Performance Measurement Framework for Demand-Led Growth

Download PDF here, or read below.

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 to do / 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.

Looking for a PDF to download? Click here.

Download the PDF here.