ROAS Calculator
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What is Return on Ad Spend (ROAS)?
Return on Ad Spend is a metric of paid ads performance. ROAS tells you how much revenue you get from each dollar spent on advertisements.
Over the years, ROAS gained widespread usage in marketing worldwide, and it's a de facto standard for all marketing platforms. So understanding this metric is mandatory for everyone who thinks about growing his business.
ROAS may be presented in different forms. Usually, it is expressed as a percentage value, but sometimes it is shown in dollars or as a ratio (i.e., in Google Ads).
How to calculate ROAS?
The calculation of ROAS is straightforward. Just follow the steps below.
- Gather all required information on Ad revenue and Ad spending.
- Input those data to the form above or substitute the ROAS equation below.
ROAS formula
The ROAS formula is a simple ratio of the revenue from the ads to its cost.
ROAS = (Ad Revenue / Ad Spend) * 100%
Where:
- Ad Revenue - the total revenue from an ad campaign
- Ad Spend - the total cost of this particular campaign
What is a good ROAS?
Good ROAS is a value that provides revenue high enough, so gross margin can cover all the costs related to the transaction.
So the margin generated by ad campaigns should cover ad spending, extra commissions, shipping, storage, logistics, etc. It should guarantee you achieve net profit.
The exact value of ROAS depends on the gross margin you have on the products and the cost structure of the company.
Most eCommerce businesses consider ROAS in the range of 500% to 1000% a good result.
Of course, there are types of businesses that could accept lower ROAS. For example, if you sell virtual products and your gross margin is close to 100%, or you have a very high customer lifetime value, it could be sufficient if your ROAS is just above 100%.
It is essential to understand that ROAS below 100% means definitive loss. Regardless of how efficient your business is and how high the margin you have, with ROAS below 100%, your ads cost much more than they make.
How to calculate break-even ROAS?
Break Even ROAS is a ratio of ad revenue to ad spend where generated margin covers all the costs related to the transaction.
In order to find this value, you should.
- Write down all the costs required to fulfill the translation without considering marketing costs. The value should cover the costs of products sold (COGS), logistics, financing costs, workload, etc. The values should be presented as a percentage of the average transaction value.
- Sum those values to find your average operating costs per transaction. For example 60% COGS + 5% logistics + 6% workforce = 71%
- Calculate the average profit per transaction before ad spend. In this case 100%-71% = 29%
- Now your break-even ROAS could be calculated using this formula:
ROAS < 1 / avg_tx_profit * 100%
In our case ROAS could not exceed: 1 / 29% * 100% = 345%
How to improve ROAS?
Although the ROAS formula is straightforward, this metric's actual value depends on various factors. To name just a few
- The brand
- Competition
- Marketing channel
- Quality of product description and images
- The price of the product
- Technical optimization of the ad campaign
In order to improve ROAS, you should address each of those factors and optimize them one by one.
Remember that some marketing platforms with advanced machine learning (Google Ads, Facebook) need some time to optimize your ad efficiency. So if you are just starting, wait a few weeks and gather some data before you begin to tune up the campaigns.
Other useful tools
If you find this helpful tool, you may also like other calculators available on Calcopolis. If you plan to optimize your business using profitability metrics, visit the category with calculators for investors.
You may find our ROI calculator and EBIT calculator particularly useful.
If you wish to grow your business, you may look at our calculators for business owners, for example, the margin of safety of the discount calculator. A good discount policy may positively impact the ROAS.
Authors
Created by Lucas Krysiak on 2022-07-14 16:50:01 | Last review by Mike Kozminsky on 2022-09-15 14:08:52