You aren’t alone.
When the engine is involved in a case study of the incredible results of its latest automatic account management system, often more work is needed to generate the right conditions for successful automation.
Automation is to be useful for meeting specific needs.
It is an easy way to show that the performance of automation depends on external factors. I used this concept at the founder’s showcase of FreeAdWordsScripts.com (Optimizer now owns it).
The revelation said that efficient automatic systems (such as autonomous vehicles) it is useful for marking the road.
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It seems clear.
But now, if we have the best way, but our GPS is closed, are we trying to get to the wrong place?
We need clear goals, measurements, and sensors that help us.
To make it a CPP world, we need:
- The account has been created well.
- Fix conversion data.
- The correct alert model (index: the exact alert model is not the last click alert).
The Machine Depends on the Correct Data on Learning
As the name means, machine learning models are systems to learn to do something.
There are different ways to achieve this learning ability. Usually, this machine depends on the device’s payment or prediction decision, and the decision is not according to the desired results depending on the payment process.
I give you a simple example of explaining my day on the Google Quality Team.
The machine learning model verifies the auction’s historical data. View all user-clicked search criteria and ad features.
Compare these credentials to your advertiser’s domain (for example, users of France can associate with more ads). The fifth attempt matches the person’s location when this click’s rate is the domain may be better and faster than just in the area.).
The machine can understand because Google has useful clickthrough rate data.
But what happens if your click is not valid? After this, the system can begin to strengthen the decision of the person that he has made to make a mistake.
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It considers “healing, emotional.” It is the principle that the right decisions are based on useful information.
Because machines do not lack human decisions, they are more dependent on useful social data. They cannot quickly determine their reasonable predictions because they cannot water in the real world.
So, how can we provide accurate information automatically? It all starts with a conversion tracking and warning model.
Attribution Models Should Reflect Typical Consumer Journeys – Last-Click Attribution
Unless you have firm brand loyalty, you can perform multiple searches before purchasing, and there will be various points of contact with several brands during the call period. Client Travel
There are hundreds of steps in the client’s journey. To simplify, imagine the conversion final, where different courses are divided into several stages.
If you have a very important warning model when using automation in your account, use the most beautiful pictures of the fan to describe.
Potential customers pass through different stages in the finals until some end up at the bottom of the finals and become their customers.
This step helps every step in the fireplace to change the likelihood of customers, and the attribution model gives the correct values at each level.
As I said earlier, most journeys are far more than a natural step.
The last click in the warning model (or the first click in the model) shows only one step and, therefore, is unsuitable for user behavior.
He ignores potential customer contributions at the second stage of the client.
Most users research very much and need to guide the customer conversion process. Incorrectly attributed to the last click, it assumes that previous contact points cannot be evaluated. For example, looking for an advanced final helps potential customers find a search that would typically be closer to the conversion.
Account managers can, therefore, handle non-competitive warning models because, in manual accounting management, we can expect account managers to understand that the user can find [washing machines] to follow this user. Do not need to change the next click.
By educating your brand’s credentials, this user can become familiar with the brand and find something special, such as [LG Washing Machine].
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From there, you can see the entire range of ads and may be convinced to search for
[the best price of LG TWIN Wash]
and convert it to the next click.
Our dependence on human sensitivity does not end up with past searches, although they cannot produce Google advertising changes.
Human Fail safes for Bad Attribution Data Don’t Work with Automation
But now, PPC is getting more automated every day. When clicking on the target based on the target CPA objective of finding expensive keywords or using a rule-based approach (such as the use of the engine of Optimizer rules), you try smart offers. Can decide to There was no change in it.
The problem is that most of them use conversion data to perform their work automatically.
When they encounter a popular channel keyword with non-popularized conversions, automation determines that it is not worth the critical keyword because the metric uses the last-click warning. It’s over There is a risk of doing it.
It is clear that it will produce bad results for you and me. But we cannot automatically accuse ourselves.
It can work automatically, but because data is incomplete, it can be compelled to force fraudulent decisions that are not accounting.
The Takeaway – Last-Click Attribution
I hope you learned three things from this article:
- The the mission is less effective than magic. He always needs human help.
- If you use it automatically, the way you value conversion is far more critical. Finally, clicking on a property is a dangerous operation used with automation.
- As CFC professor, our mission goes to execute the right combination of the automation system to produce outstanding results.
I cannot finish this message without answering any key questions.
What model should we use if we cannot count on the last-click alert?
It is a complicated answer, which I will answer in a future article, but time-saving models are a clear choice for advertisers who do not know which options Google offers.
Read also: Predicting the ROI of SEO
Time deficiency is similar to the last click, but it also has the advantage of assigning at least some values at each stage of the customer journey.