The conclusion first (this is also the most shocking point after completing this round of investment):
A total of 343 keywords were submitted
Yes 60 word order
Average clicks to place an order = 4.8 times
(median about 4.45 times)
More important: 70% (42) of the words are issued, and the order is completed within 5 clicks
What does this mean?
It means that if your advertisement can achieve this kind of "quick feedback", all subsequent optimizations (increasing budget, increasing volume, expanding words, and grouping) will be much smoother.
But here comes the problem:
Why do many people's advertisements become slower and more confusing?
- Many people do the wrong thing when advertising: you want to "control exposure" and the platform operates in a "millisecond auction"
The habits of most operations are:
"I control who is exposed on Amazon" "I can manually adjust the bid to direct the traffic to the words I want."
The reality is:
Ad distribution occurs in millisecond-level auctions, and it is difficult for you to control which word each exposure falls on by "manual command".
A more feasible approach is actually:
You do not grab the right to choose, you are only responsible for making the "entry pool" accurate.
Let the platform automatically select and amplify the "currently better quality" entrances from your entrance pool in every auction.
A human saying summary:
The entrance pool is large enough + accurate enough → it is easier for the platform to hit effective traffic → it is easier for you to see the fast feedback of "orders are placed in a few clicks".
- Why is the "keyword line" often faster than the "ASIN line"?
We observe a very stable difference:
Keywords usually produce results faster than ASINs.
Indicators
Keyword line
ASIN line
Conclusion
Total number of entries
343
13
Number of exit orders
60
9
Inlet conversion rate
- 50%
- 20%
ASIN line entrance makes it easier to place orders
Average click-through orders
- 80
times
- 86 times
Keyword lines are more efficient
Total order contribution
570
Single
74 singles
Keywords are the absolute main force
The reason is not complicated:
Keywords are closer to clear purchase intention ("I'm here to buy this")
ASIN is more related to traffic ("I was planted/associated/recommended"), and the intention is more scattered and random, so the feedback is slower
So you will see:
Keywords are like "quick knife" and ASIN are like "slow fire".
Slow does not mean bad, it just requires a longer window to converge.
- Turn "quick feedback" into replicable growth: the core only does two things
- The first thing: caliber alignment (power on at the same time)
Don't open one group today, another group tomorrow, and another group the day after tomorrow.
The entrance is not synchronized, the data caliber is chaotic, and it is difficult for you to judge who is contributing to the growth:
- The second thing: layered management (noise reduction first and then amplification)
Don't mix and manage all entries together.
Separate the entrances of different "certainty/volatility/cost structures", and your data will become clearer and clearer, instead of becoming more and more confusing.
Suppress the noise first, then it will be easier for the platform to "pick the right people" from your entrance pool:
- The SOP can be copied directly (recommended for collection)
You don't need to pursue "extreme parameter adjustment" right from the beginning.
In the first round of delivery, if the structure is smoothed first, the effect will be much faster.
Step 1: Unify statistics window
Use the same time window (such as the past 30 days) to view all entries to avoid confusion.
Step 2: Set up the entrance pool at one time (open at the same time)
Keywords, ASINs, different match types... don't add them slowly over several days.
Step 3: Create groups according to "hierarchical structure" (key)
You can simply understand it as three layers:
Convergence layer (super keyword): more stable, more certain, more suitable for tilted budgets
Incubation layer (high potential keywords): It takes time to verify, but it is worth running the data
Isolation layer (high competition keywords): high volatility, high cost, easy to interfere with the overall judgment of the entrance (separate budget control)
Step 4: Complete an attribution rhythm (it is recommended to watch the first round in 14 days)
Don't start making major structural changes within two or three days, as this will destroy the data.
Step 5: Only do two actions: migration + tilt
An entrance with stable and fast feedback → Migrate to the "convergence layer" and gradually tilt the budget
Entrances that are volatile, expensive, and interfere with judgment → stay in the "isolation layer" and control the budget independently
Step 6: Second round of refinement (bid/budget/no words)
Run the structure first in the first round, don't rush to chase the "perfect bid".
- Why does this method make you feel faster?
Many people think:
"Fast feedback depends on luck and popular words."
But this round of data is more like proving another thing:
Fast feedback does not rely on a magic word, but on the "film hit" brought by the quality of the entrance pool .
When your entrance pool is large enough and accurate enough, the platform will have a higher probability of "selecting the right entrance" in every auction.
So what you see is no longer "an order is placed occasionally", but "multiple entrances are placing orders continuously".
This is the essence of "advertising speed":
It's not that you are better at adjusting bids, but that you have done the right thing about the entrance pool.
- A conclusion that can be implemented
If your ads are getting more confusing and expensive, there is a high probability that you won't adjust your bids.
What you are missing is:
First use the structure to make the entrance pool accurate → Suppress the noise → Align the data caliber → It is easier for the platform to hit effective traffic → Fast feedback will appear naturally.
After the quick feedback appears in the film, we can talk about budget tilt, volume improvement, and word expansion, and you will be much smoother.
If you want me to write down the specific grouping template of the "hierarchical structure" (how to divide keywords/ASINs, how to place matching types, how to allocate budgets) into a table that can be copied directly, I can post another "template version".
For more detailed theory + data analysis, you can read:
《
Sakata Sales internal data analysis: The secret of Amazon advertising millisecond-level coupling (average 4. 8 clicks to place an order)
》