Utilize AI tools wisely to make bidding ads exponentially more efficient

The development of the work of advertising so far, I wonder if you have ever considered, the future of advertising between the embodiment of the effect of the competitive differences will be reflected in the where, or that we should focus on the improvement of self-placement capabilities in which plate is more valuable?

Is it the ability to optimize the fine tuning of the placement account? I don't think so, you will see that every platform is vigorously promoting intelligent, integrated placement tools, the platform is weakening this part of the optimizer's ability; is it the ability to produce explosive material? This is one aspect, but the pop-up is difficult to sustain, difficult to iterate and stable, it is difficult to form a stable advantage, even if an individual has such a capacity, and too much dependence on the organization; is it only the product itself competes with each other? The product does matter, but the ad delivery side can't adjust quickly enough.

I think that it might belie in the wholeEfficiency and iterative capability of the delivery system as well as the output of ad contentIn order to gain a competitive advantage through advertising with the same product, it is important to be more efficient in the organization of the placement.

To put it in human terms, it will manifest itself in three specific ways:

1. The account side can develop a reasonable and comprehensive overall strategy and rhythm

2. The placement process is quick to identify problems and solve them.

3. Strong creation, output and iteration in ad content capabilities.

These three things can be done, I believe that most of the problems encountered in the placement can be resolved, at least significantly compared to peers have the advantage of placement. But you will find that these three things, and not a single rely on an optimizer himself, or a writer or director of the individual placement or creative ability, but the whole team related to the placement of the overall collaborative efficiency of the competition. But this does not mean that this is the person in charge of the relevant departments to consider things, optimizer or, editorial director or, editing or, in the specific implementation, since it is the competition of the efficiency and iteration of the placement, each role is worth considering and optimize their own work direction and form of point, in order to follow the trend to bring their own competitiveness in the industry.

In terms of specific implementation, it is possible that "the account side can formulate a reasonable and comprehensive overall strategy and rhythm", which may require different roles in charge of the systematic implementation of outputs based on products, operations, budgets and activities. In this process, we can make reasonable use of some funds or accounts data Kanban or unified management analysis tools to help us make decisions.

For example, on the Tencent platform you can use"Workbench"It can realize data analysis, management and permission allocation for different subjects, accounts and plans in one background, so as to improve the efficiency of the analysis and management allocation of the placement data, or it can make a unified summary and analysis of the effect of different directions of the placement strategy. You can also use"Shared wallet."The tool realizes the shared management of funds associated with multiple accounts, facilitates unified budget statistics, and decision-making allocation, and real-time monitoring and intelligent early warning of budget progress and utilization.

The remaining two things, in fact, can be reasonable through the AI tool, to help us carry out the daily placement efficiency and effect enhancement. Different platforms on the market correspond to different tools to choose from, here to tencent platform as an example, thenI'm mainly talking about the two products, Mythic and Mythic Ask, which have seen some more product updates recently, and I think it's now at a point where it can help optimize the overall placement efficiency to a greater extent.

First, there's the magic question.Many of you may have come across it before, but may be using it purely as a tool to rush a review or answer questions about a product, which is certainly not a problem, and the capabilities of Wonderful Questions actually go far beyond that.

In addition to audit Q&A and product Q&A, another highlight function of Miaowei is that you can ask it questions to understand the TOP1 advertisement ideas in specific industries and editions, and have the ability to analyze the ideas in a simple way.i.e., the ability to be "creatively inspired"The most important thing is that it is more convenient to use this feature. Miao asked to integrate this feature I think the biggest value is mainly more convenient, in fact, we also have some other ways to understand the industry's quality ideas, but can be in the first time, the account of the most intuitive to understand the industry's quality ideas on the Miao asked. Use this ability I suggest mainly to understand the top creative main, specific script analysis is best with the use of other video tools or their own analysis depth is deeper.

One of the things that really makes me think that MyoAsk is a stronger bit of value as a product, and based on a series of feature upgrades in November, is theIn terms of placement review and strategy empowermentThe first two of the 3 things mentioned at the beginning of the article. That is, the first two of the 3 things mentioned at the beginning of the article, which Wonderful Questions was able to do to greatly empower.

firstlyRapid report generation and analysis capabilities for placement data, MyoQ can make it easier for us to notice every detail in the lifecycle of ad placement and discover important points that have been overlooked, such as - time-sharing data analysis, whether there are conversion rate anomalies in different ad IDs, generating charts to understand trends, etc. Why I think this feature is valuable is because we will find that for the novice optimizer, he may not necessarily have such comprehensive analysis and diagnostic capabilities, and even if he does, it will take more time to sort out the data, not to mention real-time sorting and analysis into charts. For mature optimizers, often based on their own experience to judge, focus on the overall consumption and cost control, will not spend too much energy to pay attention to and produce details of the placement of the report analysis, so perhaps nothing wrong. But it is also easy to ignore some potential high-cost risk points, or low-cost volume of opportunity points. And wonderful ask this function first from the program to solve this problem, directly help us to organize the data and problems.

Secondly.The placement advice given by Wonderful Questions is also well worth taking into accountAfter using it for a while, I will find that it is not necessarily worth adopting all the placement suggestions. After using it for a while, I'll find that it's not that the placement advice from Wonderful Questions is necessarily worth taking completely, but it tends to give some more comprehensive considerations that complement the information gap in the optimizer's day-to-day placement strategy development.

For example, "peer comparison", the background of the question is peer data reference, can give us peer comparison results based on these data for feedback, and our own analysis is no way to find the problem. Another example is "operation log", this is a very detailed and important, but it is very easy to be forgotten in the analysis of the point, many times we analyze from the results, how much to consume, how much the cost, how much the click-through rate, we will find some of the data with the expected law is contrary to the data.

But the question is directly based on the operation log, combined with the budget, bid, creative adjustments and then analyze the life cycle of the ads, you can get a more meaningful reference data. Another example is "suggest to open xxx function", not that it suggests, we must open, but it is really a wonderful question to mention these suggestions, we are thinking about optimization strategy, can really open up the mind, but also to seriously understand the platform's product development trend, don't let their own optimization logic is closed.

The second tool to talk about is Mythos.This is a commercial content AIGC production and content distribution platform that can help us quickly create advertising material. Just based on this introduction, maybe you will think it's nothing great, there are many AI video tools before but actually use them all with bad results and a fake glance. But I want to say that if you think about 2024, there are a lot of AI semantic models in the rapid release, iteration, and are getting better and better, more and more like a "human" thinking, then you should be able to better understand the AI video or image output capabilities that the Mythic tool can bring.

In the advertising creative production link, it is not difficult to batch output the mixed clip class material for infomercial placement, which can be realized by many AI editing tools on the market at present. However, the difficulty lies in one is that it is still difficult to batch real podcast videos, and the other is that it is actually difficult to guarantee the effect of the placement of these batch videos.

This is because the output logic of many batch video editing tools on the market is to give priority to solving the output quantity, while the optimization of video content still needs to be fed by manually optimizing a large number of original films. The output logic of Miaosi is different in that it first has the ability to analyze scripts, high-quality content, and highlights to determine what kind of video is more capable of running the volume, followed by efficient video output based on the results of the analysis.

Take a few core features for example. For example"Merchandise Video Mashup"After the merchant has uploaded the video material, Mythic will not simply mix and cut the video content in an unorganized manner, but will first learn from the running videos of similar commodities all over the net, and then produce a highly converted selling script, and then reorganize the merchant's video material for batch mixing and cutting into a piece of output.

The most important part of the script analysis and generation, Miaosi can do based on the crowd / scene / pain points / promotional goals / price and other understanding of the commodity information, to determine the need to focus on explaining and highlighting the contents of the diversity is very strong, rather than output a simple uniform subtitle style, more like "people" edited out of the video.

another exampleDigital Oral VideoThe output capacity, Mythos provides digital people in the image and voice of anthropomorphism are optimized enough, and does not make people have a strong sense of AI, reasonably with other images for mixing, the user are not necessarily able to find out that it is a digital person.

another example"Rapid Derivative Output of Sketch Material"When you're trying to iterate on 50 videos again after you've already produced 100 videos based on a quality run direction, it's all too easy for manual writers and editors to get bogged down in lack of creativity and repetitive content.

And Miaosi can be based on the AI algorithmic ability to learn the highlight features of AMS big run short dramas, produce 50 videos in 1 hour, and can simultaneously meet the attractiveness of the video (extraction and front short drama highlights), freshness (automatic understanding of the de-emphasis mechanism of the advertising system), optimization of the over-audit rate (front pre-audit+bottom line compliance audit), greatly improving the output efficiency of the video of the short drama and enhancing the probability of the run. There are some other interesting features, which will not be elaborated here due to space limitations, and interested placement teams can start trying to experience them.

After talking about the two tools on the placement of help, we go back to the beginning of the three capabilities mentioned to see, the wonderful question can help us very well on the account data to quickly organize, analyze, in our development of the overall advertising strategy adjustment to provide empowerment, and real-time monitoring and analysis of each plan or creative cast how to dig potential risks and optimization of the space, to achieve " Finding problems fast, solving problems fast". Mythic can help us produce and iterate video content more efficiently, as well as provide certain inspiration in creation.

Wise use of two tools can greatly improve our entire placement optimization industry competitiveness. But also want to emphasize one point, we are not to blindly rely on tools to work to reduce the burden and make the work easier, so that in the long run but will continue to fall into the placement of the cost and volume of the dilemma. Rather, we want the placement and video team to have more time to spend on industry insights, crowd understanding, and creative direction extension after improving work efficiency, so that they can discover new directions for placement optimization.

The ability of AI tools are still continuing to iterate and optimize, the future will be more and more intelligent, more and more useful, the role of people must be to maintain the thinking power of the business, the reasonable use of tools for collaboration and cooperation, rather than letting the tools to free their hands and then everything is fine, I think this is also the future of the advertisement placement work mechanism may have a change.