Guides, teardowns and hard numbers from the team building DataDoe — how sellers actually work their Amazon data with Claude, and what we learn shipping it.
AI agents can now operate a browser. Why clicking through Seller Central breaks, when it is fine, and why a data layer is the better route for Amazon.
ChatGPT dots are OpenAI's always-on agents. What they are, five Amazon jobs they suit, how to give a dot your Amazon data, and where a human should approve.
GPT-6 Astra is OpenAI's new flagship model. What it can do for Amazon sellers and vendors, where it stops, and how to connect it to your Amazon data.
Should you hire an Amazon seller virtual assistant or use AI? Which tasks to give a VA, Seller Assistant or an AI agent, what each costs, and the guardrails.
The best AI tools for Amazon sellers in 2026, sorted by job: Amazon's free Seller Assistant, the Selling Partner plugin, Ads MCP, research suites and more.
Project Amelia became Amazon Seller Assistant. See what changed from 2024 to Accelerate 2026, what it can do now, how to switch it on and where it stops.
Seller Assistant Workflows explained: the five pre-built workflows, custom workflows, knowledge bases, approvals, and what they cannot do.
The Amazon Selling Partner plugin (Amazon Selling Partner MCP) brings Seller Assistant into Claude. Setup, skills, limits, and how it compares.
Amazon Seller Assistant explained: what Amazon's AI seller assistant does, the Accelerate 2026 updates, how to turn it on, and where it stops.
Seven production-ready Amazon SP-API MCP workflows: daily syncs, restock alerts, settlement reconciliation, Buy Box tracking, returns and approvals.
Amazon shipped its first official MCP for SP-API. Two servers, 36+ tools, AWS Step Functions under the hood. Setup, every tool, real examples, gotchas.
Viral Claude skills pull Seller Central reports for one account at a time. Here's where they stop and where a data layer like DataDoe takes over.
What an Amazon data MCP is, how it gives Claude, ChatGPT or Cursor your Seller Central, Vendor Central and Ads data, and what AI agents can build with it.
How Amazon’s Public PII Process gates customer addresses and gift messages, and why it matters when choosing an Amazon data provider for your AI agents.
Why a maintained Amazon data layer beats raw SP-API access for any team trying to ship dashboards, alerts and AI tools — and what changes between the two.
A practical guide to detecting and reacting to Buy Box loss across your Amazon catalog — how the data flows, what to alert on, and how teams build it.
How to calculate true margin per SKU on Amazon — accounting for FBA fees, ad spend, returns, settlements and COGS — and avoid the most common mistakes.
Reporting across every Amazon marketplace in one unified dataset — currency normalization, schema reconciliation, and what good looks like.
Why Amazon’s default restock recommendations leave money on the table for many sellers, and how to build a smarter restock signal grounded in your real data.
How to read the Amazon Search Terms Report properly — search frequency, clicks and conversions — and turn it into actionable PPC and listing decisions.
Vendor Central and Seller Central look similar on the surface, but the data structure is very different. A breakdown for teams running both.
What Amazon Brand Analytics actually gives you, what it does not, and how brand owners use it alongside their own data layer for real decisions.
A practical breakdown of the fees Amazon charges FBA sellers — fulfillment, storage, referral, removal — and how to track them properly per SKU.
How Amazon charges FBA storage fees — monthly rates, long-term surcharges, peak season multipliers — and how to spot aging inventory before it hits.
How Amazon settlement reports work, what each line means, and how to reconcile disbursements against your finance system without manual spreadsheet work.
ACoS measures ad spend efficiency. TACoS measures total business health. Which one to optimize for, when to use each, and the trap of looking at one alone.
Amazon’s Account Health dashboard summarizes a lot of fragmented data. A breakdown of each metric, where it comes from, and what trips it.
FBA and FBM look interchangeable at a glance but the data, fees and metrics behind each fulfillment method work very differently for sellers.
Pan-European FBA pools your inventory across EU marketplaces. The reporting that comes with it can be confusing if you do not know where each number lives.
Inventory velocity drives every restock decision. How to calculate it properly per SKU, what window to use, and the most common mistakes teams make.
Amazon’s returns data tells you exactly why customers send products back. How to read it, what patterns matter, and how to turn it into product improvements.
Sponsored Products and Sponsored Brands serve different purposes and report data differently. How to read each, when to use which, and how to compare them.
Sponsored Display has the most audience options of any Amazon ad type. A practical breakdown of which audiences actually drive sales — and which waste budget.
Amazon’s catalog data — titles, bullets, A+ content, variations — is exposed through SP-API. How to use it for listing audits and ongoing optimization.
Amazon Brand Registry unlocks data and tools brand owners cannot get any other way. A practical breakdown of what is included and what to actually use.
Amazon owes most FBA sellers reimbursements they never claim. How the data flows, what to track, and how to detect lost or damaged inventory in your reports.
Amazon DSP reporting through API has gotten more flexible recently. What is available, what is not, and how to combine DSP with the rest of your Amazon data.
Late Shipment Rate is one of the metrics most likely to put your account at risk. How Amazon calculates it, what counts and how to monitor it ahead of warnings.
Order Defect Rate is the most consequential Account Health metric. What it measures, what trips it, and how to track the underlying signals daily.
Listing hijacking can drop your sales overnight. How to detect unauthorized sellers on your ASINs through data and react before they erode your brand.
Subscribe and Save delivers predictable recurring revenue for the right products. How the data flows, what to track, and which categories actually benefit.
Lightning Deals are sold as a way to drive sales spikes and rank improvements. Whether they actually pay back, by the numbers, depends on what you measure.
Most product launch failures could be predicted from data. The signals that separate winners from losers exist in your account before launch — if you read them.
A+ Content lifts conversion on most product pages. How to measure the actual lift, what tests to run, and how to scale what works across your catalog.
Amazon’s Buy Box rotates faster than humans can react. How automated repricing algorithms compete and what data drives them.
SP-API rate limits punish naive integrations. How Amazon throttles requests, what the limits actually are, and how to design ingestion that scales.
Long-tail keywords carry less volume but higher intent. How to find them in Amazon’s data, evaluate them, and turn them into PPC and listing wins.
Our 2025 launch post. Today DataDoe is the Amazon data and action layer for AI agents: MCP, API and BigQuery, with read and write access.
Vendor performance, forecasts, COGS, traffic, returns, and inventory health — now native in DataDoe. Just ask.
How DataDoe came to be in 2025, and how the idea grew into the Amazon data and action layer for AI agents.
Every playbook here works on your own Seller, Vendor and Ads data. Connect in about 5 minutes and let your AI read it — and act on it — the same day.
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