No ToC product can survive without Internet advertising . Because the Internet has been dominated by ToC for the past few decades, advertising has played an irreplaceable role in it, and the field has also become increasingly mature. The field of Internet advertising is complex and involves many factors.
With so many factors involved, it is almost impossible to have a comprehensive understanding of the Internet advertising sector without systematic sorting. But after careful analysis, we found that the evolution of Internet advertising is based on the evolution of transaction forms and data monetization, with the optimization of advertising display logic as a secondary line. This article mainly deduce the evolution of transaction forms and data monetization capabilities of Internet advertising, as well as the impact on other factors, and ultimately promotes the vigorous development of the Internet advertising market. 1. Contract advertising, as the name suggests, is to sell traffic in a package in the form of a contract to realize the initial traffic monetizationIn the early days of Internet advertising, the cooperation model was actually copied from offline advertising, that is, the demand side purchased traffic from advertisers in batches according to the contract. This stage had the following characteristics:
Fixed-position contract advertising, which is to buy out the display and exposure of a specific advertising position in a certain period of time, is also called CPT advertising. The main features of this stage are:
The characteristics contain pain points, and the pain points will become the driving force for things to develop to the next stage. What are the pain points of the demand side (mainly advertisers) at this stage?
The main technical issue at this stage is the scheduling system, which is to schedule the advertising display according to the time period purchased by the advertiser. As mentioned earlier, the current pain points are the driving force for subsequent changes. Based on the above pain points and because the development of targeting technology makes data monetization possible, fixed-location audience targeted contract advertising came into being. Fixed-position audience-targeted contract advertising is also called display contract advertising, which means purchasing exposures for specific groups of people in specific advertising positions. This allows the demand side to purchase traffic that meets their own requirements based on the target audience to reduce advertising waste. The supply side can also split and sell the traffic, that is, sell the traffic to more suitable demand sides, thereby obtaining more revenue. This stage has the following characteristics:
As mentioned earlier, the characteristics contain pain points, and the pain points will become the driving force for things to develop to the next stage. What are the pain points of the demand side (mainly advertisers) at this stage? The division of labor in collaboration is unreasonable because the single billing model (CPM) means that the risk of advertising effectiveness is borne by the demand side. That is, the demand side needs to predict the probability of users clicking on ads and the subsequent conversions after clicking. However, what the demand side can optimize is actually the subsequent conversions after clicking. Regarding whether the user clicks, the demand side only has the ad position information and the user's basic targeting information. What are the pain points of suppliers (mainly media platforms) at this stage? Subject to quantity constraints. Because it is difficult to accurately estimate the traffic of fine-grained label combinations, and overly fine labels lead to lower sales rates. At the same time, when a flow satisfies multiple contracts at the same time, only allocating it online may waste traffic that could have been sold at a more expensive price. The main demands for technology at this stage are: online traffic prediction, online traffic allocation (traffic can satisfy multiple advertisers at the same time and traffic is allocated under the constraints of the contract volume), and audience targeting technology. Even in the later stages of contract advertising, because it is still entirely up to the demand side to estimate the advertising effect on their own, and the supply side is difficult to participate due to quantity constraints, the demand side of contract advertising is still mainly brand advertising, which excludes a large number of long-tail users, which greatly restricts the development of the Internet advertising market. Therefore, to further unleash the potential of the Internet advertising market, it is necessary to meet the demands of these long-tail users for advertising effectiveness, that is, suppliers must bear certain responsibilities for advertising effectiveness, but in order to give suppliers sufficient motivation to participate, they must also be liberated from quantity constraints. As mentioned above, the current pain points are the driving force for subsequent changes, and thus, bidding advertising came into being! 2. Bidding advertising, that is, selling traffic in a model where the highest bidder winsInternet advertising has developed a bidding transaction form, which has a bit of the flavor of the transition from a planned economy to a market economy. There are no more "indicators" of the planned economy, but there are more market rules to be established, including pricing strategies, bidding strategies, etc. This stage has the following characteristics:
Like contract advertising, bidding advertising is divided into general bidding advertising and real-time bidding advertising based on the different abilities to monetize data. The former, like contract advertising, mainly utilizes the data of the supplier, while the latter is more likely to utilize the data of the demand side for monetization. A typical example is visit redirection, where advertisers provide users who have visited their platform and deliver advertisements to these users on the media platform. General bidding advertising is actually the demand side informing the supplier in advance of the bidding requirements. When corresponding traffic appears, the supplier will allocate the traffic to the demand side with the highest advertising value after estimating the advertising value (based on click-through rate and ad bid). For example, both demand parties A and B need male users who are 15-25 years old and live in Beijing. When a user who meets this condition appears, the supplier will obtain the advertising value based on the advertiser's bid and the estimated ad click-through rate, and allocate the traffic to the demand party with higher advertising value. In this process, the supplier's allocation is based on maximizing the advertising value without having to consider the total exposure guarantee for different advertisers. This removes the constraints of incoming traffic on the supplier in the process of traffic allocation. The main features of this stage are:
The supply side's motivation to enter this stage:
The motivation for the demand side to enter this stage:
Pain points of demand side at this stage:
What are the pain points for suppliers at this stage?
As mentioned earlier, the current pain points are the driving force for subsequent changes. Based on the above pain points and because the demand side has accumulated a large amount of data, real-time bidding advertising came into being. The essence is to bid separately for each piece of traffic. The demand side decides whether to participate in the bidding and bid based on the user ID sent back by the supplier, and then uses its own data to determine whether to make a decision. Its main features are as follows:
Requirements for the demand side at this stage: It is necessary to use its own data to improve user information and combine it with the information about the market returned by the supplier to estimate the click-through rate of advertisements. At the same time, based on this and combined with the evaluation of the click value, bids can be made. Therefore, the demand side is required to have extremely high data monetization capabilities. After the emergence of real-time bidding, advertising transactions increasingly rely on online communication between machines, rather than prior agreements or manual operations, so they are also called programmatic transactions. Programmatic trading also includes optimization, private market and programmatic direct investment. In bidding advertising, in addition to basic functions, there are also a large number of strategic issues, such as pricing strategy, bidding strategy, bidding mechanism, and market reserve price; at the same time, it also benefits from the development of artificial intelligence technology, which gives data a larger monetization space, that is, it is not limited to crowd targeting, but can also play a role in advertising click prediction, advertising value evaluation and other aspects. 3. Comparison between bidding advertising and competitive bidding advertisingFrom the supplier's perspective: in contract advertising, the supplier is only responsible for the quantity of advertising and is not responsible for confrontation; in bidding advertising, the supplier is mainly responsible for bidding and charging rules, and also includes some responsibility for confrontation. From the demand side: contract advertising lacks transparency, but because there is a guarantee of quantity, it is valuable for brand advertising; in bidding advertising, since you can pay based on the results, you can go from ensuring quantity to ensuring costs. Although Internet advertising is complex, its main development line is the transaction form (contract or bidding) and the improvement of data monetization capabilities. There are two dimensions to data monetization capabilities: the first is the data source, which initially only used supply-side data and later began to use demand-side data; the second is the way data is used, which was initially mainly used for crowd targeting and field classification (such as context and search terms), and then began to be combined with artificial intelligence technology to further explore the value of big data. IV. Conclusion
Author: A Shui Source: |
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