01
Apps & workflows
Configure commerce, paid-media, analytics, email and CRM sources from one workspace.
Measurement,
not guesswork
Bring media, commerce and customer data into one workspace. Compare reported attribution with a modelled view, and act on governed budget decisions.
Stripe payment setup · Role-based data grants · Recorded budget actions
Platform-reported
Meta Ads£82,400
Google Ads£61,900
TikTok Ads£44,100
Channels claim overlapping credit — totals overstate contribution.
Modelled contribution
Meta Ads£58,200
Google Ads£67,300
TikTok Ads£29,800
One consistent model estimates each channel's incremental effect.
Available connection options
ShopifyMeta AdsGoogle AdsTikTok AdsGA4Klaviyo
The measurement platform
Four connected parts of the platform.
Aurelia combines source connections, dbt models, dashboards, role-based data grants and a recorded workflow for proposed budget changes.
02
Governed gold layer
Bronze, silver and gold dbt models turn raw source fields into the marts read by dashboards.
03
Reported & modelled views
Compare reported attribution with period-level outputs from the marketing-mix model.
04
Governance controls
Apply role-based SELECT grants and review the before-and-after state of budget actions.
Why marketing mix modelling
Better evidence for cross-channel budget decisions.
Trusting numbers from an advertising platform is like asking a student to grade their own homework.
Each platform can report the interactions it observes, but several platforms may claim credit for the same customer or sale. Marketing mix modelling evaluates channels together against the business outcome.
ComparisonPlatform attributionMarketing mix model
Question
Platform attributionWhich tracked interaction preceded a conversion?
Marketing mix modelHow did channel investment relate to total business results?
Scope
Platform attributionThe platform’s own clicks, views and conversion window.
Marketing mix modelChannels considered together at an aggregate period level.
Credit
Platform attributionMultiple platforms can claim the same outcome.
Marketing mix modelContribution is estimated within one consistent model.
Best used for
Platform attributionIn-platform campaign and creative optimisation.
Marketing mix modelCross-channel measurement and budget planning.
MMM does not replace day-to-day platform reporting. Aurelia keeps reported attribution alongside period-level modelled results so each is used for the decision it can support.
AI marketing agent
From insight to governed action.
Aurelia Auto can move beyond explaining the numbers and draft a budget allocation. Autonomy is controlled by workspace policy, fixed guardrails and an action history—not an open-ended instruction.
1
Insight
Reads governed metrics through the semantic layer to explain performance and attribution.
2
Recommendation
Drafts a budget allocation from lower to higher average incremental-ROAS channels.
3
Policy check
Checks the movement limit, constant total budget and the workspace autonomy policy.
4
Governed action
Waits for approval or applies an in-policy plan automatically, with before/after state retained.
Assisted
The agent proposes. An owner decides.
Every budget change waits for explicit approval before it is applied to the workspace plan.
Guardrailed auto
Automatic only inside the policy.
No channel moves by more than 20%, total budget stays constant and anything outside the guardrails still requires a person.
Every proposal records before and after plan state for review and rollback.Create a workspace →
Platform components
One layer for measurement workflows.
Dashboards read the gold marts, and budget proposals use the same modelled channel-performance data through the semantic layer.
8
source options
Commerce, paid media, analytics, email, CRM and support connectors.
raw → gold
medallion pipeline
Bronze, silver and gold dbt models are included in the platform.
2 views
attribution comparison
Reported revenue alongside period-level modelled revenue.
deny-by-default
optional governance
When enabled, members read only the securables granted to their role.
before → after
budget action history
Proposals record their status and plan state for execution or rollback.
From raw to gold
A dbt pipeline from raw inputs to dashboard marts.
Airbyte lands raw source data; a dbt medallion refines it into clean, conformed, business-ready marts. Your dashboards read the gold layer directly.
Data flow
Sources to automated, governed action
Governed automation
01 · Sources
SShopify
MMeta
GGoogle
KKlaviyo
Airbyte sync
02 · Land
Data warehouse
Raw landing zone
03 · Transform
dbtBronzeLand raw
SilverClean & conform
GoldBuild marts
04 · Display
Dashboards
Live gold metrics
05 · Act with agentic AI
Aurelia Auto
Turns governed metrics into policy-checked budget actions.
Insight→Guardrail→Action
Ingest continuouslyTransform reliablyReport consistentlyAct within guardrails
Role-based governance
Control who can see what.
Aurelia organises data using a catalog.schema.table namespace. When governance is enabled, member access is deny-by-default and workspace owners grant SELECT access per role.
aurelia (catalog)
├── marketing member: SELECT
├── commerce no access
└── customers no access
Pricing
Choose the workspace that fits.
Monthly pricing is shown below. Annual billing uses the lower monthly equivalent listed on each plan.
Starter
For lean teams centralising their first marketing data.
£199/ month
£159/month equivalent when billed annually
✓5 sources
✓3 seats
✓MMM and agent workflows
Growth
For growing brands running incrementality and agent workflows.
£499/ month
£399/month equivalent when billed annually
✓15 sources
✓10 seats
✓MMM and agent workflows
Scale
For multi-brand organisations with advanced governance.
£999/ month
£799/month equivalent when billed annually
✓Unlimited sources
✓Unlimited seats
✓MMM and agent workflows
A payment method is saved during signup. No charge is made until a price and billing schedule are confirmed.
Your measurement foundation starts here.
Start a workspace
Connect your data and start measuring.
Configure supported sources, build the gold layer and compare reported attribution with modelled measurement.