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Prova 产出物
面向营销团队的 AI Readiness Scorecard
评估营销团队是否具备负责任 pilot AI workflow 所需的 signal、data、运营节奏和已 codify 的判断标准。
适合人群正在判断团队是否准备好 AI pilot 的 Marketing VP · 不想在 delivery 准备好之前销售 AI transformation 的代理商负责人 · 正在评估客户团队的 fractional CMO 或 consultant · 希望在买工具前暴露基础缺口的 marketing ops leader
模板字段
- Readiness item
- What 4+ looks like
- Current score from 1-5
- Evidence
- Gap
- Owner
- Next 30-day fix
填写示例
An in-house growth team preparing to pilot AI-supported reporting and campaign recommendations.
下面的填写示例保留英文，因为 Prova 会用英文评审提交的 artifact。
First-party conversion signals are reliable
First-party data strategy is in place
AI-native campaign types are understood and operational
Paid, owned, and earned are planned as one system
Emerging channels are considered deliberately
Primary KPIs are separated from optimization metrics
Campaign data is clean, labeled, and queryable
Planning principles and brand guides are codified for AI use
弱版本 vs 强版本
弱版本
- Item
- Data is clean
- Score
- 4
- Evidence
- We have dashboards
- Gap
- Some naming issues
- Owner
- Analytics
- Next fix
- Improve tracking
| Item | Data is clean |
|---|---|
| Score | 4 |
| Evidence | We have dashboards |
| Gap | Some naming issues |
| Owner | Analytics |
| Next fix | Improve tracking |
为什么不够好
- The score is unsupported.
- Dashboards do not prove the data is queryable or trustworthy.
- "Some naming issues" hides the operational impact.
- The owner is a department, not a person or role.
- "Improve tracking" is not a 30-day fix.
强版本
- Item
- Campaign data is clean, labeled, and queryable
- Score
- 2
- Evidence
- Google Ads and Meta naming conventions differ; LinkedIn uses old campaign taxonomy; weekly report still relies on manual spreadsheet cleanup
- Gap
- AI cannot compare cross-platform performance without manual reconciliation
- Owner
- Marketing analytics lead with paid media lead as reviewer
- Next 30-day fix
- Standardize naming for new campaigns and create a one-page exception log for legacy campaign data
| Item | Campaign data is clean, labeled, and queryable |
|---|---|
| Score | 2 |
| Evidence | Google Ads and Meta naming conventions differ; LinkedIn uses old campaign taxonomy; weekly report still relies on manual spreadsheet cleanup |
| Gap | AI cannot compare cross-platform performance without manual reconciliation |
| Owner | Marketing analytics lead with paid media lead as reviewer |
| Next 30-day fix | Standardize naming for new campaigns and create a one-page exception log for legacy campaign data |
为什么有效
- Evidence is concrete.
- The score is honest.
- The gap explains why AI output would fail.
- Ownership is specific.
- The next fix is narrow enough to complete.
Prova 会评审泛用 AI 经常漏掉的部分
- Whether readiness scores are backed by evidence
- Whether "we have dashboards" is being mistaken for usable operating data
- Whether gaps are prerequisites or nice-to-haves
- Whether the team is ready for a pilot or needs foundation repair first
- Whether the next sprint should be workflow audit, measurement architecture, rollout planning, or diagnostic repair
下一步
想获得对自己版本的反馈？Prova 会先用一个简短 assessment，让 review 标准与你的角色、目标和第一批受众一致。之后你会进入适合当前工作的 sprint。
Prova 目前仅提供英文版。
提交前：请移除客户姓名、机密数字，以及任何团队不希望存入 training 或 coaching system 的信息。
前往英文版 Prova