Short answer
Marketing analytics uses reliable marketing data to evaluate performance, explain likely drivers, state uncertainty, and guide decisions about future work and investment.
About Marketing analytics
Uses marketing data to evaluate performance, explain drivers, and guide investment decisions. It combines sound definitions, appropriate analysis, and clear limits so decisions match the available evidence.
Use this competency for
- Roles that interpret marketing data to guide program, channel, audience, or investment decisions.
- Work that defines measures, checks evidence quality, or explains changes in marketing performance.
Do not use this competency for
- Roles that only enter or export data without interpreting it or advising a decision.
Important distinctions
Marketing operations
Marketing operations maintains reliable processes, systems, and data flows. Marketing analytics interprets data to explain performance and guide choices.
Audience research
Audience research builds evidence about needs, context, and behavior. Marketing analytics evaluates observed marketing performance and its likely drivers.
Expectations by level
IC1
Individual contributor 1
Produces defined analyses with guidance, applies agreed measure definitions, checks routine data quality issues, and separates observed facts from interpretations.
Observable behaviors
- Calculates agreed measures using the documented source and definition.
- Checks missing values, duplicate records, and date ranges before reporting.
- Labels observations, interpretations, and unanswered questions separately.
Examples
- Finds that two reports use different date ranges before comparing their results.
- Rewrites a report to distinguish a measured decline from an untested explanation.
IC2
Individual contributor 2
Independently designs analysis for a defined marketing decision, joins relevant evidence, tests plausible explanations, and recommends action with stated limits.
Observable behaviors
- Chooses measures and comparison groups that fit the decision being made.
- Tests alternative explanations before naming a likely performance driver.
- Presents a recommendation with assumptions, uncertainty, and follow-up questions.
Examples
- Shows that a channel change coincided with a different audience mix before attributing the result.
- Recommends a limited test because the available data cannot support a broad investment decision.
IC3
Individual contributor 3
Sets the analytical approach for ambiguous decisions spanning programs or channels, resolves conflicting definitions, and improves how teams use evidence without overstating certainty.
Observable behaviors
- Frames an ambiguous business question as testable analytical decisions.
- Aligns teams on definitions needed for valid comparisons across work.
- Challenges unsupported conclusions and proposes evidence that would reduce uncertainty.
Examples
- Creates a common comparison method when channel reports attribute the same outcome differently.
- Advises against reallocating investment after finding that the apparent change comes from a tracking break.