Who should I call if the data is not ideal?
Why is the click-through rate high but not converted?
Why is the CPC low but the activation cost high?
In the daily delivery process of information flow advertisements, we often encounter unsatisfactory delivery data. At this time, many people habitually lock the "murderer" in CPC and CTR, adjust the price if there are differences, change the material if the price adjustment is invalid, and then constantly build a plan and test it repeatedly.
Of course, this method is feasible in some cases, but is it correct? Can it be applied to all data situations? Let's calm down and sort out this logical system from the beginning. I hope everyone will have a clearer idea after reading it.
First of all, suppose that the final evaluation KPI of advertising group S is the number and cost of new paying users on that day, and the bidding method is CPC. The data we can get in the launch includes four indicators: the number of current users, the number of clicks, the number of active users, and the number of new paying users. Now let's start analyzing them one by one.
Show before one's eyes
It is easy to understand that the exposure times of advertisements are the denominator in data analysis and the basis of all data changes, and maintaining the stability of exposure is the premise of the whole delivery. Different from other types of advertising, the existence of information flow advertising is greatly influenced by the advertising plan budget, and the media will pre-allocate traffic according to the budget value. For example, if the daily budget of Plan A is 1 1,000 yuan and Plan B is 1 1,000 yuan, the media will predict that the traffic demand of Plan B will be greater, and will allocate more traffic to Plan B, so that it has enough space to display advertisements. Another important factor is the change of the media's traffic distribution in different industries. Not long ago, students in the non-e-commerce industry should have a deep understanding. They simply experienced the troubles of endless money. This is because during the e-commerce promotion period, the media will allocate more traffic to the e-commerce industry.
The exhibition volume part leads to a concept called CPM (thousand exhibition cost). At present, information flow advertisements in mainstream media all use CPM to measure the competitiveness of an advertisement. The higher the CPM, the higher the advertising competitiveness, and vice versa. The specific factors affecting CPM will be explained in detail in the click volume section.
click rate
Clicking on this chapter leads to two concepts, CTR (click/presence) and CPC (consumption/click). Advertisers hope to get the highest CTR with the lowest CPC.
First look at CTR. CTR of information flow advertisement is a systematic prediction mechanism, that is, the media will predict the CTR of an advertisement in advance before it is put into use. According to our previous optimization experience, there are three main factors: the creative attraction of advertising, the correlation between creative content and products, and the clarity of picture materials.
Don't be too official about the copy and pictures in your creativity. After all, it is a news information platform, and the biased information style will not make users disgusted. However, we should also pay attention to relevance. Even if the content of the copy is novel, the low correlation with investment products will affect CTR estimation. Picture definition is to achieve the highest definition under the size required by the media, which is beneficial to the user experience.
In addition, the accuracy of advertising audience is also an important factor affecting CTR. Although it has little influence on CTR estimation, it has great influence on later delivery. For example, if our products are women's cosmetics, and we don't limit the gender when setting the audience, then the overall CTR will be very low, because male users are not interested in it. At this time, it is necessary to set the audience, filter out irrelevant people, reduce invalid losses and improve the overall CTR.
The main influencing factors of CPC are industry competition, bidding and CTR. When competitors increase, in order to seize more traffic, everyone is bound to raise advertising bids. At this time, the competition of competitors and the promotion of their own bidding will lead to a substantial increase in CPC. Another factor is CTR. At this time, it is necessary to quote the CPM concept mentioned above, CPM = CTR * CPC * 1000. The media will comprehensively judge the competitiveness of an advertisement according to CPM to compete with other advertisers for display opportunities. Therefore, when CTR decreases, in order to ensure the competitiveness of advertising, the CPC of the corresponding plan will also increase accordingly; Similarly, if CTR increases, the corresponding CPC will also decrease.
To sum up, we can see that advertising material is a very important factor in the click volume part. Good material can greatly improve the CTR of an advertisement, thus effectively reducing the CPC.
Activation quantity
Here, our activation amount is defined as the number of users who download the APP and activate the APP after opening it in a networked state. In the activation part, we introduce two concepts, activation cost (consumption/activation amount) and activation rate (activation amount/click amount).
The activation fee is familiar to everyone. Almost all APP products must be evaluated before they can be marketed. Of course, the lower the activation cost, the better. So how to analyze the activation cost most thoroughly? We gave a new idea. The algorithm is activation cost = consumption/activation number = consumption/(click * activation rate) = CPC/ activation rate. Only by this step can this data be the most thorough. From this formula, we can clearly analyze that the activation cost is affected by two factors, CPC and activation rate. The lower the CPC, the higher the activation rate and the lower the activation cost. The influencing factors of CPC are analyzed, and we will focus on the influencing factors of activation rate.
Through the summary of daily optimization, we find that the main factors affecting the activation rate are the matching degree between creativity and content, landing page design, network environment, operators and platform settings.
The first is the matching degree between creativity and entrepreneurial content. The content can be divided into two types: downloading directly after clicking the advertisement and entering the landing page, but the logic is the same. When a user clicks on an advertisement and finds that what is presented to him is inconsistent with the creativity, the user will lose with a high probability. For example, our creative copy is "What fruit is not easy to get tanned in summer", but after clicking the advertisement, the landing page shows the integrated e-commerce platform, and the first screen is 3C products, which is not the same content as what users want to see, so users are easy to lose. Therefore, we should also pay attention to this when advertising creativity. Don't fall into the trap of high CTR, it needs comprehensive consideration.
The second is the landing page design. With the maturity of the mobile Internet, there is basically no situation that advertisers can't find the download button on the first screen of the landing page. However, it still needs to be explored in button color matching, position design and copywriting. A good landing page can effectively improve the overall activation rate.
The third is the network environment. Mobile is different from PC. Users are very sensitive to mobile phone traffic, especially when placing advertisements downloaded by APP. When advertising, you must set up a good wifi environment, otherwise it will really waste a lot of clicks, especially for large game products.
The fourth is the operator. This is a setting for a single product and activity. For example, some advertisers' products are only suitable for Unicom users, so the scheme 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 aimed at Android, but the planned platform setting is not limited, that is, both Android and IOS can see advertisements, which will greatly affect the final activation rate data.
When the data change logic of activation rate is clear, the analysis logic of activation cost is clear, and the related content of activation amount is obtained.
Number of new paying users
The number of new payment users is the number of users who successfully completed the payment after activating the APP on the same day. The logic of this part is consistent with the amount of activation, and we also introduce two concepts, namely, paid cost (consumption/new paid users) and paid rate (new paid users/activation). After calculating the calculation formula of payment cost, payment cost = activation cost/payment rate, that is, the lower the activation cost, the higher the payment rate and the lower the payment cost. In the last part, the activation rate is analyzed comprehensively. In this part, we mainly analyze the influencing factors of the payment rate.
When the payment rate of a product drops obviously, 80% of the reason is the product itself. Students should never deny all the previous efforts and efforts without saying a word, and then stop planning. At this time, if the data we analyzed before are ok, what we need to do now is to seriously experience the process of the product itself. Here are four situations that we have encountered before.
First of all, there are problems in the product payment process, such as not receiving the verification code and being unable to click the payment button. This problem is not common but very important and needs to be investigated at the first time.
In the second case, the single product or category promoted in the idea has been sold out, or it is difficult to find in the APP. Users are downloading the APP of products in idea, but they will be disappointed if they can't find the corresponding products.
The third situation is that there are corresponding products in the APP, but the price is high in the same industry and the competitiveness is not enough. After the comparison, the user chooses to leave.
The fourth case is the preferential information reflected in the creativity, such as 88 new users, 20 less for the whole audience 100, etc. There is no obvious reflection on the APP, and there is no corresponding prompt during use. In this case, the user will give up the experience halfway. After the change of payment rate is clearly analyzed, the change of payment cost is well analyzed, so I won't go into details here.
Different from other forms of advertising, information flow advertising needs refined operation. Clear thinking logic and correct optimization ideas are necessary and sufficient conditions to ensure accurate and efficient operation. I hope this article is helpful to you.