Breaking the Profit Plateau with Full-Funnel Optimization

The Problem: The Hidden "Relevance Penalty"

In the personal care and beauty space, shoppers love to browse. They search broad terms like "organic face wash" or "night cream," scroll past dozens of products, and click around before making a decision.

For this brand, their campaigns were showing up for millions of these broad searches. They were getting a massive amount of impressions, but only a tiny fraction of shoppers were actually clicking their specific products. On the surface, impressions look like a good thing. It feels like free brand awareness.

But Amazon's algorithm does not see it that way. When Amazon shows your product 10,000 times and only 10 people click it, the algorithm concludes that your product is not highly relevant to that search term. Amazon responds by lowering your relevance score, which actively inflates your Cost-Per-Click (CPC) across the board. You end up paying a premium just to participate in the auction.

The brand's highly capable team knew this was happening, but finding these high-impression, low-click keywords across hundreds of campaigns is an exhausting, time-consuming process. Manually calculating the Click-Through Rate (CTR) for thousands of individual keywords every few days was simply not sustainable.

The Agentic Solution: Aggressive Funnel Cleanup

To break through the plateau and lower their TACoS, the brand needed to structurally improve their account-wide CTR. Amazon needed to see them as highly relevant. They deployed Clair's agents to act as a ruthless quality control layer at the very top of their advertising funnel.

1. Identifying the Top-of-Funnel Waste

First, the team used the agents to map out exactly where the impressions were leaking. Clair (The Orchestrator agent) scanned the brand's entire catalog and advertising history to build a complete funnel analysis.

The analysis showed exactly what the team suspected: a huge chunk of their ad spend was being dragged down by thousands of broad search terms that generated massive views but terrible engagement.

2. Enforcing Strict Performance Thresholds

Instead of having humans download reports every week to manually pause bad keywords, the team set up a continuous, automated rule.

They instructed Clair with a simple, natural language prompt: "Find all keywords with a Click-Through Rate (CTR) below 0.3% and more than 1000 impressions over the last 14 days, and pause them to improve campaign relevance scores."

From that moment on, the agents ran this query relentlessly in the background. Every time a keyword triggered this threshold, the agents surfaced it directly in the Pending Approvals queue on the dashboard.

3. Reallocating Budget to High-Intent Targets

Pausing bad keywords stops the bleeding, but scaling requires putting that budget to work. By constantly pruning the low-CTR targets, the brand freed up a significant amount of daily ad spend.

The agents automatically reallocated this saved budget toward exact match campaigns that had proven, high conversion rates. The brand stopped trying to be visible to everyone, and started paying to be visible only to the shoppers who were ready to buy.

The Outcome

By aggressively pausing low-relevance impressions and enforcing strict performance thresholds, the brand completely shifted their standing with the Amazon algorithm.

Within a few weeks, the brand boosted its account-wide CTR by a massive 22%. Amazon rewarded this higher relevance score with noticeably lower CPCs across the board.

This structural improvement resulted in a 17% overall reduction in their TACoS. By letting the agents handle the exhausting task of keyword cleanup, the human team was able to focus their energy on creative optimization, listing SEO, and launching new products.