Digital analytics converts customer and campaign data into decisions. Effective measurement begins with objectives and a documented tracking plan, not with collecting every available metric.
| Level | Examples |
|---|---|
| Business Outcome | Revenue, profit, retention, market share |
| Customer Outcome | Awareness, satisfaction, conversion, loyalty |
| Marketing Outcome | Qualified leads, sales, acquisition cost, lifetime value |
| Channel Metric | Reach, traffic, engagement, clicks, video views |
| Diagnostic Metric | Page speed, errors, bounce, frequency, quality score |
A tracking plan documents each event, business definition, trigger, parameters, platform, owner, and validation method. Examples include product view, form start, lead submission, add to cart, purchase, subscription renewal, and support request.
| Model | Approach | Limitation |
|---|---|---|
| First Interaction | Credits the first known touchpoint | Ignores later influence |
| Last Interaction | Credits the final touchpoint | Undervalues discovery channels |
| Linear | Splits credit equally | Assumes equal contribution |
| Position Based | Emphasizes first and last interactions | Uses predetermined weighting |
| Data Driven | Uses observed conversion patterns | Requires sufficient reliable data |
Dashboards should present objectives, targets, actual performance, trends, segmentation, and recommended action. Avoid vanity metrics, unclear definitions, excessive charts, and incompatible data sources.