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TikTok Shop ROAS Calculator

Compare your campaign ROAS with the ROAS you actually need on TikTok Shop. The referral fee for your category and any affiliate commission are deducted automatically.

By Content reviewed

Campaign data (from TikTok Ads Manager)

$
$

TikTok Shop fees and costs

Product category (referral fee)

$
$
%

Use 0% if the ad orders did not come through a creator.

Is this campaign profitable?

Actual ROAS3.50×
Break-even ROAS (after TikTok fees)2.20×
Campaign profit after ads$118.00
Cost per order (CPA)$10.00
Max CPA before losing money$15.90

Where the revenue goes

Referral fee (6%)-$42.00
Affiliate commission-$0.00
Product + shipping-$340.00
Contribution before ads$318.00
Ad spend-$200.00

Worked example: break-even ROAS

A $30 product earns $14.20 after fees, cost and postage. Break-even ROAS is price ÷ contribution = 2.11.

ROAS 1.50ROAS 2.11ROAS 3.00
Ad cost per order−$20−$14.20−$10
Profit per order$-5.80$0.00$4.20

A campaign below ROAS 2.11 loses money on every order, however good the sales volume looks.

Cost inputs are illustrative; fees are calculated with the same rates as the calculator above.

TikTok Ads ROAS formula

ROAS: Ad revenue ÷ Ad spend
Gross profit (after platform fees): Revenue × (1 − confirmed referral rate) − Product cost − Other per-order costs
Gross margin: Gross profit ÷ Revenue
Break-even ROAS: 1 ÷ Gross margin

Assumptions

  • US reference rates range from 5%–6%; no separate payment-processing rate is modeled
  • Referral fee is applied per order at the average order value; affiliate commission is applied to attributed revenue
  • Break-even ROAS assumes a single-purchase customer — repeat purchases lower the effective break-even over time

Source: seller-us.tiktok.com/university/essay · Last verified: 2026-10-11

Review the market, fee bases and exclusions shown with this tool. Published rates and illustrative cost inputs have different certainty. Compare your breakdown with an actual order statement. Sources and methodology.

Frequently Asked Questions

What is ROAS and how is it calculated for TikTok Ads?
ROAS (Return on Ad Spend) = Ad revenue ÷ Ad spend. If a $200 TikTok Ads campaign generates $700 in TikTok Shop sales, ROAS = $700 / $200 = 3.5×. Unlike raw revenue, ROAS tells you efficiency — a 3.5× ROAS means every $1 spent on ads returned $3.50 in sales, before accounting for product cost or platform fees.
What ROAS do I need to break even on TikTok Shop ads?
Break-even ROAS = 1 ÷ gross margin after platform fees. Using this calculator's 6% referral assumption and a $30 sale with $14 product cost: gross profit = $30 × 0.94 − $14 = $14.20, gross margin = 47%, and break-even ROAS = 2.11×. Replace the assumption with your confirmed Seller Center rate.
What is a good ROAS for TikTok Shop campaigns?
Calculate the contribution available before advertising from your actual settlement, product, fulfillment and creator costs. A profitable ROAS must exceed your own break-even requirement, with room for overhead and the desired profit. This page does not provide category or campaign benchmarks.
Does TikTok Shop's referral fee change my break-even ROAS?
Yes — the referral rate comes out of revenue before you calculate margin, so it raises break-even ROAS. A 5%–6% reference rate changes the result differently from the 6% example shown here. Use the category and account rate confirmed in Seller Center.
What's a common mistake when calculating TikTok Ads ROAS?
Using revenue-only ROAS as a profitability signal. A campaign can show 4× ROAS and still lose money if product cost and platform fees eat more than 75% of revenue. Always calculate your break-even ROAS first (from margin), then judge campaign ROAS against that number — not against an industry-wide "good ROAS" figure.
How does TikTok Ads ROAS compare to Shopify or Facebook Ads ROAS?
The ROAS formula itself is identical across platforms, but break-even ROAS differs with referral rate, product margin, affiliate cost, and acquisition cost. Compare using your confirmed TikTok Shop rate and the actual Shopify plan and payment assumptions instead of a universal platform ranking.