Training The Google Algorithm To Optimize For Profit

Google Ads has become an indispensable platform for scaling ecommerce businesses and profit optimization. However, the traditional metric of Return on Ad Spend (ROAS) has its limitations. While ROAS measures the revenue generated per dollar spent, it does not account for all actual costs incurred, leading to misleading insights about the true profitability of your ad campaigns. This is where Profit on Ad Spend (POAS)© comes into play, offering a more nuanced approach to measuring and optimizing ad performance.

To fully grasp the benefits of POAS and how to implement it effectively, it’s crucial to understand why ROAS falls short in measuring true profitability. This article will explore the limitations of ROAS, the advantages of shifting to POAS, and best practices for optimizing your ad campaigns to maximize profit.

The Limitations of ROAS

ROAS has long been a standard metric for evaluating the effectiveness of ad campaigns. It is calculated by dividing the total revenue generated from sales by the amount spent on advertising. 

For example, an ROAS of 300% means that for every dollar spent on ads, three dollars were generated in revenue. While this metric provides a snapshot of revenue efficiency, it falls short in several key areas:

• Lack of Cost Consideration: ROAS does not account for the various costs associated with producing and delivering a product, such as the cost of goods sold (COGS), shipping fees, packaging, and other variable and fixed expenses. As a result, a high ROAS does not necessarily indicate a profitable campaign.
• Profitability Discrepancies: Two campaigns with identical ROAS can have vastly different profit margins due to varying costs. For instance, a product with a 90% profit margin and another with a 40% profit margin can both achieve a 300% ROAS, but the profitability is significantly different.

The Shift to POAS

Recognizing the limitations of ROAS, more ecommerce brands are shifting their focus to Profit on Ad Spend (POAS). Unlike ROAS, which only considers the revenue generated from ad campaigns, POAS takes into account all associated costs, such as the cost of goods sold, shipping fees, packaging, and other miscellaneous expenses. By subtracting these costs from the revenue, POAS provides a clearer picture of the actual profit generated per dollar spent on advertising. 

For example, a POAS of 100% indicates a break-even point, whereas a POAS of 120% means a 20% profit.

Why POAS Matters

• Enhanced Profitability Insight: POAS offers a clearer understanding of how much profit each ad campaign generates, enabling businesses to make more informed decisions about budget allocation and campaign optimization.
• Better Resource Allocation: By focusing on profit rather than revenue, brands can allocate their advertising budgets more effectively, prioritizing campaigns that deliver higher profit margins.
• Increased Competitive Edge: Optimizing for profit allows brands to identify and capitalize on the most lucrative customer segments and ad strategies, providing a significant advantage over competitors who rely solely on ROAS.
• Sustainable Growth: Emphasizing profit over revenue fosters a more sustainable growth strategy. Brands can experiment with different approaches and make smarter decisions, knowing that their primary focus is on profitability.

Best Practices for Improving POAS

Here are best practices to effectively transition to a profit-on-ad spend (POAS) model and optimize your campaigns for profit.

Accurate Cost Data Integration

• Ensure All COGS Are Accurate and Accounted For: Accurate cost data is the cornerstone of a successful POAS strategy. This includes the COGS, shipping fees, packaging costs, and other miscellaneous expenses. Ensure all these costs are meticulously recorded and updated regularly.
• Integrate COGS into the Product Feed: The product feed should include an attribute for “cost_of_goods_sold” where this data is stored. It’s best to enter these costs into the backend of your website, such as Shopify’s product cost field, to ensure direct integration into the feed. This approach ensures that any changes in product costs are automatically reflected in your metrics for profit calculations as well as in machine learning for smart bidding.
• Assign Responsibility for Cost Updates: Merchandising managers or individuals responsible for adding and updating product listings should also maintain accurate COGS data. As new products are added or costs change, these updates should be promptly reflected to ensure the accuracy of POAS calculations.

Comprehensive Conversion Tracking

• Set Up New Conversion Actions: Transitioning to POAS requires setting up new conversion actions that record the profit rather than just the revenue from each sale. This involves tagging your Google Ads to record the products purchased in each sale, which are then referenced against the product feed to calculate the profit.
• Use Third-Party Tools for Simplification: Third-party tools like Profit Metrics streamline this process, offering easy integrations with platforms like Shopify and WordPress and providing detailed profit data. Profit Metrics also provides a checklist and support to guide you through the integration process, making it accessible even for those not well-versed in technical setups. These tools help bridge gaps where native Google Ads functionality falls short, ensuring more reliable and accurate profit tracking.

Experimentation and Continuous Optimization

• Ad Placement Experimentation: Experiment with different ad placements to identify which positions yield the highest profitability. This involves testing various placements via campaign types such as Search, Shopping, Display, and Video. You can also allow Performance Max (PMAX) to optimize towards the best placements automatically. These methods will help determine the most effective spots for your ads.
• Audience Targeting Refinement: Refine your audience targeting to focus on segments that are more likely to generate profitable conversions. Use detailed demographic data, interests, and behaviors to tailor your ads to the most lucrative audiences. Additionally, include audiences on Observation mode to find ones that over-index on profit, then scale into them as needed.
• A/B Testing of Ad Copy: Continuously conduct A/B testing of your ad copy to determine which messages resonate best with your target audience. Effective ad copy can significantly impact conversion rates and profitability, making it a critical component of your POAS strategy.
• Keyword Refinement: Regularly review and refine your keywords to ensure they align with terms that drive profitable traffic. Analyze performance data to identify high-performing keywords and eliminate those that do not contribute to profitability.

Continuous Monitoring and Adjustment

• Monitor and Validate Data: Regularly monitor your POAS data to validate its accuracy and make necessary adjustments. Compare profit data against historical ROAS figures to ensure consistency and accuracy.
• Adjust Campaigns Based on Insights: Use insights from your POAS data to make informed adjustments to your campaigns. This includes tweaking ad copy, changing targeting parameters, and reallocating budgets to the most profitable areas.

Success requires more than just switching metrics; continuous optimization, accurate cost tracking, and strategic adjustments are essential to fully leverage the benefits of POAS. Embracing these best practices will help brands achieve sustainable growth and a stronger competitive edge.

Setting POAS Targets and Utilizing Google’s Bidding Techniques

Setting actionable Profit on Ad Spend (POAS) targets and leveraging Google’s advanced bidding techniques are essential for maximizing the benefits of this transition to POAS.

Setting Actionable POAS Targets

Establish a Baseline

Before making any changes, establish a baseline to understand how your current ROAS translates into POAS. This involves setting up new conversion actions to measure profit alongside revenue. Allow this setup to gather data over a period of time—typically around four weeks. This data collection phase is crucial for providing a clear picture of your current profit margins and setting realistic POAS targets.

Analyze Historical Data

Use historical ROAS data to estimate potential POAS targets. By analyzing past performance and costs, you can determine achievable profit margins. This analysis will guide you in setting initial POAS targets that align with your business goals.

Set POAS Targets

Based on your baseline data and historical analysis, set actionable POAS targets. These targets should represent realistic profit margins that your campaigns can achieve.

Utilizing Google’s Bidding Techniques

Maximize Conversion Value

Initially, use the Max Conversion Value bidding strategy with your new conversion action for Profit to gather valuable data quickly. This will effectively be your “Max Profit Value” bidding strategy that aims to maximize the profit value from your ad spend. By setting a daily budget, Google’s smart bidding algorithm will optimize to bring you the most profit within that budget. This approach is effective for quickly learning and understanding the profit potential within your set budget.

Target ROAS (tROAS)

Once sufficient data is gathered, switch to the Target ROAS (tROAS) bidding strategy, effectively becoming Target POAS (tPOAS). This strategy allows you to set a target profit margin for your campaigns, ensuring that your ads only spend if they can achieve the desired profitability. tROAS provides better control over your ad spend and helps maintain profitability.

Profit Optimization By Analyzing Profit On Ad Spend (POAS)

Ecommerce brands need to constantly innovate to stay ahead of the competition and relying solely on traditional metrics like ROAS can limit their ability to fully understand and optimize the profitability of their campaigns. By shifting focus to Profit on Ad Spend (POAS), brands gain a more nuanced and accurate measure of advertising efforts, allowing for smarter and more strategic decision-making.

While not without its challenges, the benefits far outweigh the initial complexities. Accurate cost data integration, comprehensive conversion tracking, and continuous optimization are crucial steps, and tools like ProfitMetrics streamline this process. They provide an infrastructure for accurately tracking and optimizing for profit that’s unmatched in 2024. 

Notably, Google recently announced that they are working on their own profit optimization bidding strategy within their Smart Bidding system, allowing brands to optimize for profit with their Performance Max and Standard Shopping campaigns using data from cart-level conversions and costs of goods sold in the Merchant center. Google’s AI will prioritize ad placements and bids that drive higher profitability for your business. 

Google’s profit optimization goal is currently in the pilot phase, and it does not yet include tPOAS and likely won’t support other platforms like Meta Ads. 

So, while Google is catching up by releasing its own profit optimization goal, ProfitMetrics offers a more advanced and comprehensive solution for profit bidding and POAS, integrating with multiple platforms, including Meta Ads. This makes it a highly recommended tool for brands looking to implement profit optimization immediately.

But recognize that to truly leverage the power of POAS, continuous refinement of your campaigns is essential. This includes experimenting with ad placements, refining audience targeting, conducting A/B tests on ad copy, and regularly reviewing and adjusting your keywords. Utilizing advanced Google bidding techniques like Max Conversion Value and Target ROAS to optimize for profit can further enhance your ability to meet and exceed your profit targets.

Adopting a profit-focused strategy is just the tip of the iceberg. By continuously optimizing your campaigns and leveraging the detailed insights provided by POAS, you can drive sustainable growth, allocate your resources more effectively, and maintain a competitive edge in the marketplace.

About the Author: Shawn Assad is the Strategy Lead, Search, Shopping, Display, and Video at adQuadrant. He is a former US Marine who earned his B.A in Psychology from California State University, Northridge followed by an M.B.A. from Pepperdine University. Shawn has been working in digital marketing for 9 years with a passion for data and cats.