Amazon's suggested bids are designed to maximize their revenue, not yours. Rel knows the algorithms behind them — and uses that edge to grow your business.
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Capabilities
Amazon suggests bids to maximize clicks. But your real strategy is more nuanced — oversaturating pages for brand exposure, accelerating sales to clear stock, or sharpening efficiency. Rel adapts your bidding to your actual business goals.
Top-of-Search converts at 5x the rate of Rest-of-Search, yet most sellers bid the same everywhere. Rel siloes targets and independently optimizes each placement — because Amazon's "optimal" bid on a bad placement still loses money.
Exploits performance patterns most sellers never see — cold starts, target score resets, strategic recreations that reset algorithmic history. These are the mechanics Amazon doesn't document, and Rel uses them to your advantage.
LLM embeddings match your listing copy against real search queries to optimize relevance — subtly and naturally, without keyword stuffing. Your listings rank for the terms that matter without reading like a thesaurus.
Automatically finds and negates search terms burning budget with zero conversions, reallocates spend from underperforming placements, and flags inventory risks before storage fees hit.
Go beyond ROAS and bid value. Set higher-level objectives — brand exposure, inventory velocity, ACoS targets, seasonal ramps — and let Rel translate strategy into granular campaign-level execution.
We built Rel because we spent years managing Amazon campaigns and learned that the platform's own suggestions — suggested bids, default placements, auto campaigns — are optimized for Amazon's revenue, not yours. Rel encodes that hard-won knowledge into an AI that manages campaigns the way an expert would: with nuance, strategy, and a real understanding of the algorithms behind the algorithms.