u/Downtown-Escape-9600

Been dropshipping on Shopify for ~8 months. My biggest leak wasn’t bad products or shitty creatives — it was me making emotional calls on which products to scale or kill.

I’d look at Day 2 ROAS, panic, kill a product that would’ve been a winner. Or I’d “give it one more day” on a clear loser and burn another 80€.

So I forced myself to write down rules and stick to them. Here’s what’s actually worked:

Kill if:

•	Day 3, ROAS < 1.0, spend > 3x product cost  
•	CTR < 0.8% AND CPC > 1.50€ after 50€ spent (creative problem, not product)  
•	0 ATC after 30€ spent (offer/price issue)

Scale (20% budget bumps, not 2x):

•	3 consecutive days ROAS > 2.5  
•	CPA stable or dropping  
•	Don’t touch winning ad sets — duplicate instead

Test more:

•	ROAS between 1.2 and 2.0 → not dead, not a winner, needs new angles before judging

What changed for me: I stopped checking ads 10x/day. Check once in the morning, apply the rule, move on.

Got so tired of doing this manually I ended up building a small tool that pulls my Shopify + Meta data every night and outputs Scale / Kill / Test per product. Still in beta, looking for 2-3 more dropshippers to test free — happy to share more in comments if anyone’s interested.

Curious what rules you guys use. Anyone running stricter kill criteria?

Saw a few posts here about inventory sync nightmares across Shopify + Etsy.

I had the same problem so I spent the night building ShopSync — a lightweight Python tool that syncs inventory between Shopify and Etsy in real-time via webhooks.

How it works:

\- Shopify sells a unit → Etsy stock updates automatically

\- Etsy sells a unit → Shopify stock updates automatically

\- Web dashboard to monitor sync status + logs

\- Deploy on Railway in 5 minutes

Live demo here if anyone wants to see it running:

[https://web-production-98c05.up.railway.app\](https://web-production-98c05.up.railway.app)

Happy to answer questions about the technical side. If anyone wants to test it on their store I'm open to feedback.

Genuine question — when your supplier sends you a CSV with tracking numbers, what do you do with them?
Still copying them one by one into Shopify orders or did you find something that works better?
Asking because I'm spending way too long on this every day and wondering if I'm missing something obvious

Just launched my AI SaaS for Shopify dropshippers. Product is live, but struggling with customer acquisition. No audience, no email list. What actually worked for you to get your first 5 paying customers?

Kept seeing posts about oversells destroying margins for multi-channel sellers. Built ShopSync tonight — real-time inventory sync between Shopify and Etsy via webhooks. Web dashboard included. Live demo: https://web-production-98c05.up.railway.app Would love feedback from anyone selling on both platforms.

Hey everyone,

I've been dropshipping for a while and kept running into the same problem: every morning I'd spend way too long staring at numbers trying to figure out what to do with each product.

Scale it? Kill it? Give it more budget? Pull the plug?

Most of the time I was just guessing — and guessing wrong cost me real money.

So I built a tool to solve this for myself. And now I'm wondering if anyone else has this problem.

**Here's what it does:**

- Connects to your Shopify store

- Pulls your real sales data, ROAS, ad spend, conversion rate

- An AI analyzes everything and gives each product a clear verdict: **SCALE / KILL / TEST**

- You get a daily dashboard with the reasoning behind every decision

- No manual work. No spreadsheets. No guessing.

**Why I think it's useful:**

If you're spending $1,000+/month on ads, one wrong "I'll let it run one more day" decision can easily cost you $200-300. This tool catches that before you lose the money.

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I'm currently looking for **3 dropshippers to test it for free** before I officially launch it.

Not looking for anything in return except honest feedback.

**Would anyone here actually use something like this?**

Drop a comment or DM me if you're interested — happy to show you what it looks like.