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I see this constantly. Someone spends 20 minutes prompting ChatGPT, gets a clean-looking listing, publishes it, wonders why nothing happens. The writing isn't the problem. It's what the AI is working with. ChatGPT has no access to Amazon. No search volume data, no keyword trends, no information about what buyers are actually typing into the search bar right now. It's working from general knowledge of your product category. So it writes something that sounds like an Amazon listing but isn't built on actual demand signals. The words look right. The intent behind them is a guess. The fix is simple: feed the AI real data before you ask it to write anything. Here's the exact process I use. STEP 1: Amazon AI Keyword Research: Tools: Helium 10 + Claude (our your AI of choice) Output: Keyword spreadsheet, segmented by shopper intent a) Run Helium 10 Cerebro on your top competitors: Go to Helium 10, open Cerebro, and enter the ASIN of the most relevant competitor in your niche. Run the reverse ASIN lookup to pull their full keyword data. b) Download the full report: Export it as CSV or Excel. Keep all columns. Do not pre-filter manually. Claude will handle relevance filtering and grouping. c) Upload the file into Claude (or other AI): Open Claude and attach the Helium 10 export directly in the chat. Make sure the file is fully loaded before you send your prompt. 4. Submit this prompt, replacing the bracketed fields with your actual product before sending: "Conduct Amazon keyword research for this product: [PRODUCT LINK]. I have uploaded a Helium 10 Cerebro keyword data report for "[PRODUCT NAME / MAIN KEYWORD]". Please create a comprehensive keyword research report formatted as a spreadsheet. Follow these requirements: 1. Only include keywords that are directly relevant to my product 2. Exclude any keywords with a search volume below 500 3. Identify the core seed keywords from the dataset and group all related search term variations under each seed keyword. Each group should be named after its core seed keyword (e.g. a group called "yoga mat" would contain "yoga mat thick", "yoga mat non slip", "best yoga mat", etc.)

A new New York law kicked in today, June 9. It sounds scarier than it is, but it does affect most of us using AI creatives. Here's the clear version: What changed: If your ad or listing image shows an AI-generated person, like a fake model, fake UGC creator, or AI influencer, you now need a visible "AI-generated" label directly on the creative. Not buried in the caption. On the image itself. What's totally fine, no label needed: - AI backgrounds - AI product shots (no person) - AI-written copy - AI voiceover What needs the label: - AI face or model in an ad - AI "UGC creator" in a video or image - Any synthetic person presented as real Why it applies to you even outside NY: The law is triggered by where the viewer is, not where your business is. NY viewer = you're in scope. Penalties reportedly reach $5,000 per violation on the civil side. (Verify with your lawyer. Not legal advice.) The fix: One line of text on your creative. That's it. Copy-paste this into your next creative brief: DISCLOSURE NOTE FOR AI CREATIVES: If this ad features an AI-generated person (model, UGC creator, influencer), add the text "AI-generated" in a clearly readable font directly on the image or video. Not in the caption only. Minimum readable size, same contrast standard as your other text. Full legal breakdown from Cooley (reputable firm, worth bookmarking): https://www.cooley.com/news/insight/2026/2026-01-29-new-york-enacts-synthetic-performer-disclosure-law-for-advertisements-including-those-using-generative-ai Not legal advice. Talk to your lawyer for your specific situation.

Hey everyone, I'm Wasif.I've spent the last 5 years helping Amazon brands grow, with a strong focus on Amazon PPC and account management. Today, I run a agency with a team of 3-4 people. I'm here to learn from ambitious entrepreneurs, share what has worked for us, and build genuine connections. If you're in the Amazon space, I'd love to hear what you're currently working on

Most Amazon brands track competitors. Very few use that data the right way. The Problem: 87% of brands track competitors, but only 12% take automated action. Average response time? 7-14 days. One brand lost $23,400 in a week by responding manually on Day 7, while their competitor gained $18,900 by auto responding in 3 hours. The Solution: Stop asking What are competitors doing? Start asking How do we act before it affects our results? Track micro signals (review drops, creative updates, keyword shifts) and set automated rules: IF competitor reviews drop >15% → increase ad spend 20%. IF keyword impressions drop >25% → adjust budgets automatically. Real Impact: Brands using this framework cut response time from 5-7 days to 2-4 hours, reduce manual work from 15 hours/week to 3 hours/week, and add $78K/month in net revenue (340% ROI). Bottom Line: In 2026, competitive intelligence only works when signals drive instant action pricing adjusts ad pacing, review trends guide creative, keyword shifts move budgets. Amazon is fully AI augmented. Winning isn’t about more tools or higher bids, it’s about faster interpretation and tighter action loops. If competitor insights don’t change your daily actions, you’re falling behind. Waiting is the most expensive mistake you can make. What’s your response time when competitors move?