SalesFortuna allows sellers - even those with zero advertising experience - to launch Amazon ads campaigns and deploy a fully structured Amazon PPC system in just two clicks.
Instead of manually building Amazon sponsored products campaigns, organizing portfolios, configuring presets, and managing match types, the system automatically creates a working structure aligned with algorithmic optimization.
This is full ad automation - not just a PPC campaign builder. It builds a complete Amazon ads infrastructure aligned with algorithmic optimization logic.
It functions as an ad automation system for launching a structured Amazon PPC automatic campaign environment without manual setup.
Launch a structured Amazon PPC system without building campaigns manually.
Sellers who want a fully structured Sponsored Products setup without manually building portfolios, match types, and defensive layers.
Automated campaign deployment, CVR-based segmentation, preset calibration, restructuring, and negative harvesting from onboarding.
A complete PPC infrastructure that launches clean, scales faster, and stays compatible with algorithmic optimization from day one.
When the seller chooses not to modify existing campaigns, SalesFortuna deploys a fully standardized portfolio structure aligned with the algorithm's logic.
Instead of maintaining hundreds of fragmented campaigns, the system builds a unified Amazon Sponsored Products (SP) structure where each campaign has a defined role.
For each selected ASIN, the algorithm automatically creates a structured campaign foundation.
Discovery campaigns
Defense campaigns
The Broad campaign is generated using Amazon generic keywords and recommended search terms provided for that specific ASIN.
The system analyzes suggested keyword data, extracts the most frequently repeated terms, and builds a clean generic keywords list for initial traffic discovery.
Each generic keyword is selected based on recurrence logic rather than manual guesswork.
This creates a structured Amazon PPC automatic campaign environment for each product, ready for optimization.
For the traffic-role logic behind those inputs, see the Generic Keywords guide and the Search Terms guide.
Before activation, the algorithm analyzes real conversion metrics across the account.
Products are automatically divided into:
Each group receives a different preset configuration including:
Configurations are automatically calibrated so that, based on each product's actual conversion rate, the campaign structure can realistically reach the target ACOS defined by the seller.
In other words, a product converting at 20% and a product converting at 8% will receive different CPC boundaries and behavioral limits, ensuring the selected target ACOS is mathematically achievable rather than theoretical.
This ensures every Amazon PPC campaign launches with behavior aligned to its real conversion profile and target profitability model.

SalesFortuna automatically builds a defensive SP layer to protect traffic and brand positioning.
When portfolios are deployed
This ensures
If the seller allows modification of old campaigns, the system performs intelligent restructuring instead of deletion.
The algorithm
Result

During onboarding, the system automatically analyzes historical search term data.
Negative keywords are generated based on:
The seller reviews and approves suggested negatives.
Approved negatives are stored in a Golden Profile list and automatically applied to all future search campaigns.
This ensures that every newly deployed campaign starts with clean traffic filters.
For the underlying blocking logic, see the Negative Keywords guide.

After confirmation, SalesFortuna
The seller does not need to understand
From that moment, the algorithm manages performance across SP, SB, and SBV campaigns - while campaign creation and structural automation are executed at the Sponsored Products level.
The system builds and deploys the entire Amazon ads and PPC infrastructure automatically.
Free Trial - No Credit Card
14-day free trial. SalesFortuna optimizes bids 6× daily, harvests negatives,
and adjusts strategy based on real conversion data.