Performance Measurement Framework for Demand-Led Growth

Without the right measurement framework, Demand-Led Growth won’t last. If you can’t prove the incremental, profitable value of flexibility, someone in finance, trading, or leadership will eventually, and quite correctly, stop this approach.

This framework outlines the essential monitoring, optimisation and activity cadence for demand-led growth, ensuring campaigns remain responsive to demand shifts, aligned with strategic goals and free from technical constraints.

Daily focus - Ensure nothing is blocking PMax: budgets, conversion tracking, data feeds, assets, compliance, system connections. Failures and blocks here inhibit PMax from responding to demand.

Weekly focus - Check demand signals against spend, and attribution levels to their cycle in-platform. This allows you to confirm if budgets are effectively adapting profitably and are in sync with demand.

Monthly focus - Test for incrementality. Use Geo splits, holdouts and causal impact to assess if extra budget unlocked access to incremental demand, not reattribution.

Quarterly focus - Align with wider business priorities. Use contribution margin, LTV, CPA and MMM to tie budget flexibility back to Finance and C-Suite priorities.

Frequency	Focus	What to do (Detail below)	Purpose	Tools / Sources
Daily	Performance guardrails & hygiene metrics	Check budgets & delivery Confirm tracking and data feeds Verify creatives and assets Check system connectivity Review policy and compliance alerts	Ensure the AI system remains unconstrained, allowing it to capture all profitable demand.	Google Ads change history Auction insights Conversion diagnostics GA4 CRM feed logs Merchant Center Asset library API monitoring tools
Weekly	Demand response & ROI	Measure ROI & elasticity Check attribution alignment Track market signals Review category health	Confirm budgets are flexing effectively and profitably in sync with demand	Looker Studio Google Trends SA360 Auction insights BI dashboards MTA tools
Monthly	Incrementality proof & test planning	Run experimentation tests Apply insights from causal impact tests Refresh MMM data Audit attribution models Design future tests	Validate incremental value and refresh models for accuracy	Google Ads Experiments Geo frameworks (Google Meridian, Measured, Recast) R/Python MMM pipelines
Quarterly	Strategic commercial impact	Execute Geo Hold-outs Calibrate MMM data Gather key metrics Gain executive alignment	Prove commercial impact and align paid media with enterprise profit and growth priorities	MMM tools (e.g., Recast, Google Meridian) CRM & Finance BI dashboards Geo test results, MTA diagnostics

Daily metrics and signals
What do to / measure	Detail
Check budgets & delivery	Check if any campaigns hit budget caps early (“Limited by budget”), unexpected pauses, or bid strategies stuck in “learning” after large changes.
Confirm tracking and data feeds	Confirm all conversion tags firing, offline conversions uploaded successfully, enhanced conversion match rates stable, and Merchant Center/product feeds fresh with no major disapprovals.
Verify creatives and assets	Ensure no asset disapprovals, pending reviews, or missing creative formats in asset groups (esp. PMax/Demand Gen). Remove expired promotions.
Check system connectivity	Verify CRM, analytics, and API integrations are error‑free, audience lists refreshing as scheduled, and third‑party trackers in sync.
Review policy and compliance alerts	Check for new ad disapprovals, Merchant Center policy violations, or geo‑restrictions.
Major external triggers	Be aware only of significant, confirmed demand events (>200% spike or major PR/news impact) for later review.

Weekly metrics and signals
What to do / measure		Detail
Measure ROI		Measure of the extra return generated from the last increment of spend, i.e. change in revenue ÷ change in spend. Helps identify diminishing returns and optimal scaling points. ROI Comparisons: Track efficiency differences between promoted products and baseline SKUs to confirm promotional investment is incremental, not cannibalising.
Measure budget elasticity		∆ conversions / ∆ spend Measure the absolute marginal return: how many extra conversions are generated for each additional unit of spend. Useful for seeing the raw incremental efficiency of extra budget. The budget elasticity ratio: % ∆ conversions / % ∆ spend Measures the relative responsiveness of conversions to spend changes. A ratio >1 indicates conversions are growing proportionally faster than spend (scaling efficiently), while <1 shows diminishing returns. Ratio by category: Sensitivity of conversions to budget changes at product line/category level, showing where incremental spend is most effective.
Check attribution alignment		Compare platform ROAS vs business margin by checking MTA dirft and aligning attribution windows.
Track market signals	Impression share	% of total eligible impressions captured. Helps identify if volume constraints are due to competition, rank, or budget.
	Auction insights	Identify how your ads perform compared to competitors who appear in the same auctions.
	Search volume trend vs spend	Compare shifts in category/product search demand with corresponding media spend trends. Confirms budgets are aligned with market demand.
Review category health		Check SKU / Category trends to see if they are gaining or losing visibility, impressions, clicks or conversions.

Monthly metrics and signals
What to do / measure		Detail
Run experimentation tests (every 4-6 weeks)	Geo lift	Experimenting giving some regions extra spend and comparing results to show whether added media spend truly drives incremental conversions or just follows existing demand.
	Geo holdout	Deliberately withholding spend in certain regions while continuing it elsewhere to reveal the baseline level of demand and whether media spend is genuinely additive or cannibalising organic demand.
	Casual Impact	A statistical model (often Bayesian time series) that estimates what would have happened without the campaign. Used when experiments like Geo lift and Geo hold out aren’t possible and helps confirm if spend created real incremental lift.
Apply insights from causal impact tests		Break ROI down by dimension such as geography, product category, or audience to highlight which segments deliver the most incremental value and where budgets should flex for maximum impact.
Refresh MMM data		Refresh seasonality data, promotions data and competitor pricing.
Audit attribution models		Check: Tagging - are all conversion points firing correctly? Attribution windows - are lookback periods aligned with customer journey length? Assisted conversions - are upper- and mid-funnel touchpoints valued alongside last-click?
Future planning		Design experimentation tests (Geo lift / Geo hold-out / Causal impact) for the upcoming quarter with SMART objectives.

Quarterly metrics and signals
What to do / measure		Detail
Execute a Geo holdout test		Execute 1 x test every 4-6 weeks with refreshed geographies for causal validation.
Calibrate MMM data		Re-estimate MMM with geographical calibration and structural updates.
Gather key metrics And build a ‘one truth’ report	Incremental profit impact	Measure of actual contribution to gross profit or operating profit from paid media investment.
	LTV/CPA trends	Track the relationship between long-term customer value (LTV) and acquisition cost (CPA) over time to validate sustainable growth.
	SKU/Customer impact	The influence of individual SKUs on customer acquisition, retention and lifetime value. Identify; Which SKUs attract new vs repeat customers The LTV of customers acquired through certain SKUs Whether hero products are driving conversions that lead to upsells or cross-sells
	MMM (Marketing Mix Modelling) results	Econometric modelling output showing channel contribution and optimal budget allocations over time.
Gain executive alignment		Present key metrics to Finance and C-Suite and update budget strategy.

This framework provides you with the signals, metrics, and review cadence to run this process, aligning your demand-led growth strategies with key business priorities. For more on measuring demand-led growth, read this blog.

Take the next step to scaling your performance, with AI. Talk to our team to find out how our AI & ML platform uses the principles of demand-led growth with these metrics to scale PMax performance.

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