Finance at the helm of Demand-Led Growth

The shift to AI-led campaigns

Predictable, profitable and sustained growth is the cornerstone of every retailer's strategy, and every function in the business will be aligned to this strategy. But this can sometimes get lost in the weeds of department-level metrics, KPI’s and OKR’s where the language of one team does not translate into the language of another.

This challenge is at the centre of the all too often misalignment between marketing and finance, where activity-based KPI’s, fragmented toolkits, discrepancy between short and long-term goals, data that’s difficult to access and even harder to interpret clash with the numeric clarity of the finance team.

What is needed is a shared lexicon of key metrics that directly align and support business goals. AI is a key component here and is transforming the approach that finance and marketing teams are now taking to jointly collaborate.

Since its launch in 2021, Google’s Performance Max (PMax) has moved from being a new campaign type to becoming the centrepiece of Google’s AI-led advertising strategy for retail. 

The same pattern is visible across the industry: Meta with Advantage+, Amazon with AI-driven Sponsored Ads, and TikTok with Smart Performance campaigns. So the movement is clear - manual campaign formats are being retired to a large degree, and automation is becoming the default.

What has changed in the last few years is that AI-led media has matured. It now sits at the heart of most large retailers’ media plans, carrying the majority of the budget, and as more data has flowed through these powerful campaigns, PMax has become more consistent in how it allocates spend and interprets demand signals, reflecting Google’s emphasis on ongoing AI/machine learning improvements.

For Finance, this matters because these campaigns are now where the majority of retail demand is harvested and captured. They are designed to ebb and flow with the market, but only if budgets are not capped. Their learning loops also mean that today’s decisions affect tomorrow’s efficiency, and the impact in some cases can be seen weeks afterwards, which is why manual overrides or short-term day trading behaviours risk teaching the model the wrong lessons and missing out on the total opportunity.

Google is becoming increasingly more important as the way retailers scale growth, bring customers into their online brand experience, win share of consideration, acquire new customers, and grow share of wallet. To add to this, within PMax’s shopping carousel, it has become the battleground of range strength, where breadth, depth, price, delivery, and quality are pitted directly against the competition millions of times a day.

What Finance needs to know about

For Finance, PMax can feel like a black box. But at its core, it works in three ways: 

1. It aggregates intent signals from across Google properties, such as YouTube, Shopping, Display, Gmail and Maps, to spot where demand is forming in real time and where it can test and reach new audiences
2. It dynamically allocates budgets across surfaces and audiences based on where the next incremental sale is most likely
3. It learns at the level of business goals, not individual SKUs

It's important to note that part of the approach in areas of fixed budgets or “day-trading” behaviours (those whereby teams are frequently tweaking and overriding a steady state), prevents the campaigns from scaling when demand spikes, leaving stock sitting longer and cash tied up. 

When run with well-considered contribution or ROI thresholds, PMax can actually flex budgets safely, protecting margin and still capturing growth. And because it is always processing demand signals, it provides a richer set of data to work with for the next day, week, month, etc.

There are, however, important limits. Out of the box and without proper analysis, PMax does not provide SKU-level clarity, so it's not straightforward to see which products are driving performance, or not being prompted enough to drive meaningful engagement, and even with that analysis, it can’t always be acted upon.

It learns in aggregate, meaning short-term changes to targets (over certain thresholds) or budgets often cause issues by derailing the AI. It is not inventory-aware by default, unless structured trading and product signals are integrated into the retailers’ media approach.

Finally, PMax is based on reinforcement learning, a technique where the AI learns to make decisions by trial and error, receiving feedback from the data it ingests. This is like a form of ‘pass or fail’ used to maximise the overall cumulative impact over time.

How should demand-led growth be measured?

For Finance to lead the marketing teams in demand-led growth, the metrics must move beyond marketing’s language. Impressions, CTR, and even ROAS, as they don’t capture what matters to the business. Media investment at this part of the funnel should be measured in terms of gross profit contribution, so it ties directly to P&L impact. Incrementality should be proven, using methods such as geo holdouts or matched market tests, to separate true uplift from sales that would have happened anyway.

Finance should also pay attention to elasticity ratios, showing how much additional revenue and profit each incremental pound of media delivers, and at what point diminishing returns set in. And critically, demand-led growth needs to be linked to working capital. Faster sell-through reduces stock days and frees cash sooner.

As we outlined in our Performance Measurement Framework for Demand-Led Growth, retailers can track these measures across daily, weekly, monthly, and quarterly cycles. For Finance, this cadence matters as it makes returns measurable, auditable, and comparable to existing financial controls.

When Finance defines these measures, demand-led growth becomes accountable in their terms.

How profitability is delivered

Demand-led growth is not a blank cheque. It is about scaling into demand only when profitability is protected. Finance must set and enforce the rules:

• Profit floors and cost-of-demand thresholds: Budgets flex only when margins are above the minimum contribution Finance defines.
• Dynamic scaling: AI systems like PMax capture demand spikes, payday weekends, TV exposure, promotions, but only within profitability guardrails.
• SKU and category orchestration: Profitability isn’t just about more revenue; it’s about moving the right stock at the right time to avoid margin erosion from excess discounting or high holding costs.
• Governance rhythm: Shared dashboards, decision logs, and review cycles make profitability visible and auditable — so Finance stays in control while allowing Marketing the agility to act.

In practice, this means Finance isn’t simply approving marketing rules. They are monitoring them continuously within a governance framework with the marketing team. The Performance Measurement Framework for Demand-Led Growth shows how those reviews should sit across daily, weekly, monthly, and quarterly cadences, ensuring that profitability isn’t just protected but actively managed over time.

The Finance playbook for Demand-Led Growth

• Define the guardrails: Contribution margins, cost-of-demand thresholds, elasticity ratios. Ensure growth flexes only within safe limits.
• Model demand variance, not just averages: Forecast what happens when demand surges, and compare missed opportunities under fixed budgets with the cash unlocked under flexible ones.
• Translate media into P&L terms: Contribution versus ROAS, working capital unlocked versus impressions, stock days versus CTR.
• Operationalise governance: Create joint dashboards, decision logs, and regular review cycles so Finance becomes a co-pilot, not just an approver.
• Use technology as the neutral enforcer: Ensure budgets flex only when agreed thresholds are met.

Where Upp.ai fits in

Google’s PMax provides a way to capture demand, but without orchestration, it leaves Finance blind to product-level impact. Upp.ai extends PMax by structuring and enriching data and optimising at the SKU level, so Finance can see which categories are profitable, where budgets can flex, and how that affects contribution and working capital.

For Finance, that means assurance. For Marketing, it means freedom to capture every profitable opportunity of demand.