How to optimise towards profit in your paid media
- Jack Carr
- Reading time: 5 minutes
TLDR: The steps towards fully optimising your paid media based on profitability: 1) share your marketing P&L with your agency / marketing team, 2) segment your product feed into groups tiered by margin, 3) integrate tag data and platform rules to start predicting profit, 3.5) if it’s a challenge to do this yourself, use a third-party platform instead.
Optimising for profitability sounds like the obvious goal for any business. However, most still use attributed revenue or ROAS as their main forms of success measurement. While this may look great on a spreadsheet, it doesn’t always pay the bills. To move beyond surface level growth, optimising for profitability becomes key.
This requires an organisation to go on a journey. What we’re ultimately asking for is an understanding of business cost dynamics broken down to an individual SKU level. Does one item cost more to make because it is US manufactured? Or does one cost more as it involves sourcing an important material. It’s rare to be capable of jumping straight to this endpoint.
By breaking it down we move our customers through these stages: from inactive, to responding reactively to predicted profit data, and finally to proactively leading profit optimisation, creating real and tangible profit-led growth.
The first step on this journey is one that every business should be doing: creating a Marketing Focused P&L and sharing this with your marketing agency. This provides aggregated lines that allow for better transparency on how marketing spend impacts the bottom line.
Despite being the first step, we understand that getting down to the truth of your numbers can be incredibly challenging. Specifically, when you try to move from broad categories to SKU-level insights, you run into three main hurdles:
Granular Cost Allocation: It is rarely as simple as looking at the unit cost. You have to account for hidden variables that fluctuate, which can make a high-margin product look much less attractive once you dig in.
Dynamic Discounting: Site-wide promotions and complex bundles often erode margins in ways that aren’t immediately obvious. Tracking how these discounts interact with the rising cost of marketing for individual products is essential for accuracy.
Data Fragmentation: Manufacturing costs, shipping fees and ad spend often live in completely different systems. This silo effect makes it difficult to maintain a unified, real-time view of what you are actually making on a sale.
To make it a bit easier for you, if a Marketing P&L isn’t something you’re using yet, we’ve put a simple template together that you can access here. This will start to align how your marketing team or agency thinks, with what is actually important to your growth.
Outcome -> give your teams better transparency over how marketing costs impact profit for your business.
Before diving into the technical setup, it is worth asking if this additional layer of complexity actually serves you. If your margins are identical across every product, country and supplier, you probably don’t need a profit-focused restructure. Segmenting your marketing by margin in that scenario just adds an extra chunk of admin that won’t drive results.
Likewise, if your strategy relies heavily on loss leaders (products you intentionally sell at a loss to acquire customers), trying to optimise for immediate profit might actually choke your growth.
If you have varying margins, the next natural step is simple segmentation. We often start by splitting products into different campaigns based on their profitability. This allows us to set more aggressive targets for high-margin items while pulling back on the lower-margin ones.
For instance, in Google Ads, by analysing your product mix and margin variation, and adding rules into your feed to align with where profit sits, we can segment products into buckets and optimise product groups automatically.
Outcome -> we’re putting more money behind the products that actually move the bottom line.
In this next stage we build on top of those feed processes by introducing tag variables that are set up to push margin data back into the ad platforms. This helps us estimate profit margins for each transaction, which we can then build rules around in the ad platforms to optimise campaigns. Whilst still relatively basic, this is a massive leap forward in understanding and acting on what is bringing you profit.
We apply a similar logic with some of our clients for assigning estimated revenue and profit values to offline interactions like demos or surveys. This ensures the marketing budget is working toward the most valuable leads, not just the most frequent ones.
Outcome -> you’re now proactively optimising towards POAS across all of your paid media – congratulations!
Once the optimisation journey is well on its way, we look at deeper integration (this often, but not always, involves using 3rd party providers). Ultimately, the central benefit of this tech, alongside not having to do it yourself, is that these tools provide a dynamic feedback loop directly to the ad platforms, shifting the process from static to dynamic.
A noteworthy suggestion is to consider tech like Shoplytics to handle this for you. They’re a cost effective option, particularly if you don’t have the capability to implement this internally.
Platforms like ProfitMetrics also break down profit data to the same level as conventional tracking, allowing us to fully optimise down to search term/keyword or product level, and across social platforms too.
That data is then passed directly back to the ad platforms as a conversion goal, allowing the algorithm to proactively hunt for profit.
Finally, when it comes to visibility on performance, for some of our customers we use Contribution Margin as the primary measurement of success. This accounts for costs that go far beyond paid media, which is all built into our reporting dashboards to give live pictures of profit performance.
Outcome -> you’re now proactively optimising towards POAS across all of your paid media – now with maximum granularity!
There is a dynamic shift in thinking when the goals are aligned through profit share models or margin rewards. You stop worrying about whether the ROAS is high enough and start focusing on how much real growth you can see in the business. It is a journey with incremental layers but it ensures you stop being inactive or merely reactive, becoming instead proactive in your pursuit of profitability.
Background
Optimising for profitability sounds like the obvious goal for any business. However, most still use attributed revenue or ROAS as their main forms of success measurement. While this may look great on a spreadsheet, it doesn’t always pay the bills. To move beyond surface level growth, optimising for profitability becomes key.
This requires an organisation to go on a journey. What we’re ultimately asking for is an understanding of business cost dynamics broken down to an individual SKU level. Does one item cost more to make because it is US manufactured? Or does one cost more as it involves sourcing an important material. It’s rare to be capable of jumping straight to this endpoint.
By breaking it down we move our customers through these stages: from inactive, to responding reactively to predicted profit data, and finally to proactively leading profit optimisation, creating real and tangible profit-led growth.
Stage 1: The Marketing P&L
The first step on this journey is one that every business should be doing: creating a Marketing Focused P&L and sharing this with your marketing agency. This provides aggregated lines that allow for better transparency on how marketing spend impacts the bottom line.
Despite being the first step, we understand that getting down to the truth of your numbers can be incredibly challenging. Specifically, when you try to move from broad categories to SKU-level insights, you run into three main hurdles:
Granular Cost Allocation: It is rarely as simple as looking at the unit cost. You have to account for hidden variables that fluctuate, which can make a high-margin product look much less attractive once you dig in.
Dynamic Discounting: Site-wide promotions and complex bundles often erode margins in ways that aren’t immediately obvious. Tracking how these discounts interact with the rising cost of marketing for individual products is essential for accuracy.
Data Fragmentation: Manufacturing costs, shipping fees and ad spend often live in completely different systems. This silo effect makes it difficult to maintain a unified, real-time view of what you are actually making on a sale.
To make it a bit easier for you, if a Marketing P&L isn’t something you’re using yet, we’ve put a simple template together that you can access here. This will start to align how your marketing team or agency thinks, with what is actually important to your growth.
Outcome -> give your teams better transparency over how marketing costs impact profit for your business.
When you shouldn’t bother
Before diving into the technical setup, it is worth asking if this additional layer of complexity actually serves you. If your margins are identical across every product, country and supplier, you probably don’t need a profit-focused restructure. Segmenting your marketing by margin in that scenario just adds an extra chunk of admin that won’t drive results.
Likewise, if your strategy relies heavily on loss leaders (products you intentionally sell at a loss to acquire customers), trying to optimise for immediate profit might actually choke your growth.
Stage 2: Feed based optimisation
If you have varying margins, the next natural step is simple segmentation. We often start by splitting products into different campaigns based on their profitability. This allows us to set more aggressive targets for high-margin items while pulling back on the lower-margin ones.
For instance, in Google Ads, by analysing your product mix and margin variation, and adding rules into your feed to align with where profit sits, we can segment products into buckets and optimise product groups automatically.
Outcome -> we’re putting more money behind the products that actually move the bottom line.
Step 3: Recording transaction margins
In this next stage we build on top of those feed processes by introducing tag variables that are set up to push margin data back into the ad platforms. This helps us estimate profit margins for each transaction, which we can then build rules around in the ad platforms to optimise campaigns. Whilst still relatively basic, this is a massive leap forward in understanding and acting on what is bringing you profit.
We apply a similar logic with some of our clients for assigning estimated revenue and profit values to offline interactions like demos or surveys. This ensures the marketing budget is working toward the most valuable leads, not just the most frequent ones.
Outcome -> you’re now proactively optimising towards POAS across all of your paid media – congratulations!
Step 3.5: Integrating profit data down to a product and keyword level
Once the optimisation journey is well on its way, we look at deeper integration (this often, but not always, involves using 3rd party providers). Ultimately, the central benefit of this tech, alongside not having to do it yourself, is that these tools provide a dynamic feedback loop directly to the ad platforms, shifting the process from static to dynamic.
A noteworthy suggestion is to consider tech like Shoplytics to handle this for you. They’re a cost effective option, particularly if you don’t have the capability to implement this internally.
Platforms like ProfitMetrics also break down profit data to the same level as conventional tracking, allowing us to fully optimise down to search term/keyword or product level, and across social platforms too.
That data is then passed directly back to the ad platforms as a conversion goal, allowing the algorithm to proactively hunt for profit.
Finally, when it comes to visibility on performance, for some of our customers we use Contribution Margin as the primary measurement of success. This accounts for costs that go far beyond paid media, which is all built into our reporting dashboards to give live pictures of profit performance.
Outcome -> you’re now proactively optimising towards POAS across all of your paid media – now with maximum granularity!
Key Takeaway
There is a dynamic shift in thinking when the goals are aligned through profit share models or margin rewards. You stop worrying about whether the ROAS is high enough and start focusing on how much real growth you can see in the business. It is a journey with incremental layers but it ensures you stop being inactive or merely reactive, becoming instead proactive in your pursuit of profitability.
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