How This Amazon Seller Uses Helium 10 as the Data Engine Behind an AI-Powered Optimization Workflow

Introduction

Arnold Lau took over an existing Amazon business with products sold across multiple Amazon marketplaces, including the US, Canada, the UK, and Australia. While he was not new to ecommerce, stepping into an established Amazon operation meant he needed to quickly get up to speed on performance, campaigns, and product opportunities across a growing catalog. 

To manage that complexity, he combined Helium 10 data with AI, building a scalable workflow to monitor performance and optimize his business. 

Challenge

Like many brands managing multiple SKUs across multiple marketplaces, Arnold faced a workflow problem. He had data across each marketplace, but pulling it together, reviewing it consistently, and turning it into action took time and tedious manual effort. 

Before building his current process, campaign optimization meant manually clicking through products, marketplaces, search terms, and campaign details one by one to figure out what to scale up, scale down, isolate, or negate. Amazon had raw data, but the way that it was formatted made it unfeasible to load into an AI model, meaning any decisions made by Perplexity wouldn’t be based in facts. 

Even beyond formatting, Amazon’s data alone lacked the competitor and keyword insights needed to fully understand market positioning and opportunity. Balancing ongoing optimization with growth opportunities, Arnold needed a way to process information more efficiently without sacrificing the quality of the decisions being made.  

Solution

Arnold built a weekly optimization workflow that combines Amazon’s real performance data with Helium 10’s proprietary keyword intelligence, then feeds both into an AI-powered analysis and workflow using Perplexity. 

Instead of relying on Amazon data alone, which is inherently limited to what has already happened inside his account, Arnold enriches that dataset with Helium 10 keyword data, which provides competitive insights and broader market context. 

He is also able to work much faster with his Amazon data by dealing with the consolidated and organized formats within Helium 10.  

Currently he pulls in: 

• Search Query Analyzer to understand real conversion and search term performance from Amazon  

• Cerebro to layer in keyword volume, competitor rankings, and untapped search demand he wouldn’t have access to otherwise 
• Profits to incorporate financial performance and ensure decisions align with profitability.

| “Helium 10 pulls everything together in a way that makes the data much easier to understand.”

Results

By combining Amazon data with Helium 10’s proprietary keyword insights, Arnold has fundamentally improved the quality of his decision making. 

Rather than optimizing based on a partial view of performance, he now operates with a more complete dataset that captures both conversion reality and market opportunity. 

This shift has led to: 

• More confident campaign decisions, grounded in both actual performance and validated keyword demand  

• Time savings of 1–2 hours per day on PPC optimization, by eliminating the need to manually click through each marketplace and campaign 

• Faster optimization cycles, as AI processes large datasets across multiple marketplaces in minutes instead of hours  

• Improved ability to identify growth opportunities, including high-volume keywords and competitor gaps that would not be visible in Amazon data alone  

Most importantly, Arnold is no longer limited by the constraints of Amazon’s native data. By pairing it with Helium 10’s broader market intelligence and rich datasets, he can make decisions with a clearer understanding of both where his business stands today and where it can grow next.