Marketing Measurement

One measurement system, instead of five platforms arguing with each other

Every DTC brand ends up with the same problem: Meta says it drove the sale, Google says it drove the sale, and last-click says something else entirely. Pangolin replaces that patchwork with a single, unified measurement system built on incrementality, so you know what's true rather than what each platform wants to claim.

Unify your measurement See how it works

Fragmented Attribution (95% Claimed)

Meta Ads41%

Google Ads35%

TikTok Ads19%

➔reconciled

Pangolin Unified (100% Reality)

Meta Ads24%

Google Ads22%

TikTok Ads9%

Baseline Organic45%

When every platform's attributed revenue is added together, DTC brands routinely see 150-250% of actual revenue being claimed. Unified measurement is how you find out what's real.

The problem

Every platform is grading its own homework

Classic marketing mix models were built for enterprise consumer brands with TV budgets. For digital-first DTC brands, they are completely broken.

01 Fragmented data Each ad platform, plus GA4 and Shopify, measures success using its own definitions, cookies and lookback windows.

02 Misleading attribution Platforms have a structural incentive to over-claim credit, since more attributed revenue justifies more budget.

03 Poor investment decisions Budget flows toward whichever platform's attribution looks best, not whichever channel is genuinely incremental.

04 Inefficient marketing spend The brand ends up funding attribution competitions between its own ad platforms, rather than funding growth.

This isn't a data quality problem you can fix with better tracking. It's a structural conflict of interest — no platform is incentivised to tell you it's less effective than it claims.

Attribution vs Reality

Attribution answers 'who gets the credit,' not 'what actually worked'

Measurement Method Traditional Trap Pangolin Unified Standard

Platform-attributed revenue✗ Multiple platforms claim credit for the same sale✓ A single reconciled view that sums to actual revenue

Last-click attribution✗ Ignores the upper-funnel channels that built the demand✓ Full-funnel incremental contribution

Pixel-based tracking✗ Degraded by iOS privacy changes and cookie restrictions✓ Aggregate, privacy-resilient modelling

Platform ROAS✗ Self-reported, with an inherent incentive to overstate✓ Independent, incrementality-based measurement

You cannot resolve a conflict of interest by asking the interested parties to mark their own work.

The Pipeline

From platform disputes to one trusted number

1Data IntegrationConnect your dataSpend and platform metrics from every channel are unified alongside actual business outcomes from Shopify and GA4.

2History AnalysisUnderstand historyA single statistical model is built across your trading history, independent of any platform's own claims.

3Bayesian EngineModel contributionEach channel's genuine incremental impact is separated from baseline demand and cross-channel overlap.

4Marginal ReturnsIdentify saturationResponse curves show where each channel's returns are strong and where they're already diminishing.

5Active ExecutionOptimise investmentRecommendations translate the unified model into a specific budget reallocation, with expected commercial impact.

Attribution vs Incrementality

What platforms claim versus what actually happened

Meta Ads

Platform Claimed41%

True Incremental24%

Google Ads (brand)

Platform Claimed18%

True Incremental6%

Google Ads (non-brand)

Platform Claimed17%

True Incremental16%

TikTok Ads

Platform Claimed19%

True Incremental9%

💡Insight: Branded search is the clearest example of platform over-claiming: it captures demand your other marketing already created, then reports it as its own performance.

What we do

From platform noise to a system you can trust

UnderstandWhat is happening?Pangolin builds one measurement system across every channel, so you're comparing like with like for the first time.

ExplainWhy is it happening?Every figure comes with the modelling logic behind it, so you can see why the unified view differs from what each platform claims.

PredictWhat's likely to happen next?Forecasts show how each channel is likely to perform at different spend levels, based on genuine incremental behaviour.

OptimiseWhat should we do?Budget recommendations are generated directly from the unified model, with human approval before anything changes.

Platform Interface

One dashboard, reconciled to reality

INCREMENTALITY MODEL ACTIVE Verification: Shopify Live Sync

Modelled Budget Allocations

Branded Search£25,000

Reduce to £7,000Over-claiming (71% Baseline demand created elsewhere)

Upper-Funnel Social£45,000

Scale to £63,000High Incremental efficiency (2.8x Marginal ROAS)

Retargeting£15,000

Keep StableWithin healthy saturation limits

Recommended Reallocation

Monthly savings-£18,000reallocated from Branded Search

Incremental opportunity+£18,000allocated to Upper-Funnel Channels

Expected profit impact+£34,200/mo

Deploy Budget Plan

Built for DTC Teams

A unified view for every stakeholder

CMONeeds one number to trust

• A single measurement system replacing platform-by-platform reporting.

• Confidence in board-level budget conversations.

Head of GrowthNeeds to stop wasting budget

• Clear visibility into where platforms are over-claiming credit.

• A model-backed reallocation plan.

Performance MarketerNeeds a defensible answer

• An independent view that isn't graded by the platforms themselves.

• Evidence to bring to internal budget discussions.

Finance TeamNeeds accurate reconciliation

• A unified view that sums to 100% of revenue, not 200%.

• A trustworthy basis for approving marketing budget.

Clear parameters

Frequently Asked Questions

Why do platform dashboards add up to more than 100% of my revenue?

Each platform's attribution model has an incentive to claim as much credit as possible to prove its worth and justify higher client spend.

Is unified measurement the same as multi-touch attribution?

No. Multi-touch attribution still assigns credit based on touchpoints and cookies. Unified measurement uses robust incrementality modeling to verify impact independent of user-level tracking.

How does Pangolin handle branded search specifically?

Branded search demand is modeled as a downstream effect of other marketing activity. We verify how much of it was organic demand that would have converted regardless.

Will this replace my ad platform reporting entirely?

Platform dashboards remain useful for day-to-day creative and campaign optimisation. Unified measurement drives strategic, high-level budget allocation decisions.

How long does it take to see a unified view?

Initial modelling is typically available within the first data connection cycle, giving you actionable allocation recommendations immediately.

Is this suitable for a brand just starting to scale paid media?

Yes. Adopting a unified measurement standard early prevents building bad habits based on over-inflated platform claims.

Stop letting your ad platforms mark their own homework

See what a unified view of your marketing actually shows.

Book a demo