Use CasesResources
Book a CallScan Now
Meet IaaSimov

Autonomous observability for marketing divergence.

Every platform in your marketing stack produces a confident answer. IaaSimov is the only instrument positioned to see where those answers diverge from reality — across your entire stack, continuously, from outside every system it monitors.

Proposition — I

An observer cannot be inside the system it observes.

The Observer Position

Why it has to be outside the stack.

Every existing tool — your analytics, your attribution platform, your tracking debugger — is embedded inside the system it monitors. Each can only see its own slice. None can see what bypasses it, contradicts it, or degrades before reaching it.

Embedded tools
See their own slice.
  • Process only what passes through them — cannot see what was bypassed, corrupted, or routed elsewhere
  • Cannot see their own blind spots — that's what makes them blind spots
GA4 · Meta Ads Manager · Google Tag Diagnostics · Elevar · Triple Whale · Northbeam
IaaSimov
Sees the space between.
  • Holds all layers simultaneously — what each platform received, recorded, and what actually happened
  • Lives in the space between platforms, where divergence occurs and no embedded tool can reach
External · Continuous · Cross-platform · Atomic to dollar

No embedded actor can see its own blind spots. IaaSimov can — because it is not inside any of the systems it is watching.

Proposition — II

Divergence isn't one problem in one place.

Three layers of divergence

It compounds upward through the stack.

Divergence isn’t a tracking problem. It isn’t an attribution problem. It shows up across your entire marketing operation — in three layers, each building on and contaminating the next.

L03

Strategic

Budget, allocation, optimisation.

Surface · the decisions

Budget drifts toward channels that report well — not channels that perform well.

Each optimisation cycle widens the gap. ROAS-based allocation built on signals corrupted at the structural layer below — so every decision compounds the next.

01

Meta reports 4.2× ROAS. Google reports 3.8×. Shopify shows revenue neither fully accounts for. Budget shifts to Meta.

Was Meta better — or did it just have better tracking?

02

Performance Max trained on conversion data missing 38% of actual events.

The algorithm optimises toward a diverged version of reality — drifting further from ground truth with every cycle.

Builds on L02↑
L02

Experience

User behaviour, conversion paths, creative.

The journey

User behaviour gets read from what platforms recorded — not from what users actually did.

Funnels report drop-offs that converted elsewhere. Creatives perform inconsistently because the platforms measuring them disagree. UX decisions get calibrated to signals, not to people.

01

Performance marketer refreshes creative. Tries new audiences. Numbers barely move.

The cause isn't the creative — it's that the platforms measuring it can't agree on what they're seeing.

02

£40K checkout redesign targeting 215 reported drop-offs. 109 were tracking artefacts.

The real UX problem was 48 users — ROI calculated against the wrong denominator.

Builds on L01↑
L01

Structural

Signals, data, infrastructure.

Foundation · signals & data

Your tracking says healthy. The data passing through it is degraded.

Signals that never arrive. Parameters corrupted in transit. Consent gaps that silently block data. Events that fire correctly but reach platforms missing the identifiers that make them useful.

01

FBCLID truncated in a redirect chain. Meta accepts the event. Conversion recorded. Attributed to the wrong source.

No error. No alert. The data looks clean — and is acting on a lie.

02

CAPI event sent 47 minutes after the user left. Platform records a "conversion."

The signal is stale by definition — and retargeting acts on it like fresh truth.

Foundation
Everything above is built on this layer — every layer above inherits its corruption.

Each layer’s failures feed the layer above. Each layer also has its own independent failures. The waste compounds with every optimisation cycle.

Proposition — III

Not a better version. A different category.

Why no one else can do this

Three blind categories. One vantage no one occupies.

The market has three categories of tools. Each is partially right. Each is structurally blind to a different layer. None is positioned to see the whole.

01

Platform Diagnostics

Meta · Google · GA4
Sees

Single platform, internal consistency. Whether their own system is working correctly.

Blind to

Cross-platform divergence. Ground truth vs platform record. What was lost before data reached them.

02

Attribution Tools

Triple Whale · Northbeam · Rockerbox
Sees

Cross-platform reconciliation of platform-reported data. Disagreement between platforms.

Blind to

Divergence that occurred before data reached platforms. Inherit the corruption they're trying to reconcile.

03

Tracking Tools

Elevar · LittleData · Stape
Sees

Server-side tracking integrity. Shopify data pipeline. Events as they pass through.

Blind to

What their own pipeline position causes them to miss. Embedded actors inside one layer.

Or — and this is the leap —
you could be outside all three.

— IaaSimov —

External Observer

positioned outside the stack

Positioned in the space between platforms and layers — where divergence actually lives, and where no embedded tool can reach. Not a feature improvement to an existing category. An entirely new vantage point.

All three layers. Cross-platform. Atomic to dollar. Continuously.

Vantage
Outside every system it monitors

This is not a product category improvement. It is a different product category.

The Mission

Trace every effect
back to its cause.

Across the entire marketing stack. Continuously. Autonomously. With full transparency.

Begin where divergence is most measurable. Expand as the data surface grows.

Atomic Event

FBCLID truncated in redirect chain

Signal Corruption

Meta records conversion, wrong source attributed

Strategic Drift

ROAS inflated → budget shifts to Meta

Dollar Waste

£12,400 /month attributed to wrong channel

Trace direction — atomic finding to dollar waste

Ready to see what’s diverged?

Start with a free Surface Scan. Or explore how IaaSimov works under the hood.

Start Free Scan →How IaaSimov Works