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Advanced Amazon PPC: The Math-Driven Way to Optimize Single Keyword Campaigns Using Placement Modifiers
Written by Brett @ FBAExcel on Jul. 7th 2025
Amazon PPC ads are one of the most powerful ways to grow your brand, but getting the most out of them requires more than just adjusting bids and launching new campaigns.
The majority of new sellers simply focus on trying to optimize the base bids on their campaigns, but putting some intentional focus on placement modifiers can really throw gas on the fire if done right.
If you've ever struggled with optimizing your Amazon pay-per-click advertising to reduce wasted spend while improving ACOS, and specifically trying to figure out what placement percentage to set... this strategy is for you.
In this post, we’ll walk through the core concept of using Revenue per click and Target ACOS in single keyword campaigns to optimize campaign performance. We'll use a simplified example, then show how we apply it at scale across your entire Amazon PPC account with just a few clicks.
🎯 The Power of Placement Modifiers in Amazon PPC
Amazon doesn’t allow negative modifiers for weak placements, which means you need to be intentional with your base bid. If you set your base bid too high, you'll end up overpaying on less profitable placements like Product Pages in the majority of cases. If you set it too low, you risk losing impressions altogether.
The strategy outlined below flips this problem into an advantage.
The main concept is we set a lower base bid to start working to suppress poor placements and use positive placement modifiers to bring high-performing placements back up to their deserved level. This allows for more effective PPC optimization without increasing your Amazon PPC cost unnecessarily.
Step 1: Determine the Base Bid
*Special Note: the strategy outlined in this post works well for single keyword campaigns since placement modifiers are set at the campaign level. If you are only targeting 1 keyword you can ensure all placement data is based on that target. Multi keyword campaigns are more complex and will be discussed in a future blog post. In addition dynamic up and down bid strategy is not advised.
Let’s go through a quick example for a campaign that's never optimized for placements. The example below is for a single keyword campaign with a base bid of 2.50 and dynamic down only bidding strategy.
You have a few options when figuring the optimal base bid. Most of the time Top of Search will be the most expensive CPC which is the case in the sample data below (cpc = 2.47).
1️⃣ If one placement (like Top of Search) is clearly outperforming the others across CVR, CTR, ACOS, and Orders, in our experience it's wise to hedge your strategy toward that placement by using its CPC as the reference point when calculating your base bid. This ensures the strongest performer gets traffic, while weaker placements will start getting suppressed.
2️⃣ On the other hand, if multiple placements are performing well, you can optimize more broadly by setting your base bid based on the lowest CPC among the well-performing placements. This allows you to drive performance across multiple sources efficiently, while still controlling costs.
For the campaign above, although all placements have orders, Top of Search is clearly performing the best across critical PPC performance metrics like CTR, CVR, Orders, and ACOS. In this case we should hedge most of our spend towards this placement to scale the campaign faster.
To adjust the base bid apply a “nudge factor” to slightly reduce the bid below the Top of Search CPC. A good general factor is 10% based on our experience.
For this example the calculation is 2.47 x .9 = 2.22.
2.22 will become the new base bid of the keyword in this single keyword campaign, a reduction of .28 from the current bid of 2.5
Step 2: Calculate Placement Modifiers Using RPC
The next optimization step is figuring out the Revenue Per Click (RPC) for each placement.
RPC tells you how much money each click is generating, on average. It’s a quick way to measure how valuable traffic is from each placement.
For example, if Top of Search has an RPC of $20 and Product Page has an RPC of $2, that means clicks from Top of Search are 10x more valuable — so you'd want to spend more there. RPC helps you decide where to apply your budget for the biggest return.
To calculate the RPC column just divide the Revenue/ Clicks as shown below:
Step 3: Final Adjustments
Now that we’ve set our base bid and calculated RPC for each placement, we can compute the final modifiers. The formula we use is:
Modifier = (((RPC × Target ACOS) ÷ Base Bid) - 1) x 100
This tells us how much we can increase the bid for each placement while staying within our ACOS target. A higher RPC means that placement is generating more revenue per click — and therefore can afford a higher bid.
Negative modifiers are ignored since Amazon doesn’t support them; instead, poor placements are automatically throttled by the low base bid. For this example here are the inputs with an example calculation:
> New Base Bid from step 1: $2.22
> Target ACOS: 35%
> Modifier: ((RPC × Target ACOS) ÷ Base Bid) - 1 ->> ((RPC × 0.35) ÷ 2.22) - 1
These final modifiers help you direct spend toward the placements that actually perform.
Top of Search and Amazon Business are showing strong efficiency, so we’re applying aggressive boosts to maximize volume from those high-converting clicks.
Rest of Search and Product Page, on the other hand, are underperforming against your ACOS target — so we’re letting the low base bid throttle them naturally.
This structure keeps your campaign efficient, scalable, and aligned with ROI, even as performance shifts over time.
📊 Scaling This Strategy Across Thousands of Campaigns
While this example shows how to effectively optimize one single keyword campaign, it can be a time-consuming challenge to implement this strategy at scale.
That’s exactly why we built Adtactix — our Amazon PPC bulk operations tool that can apply this placement-based strategy across thousands of keywords and campaigns in minutes. With the Scale plan, you can access our newest placement optimization algorithms, pull performance data in seconds, and automate base bid + modifier updates using your real RPC and ACOS targets.
Want to see it in action?
📺 Check out our latest YouTube demo walking through how we apply this method across real Amazon campaigns using Adtactix. It also covers our new "Placement Optimization Score" feature - super helpful in quickly determining which campaigns have the most potential for placement optimization.
🚀 Need 1-on-1 Help?
If you want expert help implementing this system — without giving up control of your ad account — book a call with us to learn about the Scale Assisted Plan.
With our Scale Assisted plan, our team well versed on all things FBAExcel will become an extension of yours.
We help you:
✅ Set up and maintain your FBAExcel PPC tools
✅ Run weekly/monthly SOPs that can be tedious to maintain consistently
✅ Ensure your team stays focused on the top tasks to drive your business forward
✅ Access unlimited support via our private Discord
You stay in control of Seller Central. We handle the heavy lifting in the background.
👉 Book a call with Brett and we’ll walk you through how Scale Assisted can help you master your PPC and streamline your FBAExcel setup.
💭 Final Thoughts
Mastering Amazon PPC optimization requires more than just adjusting bids — it takes a strategic, math-driven approach that aligns your spend with true performance data.
By leveraging Revenue Per Click (RPC) and placement modifiers, you can take control of your campaigns, reduce wasted spend, and scale more profitably. Whether you're running one campaign or thousands, the principles in this post give you the foundation to make smarter, more effective advertising decisions.
And if you’re ready to take it further, our tools and team at FBAExcel are here to help — whether you want to automate the process with Adtactix or get hands-on support through our Scale Assisted Plan. Let’s optimize smarter, not harder.
About the Author: Brett @ FBAExcel
I spent 10+ years climbing the corporate ladder as an engineer before learning I wanted to be an entrepreneur when I grow up. Now I focus my time on growing Amazon brands, helping other sellers at FBAExcel.io and building SaaS tools. If you are an Amazon junky drop your email below and follow the journey.
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