Transparency is the foundation of a credible benchmark.
We publish our methods openly so participants and readers can judge the research on its merits. This page explains how the study is designed, how responses are handled, and how scores are calculated.
Purpose
The study measures the adoption, maturity, and competency of AI within Chicago-area marketing organizations, and tracks how these change from year to year. It is intended as a shared reference for the regional community, not a ranking or a certification.
Who qualifies
Respondents must be involved in marketing at an organization that operates in the greater Chicago area. We welcome responses across seniority levels and organization sizes. Where multiple people from one organization respond, each response is retained and organization-level analysis is handled carefully to avoid double-counting.
How responses are validated
Responses are reviewed for completeness and internal consistency before inclusion. Incomplete submissions and responses that fail basic quality checks are excluded from the published aggregates. Authentication is required to reduce duplicate and low-quality submissions.
How data is anonymized
Findings are reported only in aggregate. Individual answers are never published or attributed. Organization names are used solely to count distinct participants and are separated from published results. Personally identifying details are not included in any released dataset.
Scoring philosophy
The AI Marketing Maturity Score is a weighted composite across 10 categories. Each question maps to a point scale reflecting increasing maturity, from absence of practice to embedded, measured, and governed use.
Category scores are normalized to a 0–100 scale, and the overall score is the weighted aggregate of answered, applicable questions. Conditional questions that do not apply to a respondent are excluded from their denominator, so scores are not penalized for irrelevance.
The score is deliberately framed as an informative benchmark rather than a precise diagnostic. It is most useful read alongside the category detail, and in comparison to the community average as it accumulates.
Five levels of AI marketing maturity
Overall scores map to one of five maturity levels. The bands are held constant year over year so progress remains comparable over time.
- Nascent0–24
AI is largely absent or experimental. Adoption is driven by individual curiosity rather than organizational intent.
- Emerging25–44
Early adoption is underway in pockets of the organization, but strategy, integration, and governance are still forming.
- Developing45–64
AI is a regular part of several marketing functions, supported by growing structure and leadership attention.
- Advanced65–84
AI is integrated across the marketing organization, measured deliberately, and paired with meaningful governance.
- Leading85–100
AI is embedded in how the organization operates and competes, with mature measurement, governance, and continuous experimentation.
Limitations
As with any self-reported survey, results reflect respondents' perceptions of their own practices. Early in each collection cycle, sample sizes are small and comparisons should be read as directional. We disclose response counts alongside all published figures.
Privacy
We collect only what the research requires. Data is stored securely, access is restricted, and individual records are never sold or shared. Participants may request removal of their data at any time.
Research integrity
The methodology is reviewed with independent research advisors. When we refine questions or scoring between years, we document the change so year-over-year comparisons remain honest and interpretable.