. Here I mainly analyze four situations that I have encountered before. The first is a problem with the product payment process, such as not receiving a verification code or being unable to click the payment button. This problem is uncommon but very important and needs to be checked as soon as possible. The second situation is that the single product or category promoted in the creative idea is sold out or difficult to find in the APP. The user downloads the APP for the product in the creative idea, but will definitely be disappointed if he cannot find the corresponding product. The third situation is that there are corresponding products in the APP, but the prices are relatively high in the same industry and are not competitive enough, so users choose to leave after comparison. The fourth situation is that the preferential information reflected in the creative, such as 88 yuan for new users to register, 20 yuan off for purchases over 100 yuan, etc., is not clearly reflected in the APP, and there are no corresponding prompts during use. In this case, users will give up halfway through the experience. After the changes in payment rate are analyzed clearly, the changes in payment costs will also be very easy to analyze, so I will not go into details here. It is said that children who are responsible for placing information flow advertisements must have good physical fitness, because this is really a physical job. You have to work during users' working hours, race against time to prepare plans and urge reviews, and solve various strange cases; you have to work even more during users' rest time, and you must not miss the peak traffic period. Therefore, even in such a hard situation, we must have a clear idea and not be blind. We must find the core problem points every time we optimize to achieve twice the result with half the effort. Your APP |
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