r/AmazonFBATips

Amazon Seller 101: I made a small CLI to find customer pain points before sourcing

Amazon Seller 101: I made a small CLI to find customer pain points before sourcing

A lot of Amazon product research starts with demand, price, competition, keywords, margin, all that stuff.

Obviously useful. But ngl, I feel like sellers sometimes skip the most obvious part:

What are customers already annoyed by?

Bad packaging, wrong sizing, cheap material, confusing setup, missing accessory, unclear instructions, weird smell, battery dies too fast, product looks different from the photos, etc.

That stuff is basically free product research. If the same issue keeps showing up across competitor products, it’s either a red flag or an opportunity before you even source.

The annoying part is doing this manually. You open a bunch of competitor ASINs, read through customer language, take notes, copy/paste into a doc, then try to turn that into product specs or listing ideas. It works, but it’s slow and super easy to bias toward what you already wanted to believe.

So I made a small open-source CLI for this.

You put in an Amazon ASIN, and it gives you a quick first-pass report around customer pain points, selling points, buyer language, and listing improvement ideas. Not meant to replace seller judgment. More like a starting point before you spend hours digging manually.

Also made it CLI-based because I wanted something that could plug into agent workflows later, instead of another dashboard I have to babysit.

Curious how other sellers/agencies are doing this today. Are you actually looking at customer pain points before sourcing, or mostly relying on sales estimates + keyword tools?

Repo is on GitHub: https://github.com/mguozhen/voc-amazon-reviews

u/mguozhen — 13 hours ago

Most Amazon appeals fail for one stupid reason.

It's not the writing. It's not the violation severity. It's that sellers try to convince instead of just matching the structure Amazon wants.

I went through 500+ suspension cases. The ones that win don't sound like lawyer letters or emotional pleas. They just: name the violation clearly, show exactly what changed, and stay short enough to scan in 30 seconds.

Everything else gets the copy-paste rejection.

Anyone else noticed this or am I just staring at too many appeals?

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u/mikael_endale — 20 hours ago

A new-product ads playbook I actually follow, step by step

Most sellers I talk to can open campaigns, stuff keywords into a listing, and swap main images. What they don't have is a launch plan. So the ads drift. One week it's about rank, the next it's about ACoS, the next it's about scaling spend, and nothing finishes.

Here's the sequence I use when I launch a new ASIN. It's boring on purpose.

**1. Decide what the ads are actually for**

New-product ads have two jobs: push the organic rank of the keywords you care about, and pick up orders at an ACoS you can live with. Early on, the rank job matters more. Weight is low, there are no reviews, organic position is buried. Judging a cold-start campaign by pure ad profit is misreading the stage. If ads are lifting your keyword positions and feeding the associated placements, short-term losses are often fine.

**2. Answer these before you open the campaign**

- Is this a long-term hero SKU, a seasonal SKU, a test SKU, or filler?

- How long is the launch window?

- Does your first inventory run plus restock cadence actually support sustained ad spend?

- What are the week-1 targets for orders, sessions, keyword rank?

- What's the cap on daily spend, and what's the stop-loss?

- Is phase one about testing creatives and price, or purely about rank?

If any of these are fuzzy, the campaign will flip between goals and never finish any of them.

**3. Learn manual exact before you bolt on anything else**

I know auto campaigns are the default recommendation. I still don't start there. Manual exact with a tight keyword set gives you the cleanest signal: who clicks, who converts, who burns budget. Fewer campaigns, less noise, easier calls. Add auto, product targeting, SB, and SD once the core story is clear.

**4. Structure for week one**

Small ad groups. No more than three exact or long-tail keywords each. Give every group enough daily budget to run uninterrupted for roughly a week. This is the only way to tell which keyword is actually driving the results instead of splitting your budget across 30 terms and seeing nothing.

Pick keywords before you run, not after. Reverse-search competitors, pull a short seed list, and prioritize terms where the first page still has gaps. Precision beats volume.

Match types: start with exact and phrase so you control where traffic lands. After data stabilizes, layer in broad on top, but keep exact as the workhorse and phrase as the scaler. Broad only enters when you need discovery or long-tail coverage. If rank is the goal, exact. If you need safer expansion, phrase.

Auto's role in week one is a sanity check: does Amazon read your listing the way you intended? Product targeting should also go live early, aimed at direct competitor detail pages. Keep those bids high enough to actually show. A low bid on a competitor page is a wasted line item.

**5. Placement strategy**

Top of search is expensive, but it pulls organic rank faster than anything else. Product pages are where you pick up associated traffic and cross-sell your own catalog. If the budget is tight, rest-of-search holds you in position at a lower CPC so the core keywords don't fall off the map.

**6. What to actually watch in week one**

Three numbers:

- CTR. If CTR is weak and the keyword is right, the problem is main image, price, title angle, or review count. Ads can't fix a listing that doesn't compete on the search page.

- Burn rate. Start bids near the suggested midpoint. If budget empties early, CPC is climbing too fast. Cheap effective clicks beat expensive top placements in the first week.

- Organic rank on your target keywords. This is the number. If spend is happening and rank isn't moving, something upstream is wrong: keyword fit, product competitiveness, or listing quality. Fix that before adjusting bids.

**7. Tuning after it's live**

- Don't adjust daily. Run three days, then decide. Most "issues" in the first 48 hours are noise.

- No impressions, no clicks: likely bid. Raise 10-20% and watch another few days. Don't slam the bid up, a new product with a runaway CPC bleeds fast.

- Impressions but no clicks: search the keyword on the front end. If your ad is buried on page three, it's bids. If it's on page one and still ignored, it's main image or price.

- Stop-loss cleanly. Inside a single campaign, once keywords separate into winners and losers, cut the losers. Move that budget into a new campaign testing new terms.

- Shift from dashboard-watching to weekly reviews. Pull the report, pick the keywords that are consistently clicking, converting, and controllable on ACoS, and give them their own campaign, budget, and exact targeting. That's how structure gets cleaner over time.

**8. Four-week rhythm for a competitive category**

Week 1, cold start. Simple structure. Lower price plus a strong coupon (around 20% off), Vine enrolled. Point is to confirm the creative works and that a handful of keywords convert.

Week 2, scale. Ratings start showing up. Raise daily budgets. Pull any winning search terms from auto into their own manual campaigns. Increase product-targeting share to pick up more associated traffic.

Week 3, weight building. Core keywords start lifting organically. Widen into long-tail and related placements. If organic rank is climbing, you can ease off the coupon. Prune underperforming terms.

Week 4, harvest and hold. Ad-order share goes down as organic carries more weight. Concentrate spend on the keywords you've proven. Run a Deal or Lightning Deal to lock the core keywords into the first two search pages.

**9. Common ways new-product ads fail**

- Auto-only. Feels easy, ends up training the system on the wrong signals. You waste the cold-start window.

- Too many manual keywords on day one. Budget is diluted across everything, and no single term gets enough clicks to tell you anything.

- ACoS tunnel vision. If you only look at ad profit, you'll cut the ads that are quietly pushing rank, and the listing sinks.

- Impressions that don't matter. If your ad placement is on page four, those impressions aren't real opportunities. Rank won't move from ghost traffic.

- No phase plan. Running auto, manual, and product targeting with no idea which one is supposed to drive rank, which one is discovery, and which one is defense. Busy dashboard, zero direction.

- Ignoring the listing itself. This is the one that kills launches quietly. If the main image, price, reviews, or A+ can't carry traffic, ads will amplify the problem, not fix it. Ads are a magnifier. Whatever the product is, they make more of it.

**10. If you're about to launch**

Don't run every lever at once. Set the goal, build the structure, read the signals, then tune. One phase at a time.

The winners in new-product advertising aren't the ones spending hardest. They're the ones who can name, out loud, what each campaign is for this week.

Still refining these notes as I run more launches. If you're running this with a live ASIN and want to compare numbers, a small Discord where a few of us trade notes is open , drop a comment and I'll share the invite.

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u/Proud-Skin-3697 — 1 day ago

Do not pay for repricers in 2026

In 2026, winning BB is not longer a thing as the model has changed so that the BB rotates constantly based on your account standing and metrics not your price.

90% of a repricer job is to win BB with price, that longet translates to conversions. So even not using a repicer at all is better now or using amazons own, you are wasting your money other wise. You can google this.

reddit.com
u/Significant-Ear-9040 — 16 hours ago

Is there really a “best Amazon FBA niche” in 2026… or is that the wrong question?

I’ve been seeing a lot of people chase trending niches—pet products, skincare, fitness—thinking that’s the shortcut to success.

But here’s the reality:

Most sellers don’t fail because of the niche.
They fail because they pick the same niche the same way as everyone else.

I broke down what’s actually working in the US market (and what most people get wrong) here:
👉 https://www.linkedin.com/pulse/what-best-amazon-fba-niche-2026-us-market-reality-balasubramanian-ny6gc/

Curious—are you still choosing niches based on trends, or on real data?

u/Lost_Albatross7593 — 1 day ago

pick and pack costs when using 3PL for FBA overflow, how i finally figured out what i should actually be paying

u/Ilikeyourmom93 — 2 days ago

Is there any service anyone can recommend for helping design your first product listing with pics & text

u/DonkChonk4 — 2 days ago

I lost $1,600 on my first FBA product. The supplier wasn’t the problem. I was.

I launched a home organization product in March last year. $29 price point, top sellers under 150 reviews, solid demand numbers on Helium 10. Spent six weeks on research before touching anything.

Found a supplier on Alibaba with Trade Assurance, good response time, and photos that matched exactly what I needed. Ordered 200 units at $5.10 per unit without ordering a sample because the profile looked legitimate and I was impatient to move.

Units arrived at the FBA warehouse and I got my first customer photo in a review three weeks later. The product was arriving with a surface finish that looked nothing like the listing images. Not damaged in transit. Just manufactured differently from what was photographed. Two reviews mentioned it specifically. My conversion rate dropped and never recovered.

I pulled the listing after seven weeks. Lost $1,600 across product cost, shipping, FBA fees, and ad spend chasing a conversion rate that was never going to fix itself.

Second product I ordered samples from four suppliers and spent two weeks comparing them physically before committing. I bought a small digital scale and calipers during a $10 off every $100 spent promotion at Amazon to measure and document everything against the supplier spec sheet. That product did $7,200 in its first 60 days.

The sample cost me $140. Not ordering one the first time cost me $1,600.

Always order the sample.​​​​​​​​​​​​​​​​

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u/maveriCkharsha — 4 days ago