Why Most Sellers Lose Money on Their First 10 Products
They research a product in their head, feel good about it, and source it. No record. No numbers. No comparison. When it does not sell, they cannot figure out what went wrong — because there is nothing to review.
A product research sheet fixes this completely. It turns research from a feeling into a system. You document every product you evaluate, every number you check, and every decision you make. Weeks later, you can look back and see exactly why you chose some products and skipped others.
This is not about being organised for its own sake. It is about having a repeatable process that you can improve over time. When a product fails, you review the sheet row and learn. When a product wins, you find more products that match the same numbers. The sheet is your training data.
The 9 Essential Columns for Every Product Research Sheet
These nine columns capture everything you need to make a confident sourcing decision. Add them in this exact order — left to right — so your eyes flow from research inputs to final verdict.
Setting Up the Google Sheets Formulas
Open Google Sheets. Create one row per product evaluated. Use these formulas in the corresponding columns:
Column E — Sell-Through Rate (STR)
Assuming Column C = Sold/Month and Column D = Active Listings:
=IF(AND(C2>0,D2>0), ROUND(C2/(C2+D2)*100,1)&"%", "—")
This calculates STR as a percentage. Cells where sold or active data is missing will show a dash instead of an error.
Column H — Estimated Profit
Assuming Column F = Avg Sale Price and Column G = Buy Price:
=IF(AND(F2>0,G2>0), ROUND(F2 - G2 - (F2*0.131) - 4.5, 2), "—")
This deducts 13.1% total eBay fees and a flat $4.50 shipping cost. Adjust the shipping figure for your actual model (dropshipping = higher, local sourcing = lower).
Conditional Formatting for Decision Column
Select your decision column → Format → Conditional Formatting → Custom formula:
- Green background:
=I2="✅ PURSUE" - Red background:
=I2="⛔ SKIP" - Yellow background:
=I2="🔄 REVISIT"
Your sheet will now colour-code every row the moment you enter a decision.
Three Optional Columns Worth Adding Later
Once you are comfortable with the 9 core columns, add these to deepen your analysis:
- Trend Direction: Rising / Stable / Declining — based on a 6-month Google Trends check
- Brand Risk: Yes / No — is the product a branded item that could get a VERO takedown?
- Source Lead Time: How many days from order to customer delivery? Over 30 days damages seller metrics.
How to Use the Sheet as a Daily Decision Engine
Research 5 to 10 products per session. Fill every column for each one. Never source a product that does not have a completed row in the sheet. At the end of the session, sort by STR descending. The top products with STR above 50%, active listings under 300, and profit over $5 are your shortlist. Put them in the REVISIT column and check again in 3 days. If the numbers hold, pursue.
Key Takeaways
- A product research sheet replaces guesswork with documented, reviewable numbers
- The 9 core columns are: Keyword, Category, Sold/Month, Active Listings, STR, Avg Price, Source Price, Profit Estimate, Decision
- Use Google Sheets formulas to auto-calculate STR and profit — saves time and eliminates human error
- Conditional formatting turns your sheet into a visual dashboard — green rows pursue, red rows skip
- Only source products with a completed row. No exceptions.
