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title: Dynamic Pricing Strategies For ACOS Optimization
description: Trellis Knowledge Base
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# Dynamic Pricing Strategies For ACOS Optimization
## Using Price Strategy to Improve ACOS Performance
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Most advertisers try to improve performance by pulling one lever: **bid management**.
But bids are an over-pulled lever. Every competitor is adjusting CPCs. Very few are strategically optimizing **conversion rate (CR)** and **price,** two variables that directly influence advertising efficiency.
ACOS can be simplified as:
> **ACOS = CPC ÷ (CR × Price)**
This means ACOS improves when:
- Conversion Rate increases
- Price increases (without hurting CR)
- CPC decreases
Since CPC pressure is competitive and often rising, a smarter edge comes from influencing **CR and Price through dynamic pricing**.
Below are the key dynamic pricing strategies that directly support advertising performance.
### **1. ACOS Reduction Through Conversion Rate Expansion**
### Business Use Case
Advertising spend is healthy, but ACOS is too high. Bid reductions are limiting scale, and further CPC cuts reduce impression share.
### Goal
Lower ACOS by increasing conversion rate through controlled price competitiveness rather than cutting bids.
### Trellis Configuration
- **Min Price:** 3–5% below current price
- **Max Price:** Current price (or slight upside flexibility)
- **Strategy:** Boost Volume
### Success Metric
- **Primary:** ACOS reduction
- **Secondary:** Sales Above Expected
### Expected Result
The system tactically lowers price within guardrails to improve conversion rate. Higher CR lowers effective ACOS without sacrificing traffic or scaling down bids.
### **2. ACOS Improvement Through Price Expansion**
### Business Use Case
Conversion rate is stable and strong, but ACOS remains elevated due to higher CPCs.
### Goal
Improve ACOS by increasing average selling price while maintaining conversion efficiency.
### Trellis Configuration
- **Min Price:** Current price
- **Max Price:** Provide upward flexibility
- **Strategy:** Balanced
### Success Metric
- **Primary:** ACOS reduction
- **Secondary:** GCD (Gross Contribution Dollars)
### Expected Result
The system opportunistically increases price where elasticity allows. Higher price improves revenue per click, lowering ACOS without requiring bid reductions.
### **3. Balanced ACOS Optimization**
### Business Use Case
ACOS is slightly above target, and performance needs improvement without aggressive price changes.
### Goal
Allow the system to explore both marginal price increases and minor reductions to find the optimal efficiency point.
### Trellis Configuration
- **Min Price:** Slightly below current price
- **Max Price:** Slightly above current price
- **Strategy:** Balanced
### Success Metric
- **Primary:** ACOS reduction
- **Secondary:** Margin improvements
### Expected Result
The system dynamically adjusts within a narrow band, improving advertising efficiency while maintaining revenue stability.
### **Strategic Takeaway**
Advertising performance is not just a bidding problem.
Because:
> **ACOS = CPC ÷ (CR × Price)**
If competitors are only adjusting CPCs, you gain advantage by optimizing:
- Conversion rate through competitive pricing
- Revenue per click through price expansion
Dynamic pricing allows you to influence both variables in real time, turning pricing into a competitive advertising lever, not just a revenue tool.
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