AI & data readiness scorecard for ecommerce marketing

Data unification1. Where does your marketing data (Shopify, ads, email, CRM) live today?

In each platform; we export when we need itPartly in a dashboard tool, partly in spreadsheetsIn a warehouse, but not all sources are connectedIn one warehouse with every source connected and modelled

Data unification2. Can you see one customer's orders, email engagement and ad touchpoints in a single record?

NoOnly inside the CRM, and it is incompleteMostly, with manual joinsYes, in a governed customer model

Reporting trust3. Do marketing revenue numbers match finance numbers at month end?

Rarely; it causes argumentsThey differ and we explain the gap each monthClose, with a documented reconciliationYes; one source of truth reconciled to the ledger

Reporting trust4. How long does the weekly performance report take to produce?

A day or more of someone's timeA few hours in spreadsheetsUnder an hour; mostly automatedIt is fully automated and lands before anyone asks

Workflow automation5. How are campaign launches checked before they go live?

By memory and goodwillA shared checklist someone ticks manuallyPartly automated checks on feeds, links and trackingAutomated QA with alerts; humans only review exceptions

Workflow automation6. How much of the team's week goes to copy-paste work between tools?

More than a thirdAround a quarterAround a tenthAlmost none; the tools talk to each other

AI usage7. How is the team using AI today?

Individuals use ChatGPT ad hocA few approved tools, no shared workflowsAI is built into one or two team workflowsAI tools run on our own data with measured quality

AI usage8. Can anyone on the team ask a question of your data in plain language and get a trusted answer?

No; it goes to an analyst's backlogOnly for a few saved dashboardsYes, for some sources, with caveatsYes, across the warehouse, with governance

Data security9. Is there a policy for what customer data can be sent to AI tools?

No policyAn informal rule people mostly followA written policy, not technically enforcedWritten policy enforced by redaction and access controls

Data security10. Where would an AI model that uses customer data run?

Wherever the vendor runs itA vendor with a data-processing agreementOur cloud account for some workloadsOur cloud account with encryption, logging and least privilege

Team capacity11. Who owns marketing data and automation in your team?

Nobody; it falls to whoever is freeA marketer who learned on the jobA dedicated analyst or ops personA small team with engineering support

Team capacity12. If a pipeline or automation broke tomorrow, how quickly would you know?

When someone notices the numbers look wrongWithin a few daysSame day, via a manual checkWithin minutes, via monitoring and alerts

How ready is your marketing team to run on its own data and AI?