Audit scattered marketing data, kill zombie reports, and build a unified reporting framework. Calibrated for the metrics HR Tech buying committees actually care about.
List every place marketing data currently lives. The ones you forget are usually the ones causing the most confusion.
| Source | What it tracks | Owner | Last reviewed | Confidence |
|---|---|---|---|---|
| CRM | H / M / L | |||
| Marketing automation | H / M / L | |||
| Web analytics | H / M / L | |||
| Ad platforms | H / M / L | |||
| Email platform | H / M / L | |||
| Event tools | H / M / L | |||
| Spreadsheets | H / M / L | |||
| H / M / L |
Active spreadsheets: If more than 3, you have a data fragmentation problem.
If a report doesn't directly inform a decision, it's a zombie. Kill it.
| Report name | Frequency | Who reads it | Decision it informs | Verdict |
|---|---|---|---|---|
| Keep / Kill / Redesign | ||||
| Keep / Kill / Redesign | ||||
| Keep / Kill / Redesign | ||||
| Keep / Kill / Redesign |
Monthly website traffic reports nobody acts on. Social media follower counts sent to leadership. "Campaign recap" decks that get filed and never referenced. Weekly lead counts without source attribution.
Tier 1: Board / Executive (monthly or quarterly)
| Metric | Current value | Source of truth | Confidence |
|---|---|---|---|
| Pipeline generated by marketing | H / M / L | ||
| Marketing-sourced revenue | H / M / L | ||
| Customer acquisition cost (CAC) | H / M / L | ||
| Pipeline velocity (days to close) | H / M / L |
Tier 2: Marketing Leadership (weekly)
| Metric | Current value | Source of truth | Confidence |
|---|---|---|---|
| MQLs by source | H / M / L | ||
| MQL → SQL conversion rate | H / M / L | ||
| Cost per MQL by channel | H / M / L |
HR Tech companies often count noise as signal. If your MQL definition doesn't filter for HR buyer titles and company size, fix that before optimizing anything else.
| Your current MQL definition | |
| Filters for HR buyer titles? | Yes / No |
| Filters for company size/stage? | Yes / No |
If your VP of Marketing and your demand gen manager pull "pipeline generated" and get different numbers, you have a definition problem — not a data problem. Align on definitions before building dashboards.
| Metric | Two people get same number? | Historical data available? | Can explain calculation? | Grade |
|---|---|---|---|---|
| Yes / No | Yes / No | Yes / No | A / B / C / F | |
| Yes / No | Yes / No | Yes / No | A / B / C / F | |
| Yes / No | Yes / No | Yes / No | A / B / C / F | |
| Yes / No | Yes / No | Yes / No | A / B / C / F |
| Gap type | Gap 1 | Gap 2 | Gap 3 |
|---|---|---|---|
| Data gaps (should track, can't) | |||
| Quality gaps (track, don't trust) | |||
| Reporting gaps (exists, not surfaced) |
| Week | Action | Owner | Definition of done |
|---|---|---|---|
| 1-2 | Align on MQL definition + Tier 1 metric calculations | Written definitions reviewed by mktg + sales | |
| 3-4 | Consolidate critical spreadsheet data | Spreadsheets migrated or connected | |
| 5-6 | Kill zombie reports, redesign keepers | Report list actioned | |
| 7-8 | Build Tier 1 dashboard with trusted data | Leadership can self-serve Tier 1 metrics | |
| 9-10 | Add Tier 2 metrics to dashboard | Marketing team has weekly operational view | |
| 11-12 | Establish data review cadence | Monthly data quality check scheduled |
Time cost: ______ hours/week spent pulling, reconciling, and formatting data × $______ loaded cost/hour = $______ /year in reporting labor.
The ask: "I need [X hours] to audit our data and build reporting we can trust. The output replaces [Y] manual reports and gives us confidence in the numbers behind budget decisions."
Need more than a template?
Fractional CMO leadership for HR Tech companies.
Email: christen@cgm-marketing.com | cazimimarketing.com/contact-me