Practical guides for Amazon sellers: decide, execute, iterate.
A launch SOP for Amazon sellers: validate terms first, cold start with clean structure, then scale through Sponsored Products tiers.
1. Introduction: The mystery of the “randomness” of Amazon orders. First of all, a question: Q: If there is only one order for a keyword in 30 days, should I invest? The possible answers are: A: No! What if: Q: There are hundreds or even thousands of these
How an Amazon newbie used the "SP Panoramic View Naked Opening Dafa" to counterattack in 21 days to achieve cross-border e-commerce "earning money" and a surge in natural orders! (An in-depth article of over 10,000 words, it is recommended to save it for later reading) 1 Core idea: Randomness is the "low cost" with the greatest opportunity, and advertising is the greatest
Let me give the conclusion first (just remember these 3 sentences) 1. The ultimate goal of advertising is not to make the "proportion of advertising orders" beautiful, but to increase the absolute order of magnitude of natural orders. 2. Within this sample window: the proportion of natural orders remains at 72.1%, but daily
🏆 Conclusion first: Amazon’s recommended bidding range is really unreliable! ✅ More accurate: Amazon's recommended bid is on average 64.7% higher than the actual CPC; the average deviation between Satlis's predicted bid and the actual CPC is only -6.4%. 💰
🎯 1. Conclusion first Put the conclusion first: The core of SP Panoramic View is not "I control who Amazon exposes", but to first determine the candidate pool and let Amazon make the best choice for me in the millisecond auction. When using SP panoramic ad group to open massive entrances at the same time
Let’s start with the conclusion (this is also the most shocking point after completing this round of advertising): A total of 343 keywords were voted in, and 60 words were used to place orders. The average number of clicks to place orders for words was 4.8 times (the median was about 4.45 times). More importantly: 70% (42) of the words were placed
1. Give a conclusion first (remember 3 sentences is enough) "Advertising order proportion" is not the optimal goal; what is more worthy of attention is: the absolute order of magnitude of natural orders. In this sample: the proportion of natural orders is still 72.1%, while the number of daily natural orders has increased from 30 to 19
1.PR0｜General Index of Product Selection What can you take away from this article? If you are choosing a product, there are usually three things that are most likely to trip you up: It looks like there is sales, but when you go in, you find out that it is a red ocean price war. It looks like there is a chance, but it turns out that it is stuck at the review threshold/quality threshold. Obviously
1.1. Positioning of ideal competitive products analysis After completing the category judgment (blue ocean/red ocean), the next step is not to continue to look at the "big market", but to enter a more critical level: at the specific product level, identify the "ideal competing product candidate pool that can be used as a target." Ideal competitor
1.1. Design a winnable battle. This is the essence of the entire methodology of Satlis and the core reason why it is called a “ceiling-level AI agent”. After the category direction is confirmed (PR1) and the ideal competitive product image is established (PR2), the real decision is made
1. New product promotion SOP and cases 1.1. New product cold start only lacks two things (establish a sense of purpose first). The two most lacking things in the new product stage are: Display opportunities: Does the system dare to give you a natural position? Weights and labels: What demand scenarios does the system classify you into? So the cold start is
2026 Amazon Enterprise Cutoff Line: Stop "listening to AI lessons", it's time to fight with "AI systems". The original text and accompanying pictures are included in full
Practical process: Import 30-day SP report, generate keyword/product combinations, and execute directly according to quality level
How to organize SP advertising portals into stable layers, classify portals according to winning rate, and then use role-based bidding to execute them
LB1 combines executable keywords with the product fact database to form a shelf-ready copywriting package, and cooperates with compliance inspections and score revisions
KR2 engineers the verification process: first the qualification gate, then the opportunity gate, and finally generates executable keywords that can be used for copywriting and advertising
How to use keyword mining to expand intent clusters, first make the candidate entry pool larger, and then submit it to the keyword refinement library for verification
KR0 defines the complete link from word source expansion to conversion and volume, and clearly distinguishes candidate words from executable keywords
PR3 puts the analysis results into the main attack plan, covering the five levels of traffic, conversion, trust, operation and advertising space
The goal of PR2 is to screen "hittable targets" rather than "sales champions" and distinguish the target logic of blue ocean and red ocean
Use 15 dimensions to turn market data into a Go / Hold / Skip decision with clear risk gates.
Turn fragmented product research into one decision chain: market check, target lock, and execution plan.
A practical framework to reset stalled ASINs by cleaning entrance pools, stabilizing structure, and improving Top of Search IS and TACoS trends.
