aiwg

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Cognitive architecture for AI-augmented software development with structured memory, ensemble validation, and closed-loop correction. FAIR-aligned artifacts, 84% cost reduction via human-in-the-loop, standards adopted by 100+ organizations.

aiwg.io

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# KPI Dashboard Specification Template ## Metadata - ID: RPT-### - Owner: [Data Analyst / Analytics Engineer] - Contributors: [Dashboard Designer, Marketing Ops, BI Developer] - Reviewers: [Analytics Lead, Marketing Leadership] - Team: Marketing Analytics - Stakeholders: [Dashboard End Users - Campaign Managers, Leadership, etc.] - Status: draft | in-progress | review | approved | published | archived - Dates: created YYYY-MM-DD / updated YYYY-MM-DD / published YYYY-MM-DD / scheduled YYYY-MM-DD - Campaign: CAM-### (if campaign-specific) or N/A (if organization-wide) - Channel: multi-channel (covers all marketing channels) or [specific channel] - Audience: [Target dashboard users - e.g., "Campaign Managers", "Executive Team"] - Related: [RPT-### (measurement plan), CAM-### (campaigns), STR-###] - Links: [Dashboard URL, design mockups, data source documentation] - Tags: [dashboard, KPIs, reporting, analytics, visualization] ## Marketing-Specific Metadata - KPIs: N/A (this defines dashboard displaying KPIs) - Budget: $[dashboard tool licensing costs, development time] - Timeline: start YYYY-MM-DD / end YYYY-MM-DD / milestones [design, development, testing, launch] - Brand Compliance: N/A (internal tool) - Legal Review: N/A (internal tool, privacy-compliant data sources) - Performance: N/A (specification document) ## Related Templates - /templates/analytics/measurement-plan-template.md - /templates/analytics/campaign-report-template.md - /templates/analytics/monthly-report-template.md --- ## 1. Dashboard Overview ### 1.1 Purpose **Dashboard Name**: [e.g., "Executive Marketing Dashboard" or "Q1 Product Launch Campaign Dashboard"] **Primary Purpose**: [One sentence describing what this dashboard solves - e.g., "Provide real-time visibility into marketing-sourced pipeline and ROI for executive decision-making"] **Use Cases**: - [Use case 1 - e.g., "Daily performance monitoring during active campaigns"] - [Use case 2 - e.g., "Weekly business reviews with marketing leadership"] - [Use case 3 - e.g., "Month-end reporting for finance reconciliation"] **Success Criteria**: [How we measure dashboard effectiveness - e.g., "80% of executives use dashboard weekly, reduces manual reporting time by 50%"] ### 1.2 Target Audience **Primary Users**: - **Role**: [e.g., "VP Marketing, CMO"] - **Usage frequency**: [Daily / Weekly / Monthly / As-needed] - **Key questions**: [What they need to answer - e.g., "Are we on track to hit MQL target?", "What's our ROAS by channel?"] - **Technical proficiency**: [Low / Medium / High - influences complexity of dashboard] **Secondary Users**: - **Role**: [e.g., "Campaign Managers, Paid Media Specialists"] - **Usage frequency**: [Daily / Weekly / Monthly / As-needed] - **Key questions**: [e.g., "Which ads are underperforming?", "Should I reallocate budget?"] - **Technical proficiency**: [Low / Medium / High] **Dashboard Access**: [Who can view - e.g., "All marketing team members", "Marketing + Sales leadership", "Public (for team transparency)"] ### 1.3 Data Sources | Data Source | Data Included | Update Frequency | Latency | Owner | |-------------|---------------|------------------|---------|-------| | [e.g., "Google Analytics 4"] | [User behavior, conversions, traffic sources] | [Real-time] | [<5 minutes] | [Marketing Ops] | | [e.g., "Salesforce CRM"] | [Leads, opportunities, revenue] | [Real-time sync] | [<15 minutes] | [Sales Ops] | | [e.g., "Google Ads"] | [Impressions, clicks, spend, conversions] | [Hourly] | [<1 hour] | [Paid Media Manager] | | [e.g., "HubSpot"] | [Email engagement, form submissions] | [Real-time] | [<5 minutes] | [Marketing Ops] | | [Data source N] | [Data] | [Frequency] | [Latency] | [Owner] | **Data Warehouse Integration**: [Yes / No - if yes, specify: e.g., "Data aggregated in BigQuery, dashboard powered by Looker Studio"] **Data Refresh Schedule**: [e.g., "Real-time for most metrics, CRM syncs every 15 minutes, ad platforms sync hourly"] --- ## 2. KPIs & Metrics ### 2.1 Primary KPIs **North Star Metric**: [Single most important metric - e.g., "Marketing-Sourced Pipeline"] **Primary KPIs** (top 5 metrics): | KPI | Definition | Calculation | Target | Data Source | Update Frequency | |-----|------------|-------------|--------|-------------|------------------| | [e.g., "MQLs"] | [Marketing-qualified leads] | [COUNT(leads WHERE status='MQL')] | [500/month] | [CRM] | [Real-time] | | [e.g., "Cost per MQL"] | [Total spend / MQLs] | [SUM(ad_spend) / COUNT(MQLs)] | [$50] | [Ad platforms + CRM] | [Daily] | | [e.g., "MQL → SQL %"] | [MQL to sales-qualified lead conversion] | [COUNT(SQLs) / COUNT(MQLs)] | [30%] | [CRM] | [Real-time] | | [e.g., "Pipeline Created"] | [Total opportunity value from marketing] | [SUM(opportunity_value WHERE source='Marketing')] | [$500k/month] | [CRM] | [Real-time] | | [e.g., "ROAS"] | [Return on ad spend] | [Revenue / Ad Spend] | [3.0x] | [CRM + Ad platforms] | [Daily] | ### 2.2 Supporting Metrics **Funnel Metrics**: | Funnel Stage | Metrics | Target | Rationale | |--------------|---------|--------|-----------| | **Awareness** | [Impressions, Reach, Share of Voice] | [1M impressions/month] | [Top-of-funnel health] | | **Consideration** | [Website visits, Content downloads, Time on site] | [50k visits/month, 2:30 avg time] | [Engagement depth] | | **Intent** | [Demo requests, Trial signups, Pricing page views] | [200 demos/month] | [Buying intent signals] | | **Conversion** | [MQLs, SQLs, Opportunities] | [500 MQLs, 150 SQLs, $500k pipeline] | [Sales-ready leads] | | **Retention** | [Customer engagement, NPS, Renewal rate] | [NPS 50+, 90% renewal] | [Long-term value] | **Channel Metrics**: | Channel | Primary Metrics | Target | Rationale | |---------|-----------------|--------|-----------| | **Paid Search** | [Clicks, CPC, Conversion rate, ROAS] | [5000 clicks, $2.50 CPC, 5% CVR, 4x ROAS] | [Performance and efficiency] | | **Paid Social** | [Impressions, CPM, CTR, Cost per lead] | [500k impr, $15 CPM, 1.5% CTR, $40 CPL] | [Reach and lead gen] | | **Organic Search** | [Organic traffic, Keyword rankings, CTR] | [20k visits, 15 keywords in top 10, 3% CTR] | [SEO health] | | **Email** | [Send volume, Open rate, Click rate, Conversion rate] | [50k sends, 25% open, 5% click, 2% CVR] | [Engagement and conversion] | | **Content** | [Page views, Time on page, Downloads, Social shares] | [100k views, 3:00 avg time, 500 downloads] | [Content engagement] | ### 2.3 Operational Metrics **Health Indicators** (early warning signals): | Metric | Definition | Target | Alert Threshold | |--------|------------|--------|-----------------| | [e.g., "Tracking Coverage %"] | [% of campaigns with proper UTM tagging] | [100%] | [Alert if <95%] | | [e.g., "Data Freshness"] | [Minutes since last data sync] | [<15 min] | [Alert if >30 min] | | [e.g., "Conversion Discrepancy %"] | [Difference between GA4 and CRM conversions] | [<5%] | [Alert if >10%] | | [e.g., "Budget Pacing %"] | [Spend to date / (Budget * % through period)] | [95-105%] | [Alert if <90% or >110%] | --- ## 3. Dashboard Layout & Design ### 3.1 Dashboard Sections **Section 1: Executive Summary** (top of dashboard): - **KPIs displayed**: [MQLs, Pipeline, Revenue, CAC, ROAS] - **Visualization type**: [Scorecards with trend indicators (arrows, sparklines)] - **Layout**: [5 scorecard tiles in horizontal row] - **Filters applied**: [Current month by default, user can change date range] **Section 2: Funnel Performance**: - **KPIs displayed**: [Impressions → Clicks → Leads → MQLs → SQLs → Opportunities → Closed-Won] - **Visualization type**: [Funnel chart with conversion rates between stages] - **Layout**: [Full-width funnel chart] - **Filters applied**: [Date range, channel] **Section 3: Channel Performance**: - **KPIs displayed**: [Spend, Impressions, Clicks, Conversions, ROAS by channel] - **Visualization type**: [Horizontal bar chart for channel comparison, line chart for trends] - **Layout**: [Split view - bar chart left, line chart right] - **Filters applied**: [Date range, campaign] **Section 4: Campaign Deep-Dive** (optional, below the fold): - **KPIs displayed**: [Campaign-level metrics - impressions, clicks, conversions, spend, ROAS] - **Visualization type**: [Data table with sortable columns] - **Layout**: [Full-width table with drill-down capability] - **Filters applied**: [Date range, channel, status (active/paused/completed)] **Section 5: Trends & Insights** (optional): - **KPIs displayed**: [Week-over-week / month-over-month comparisons] - **Visualization type**: [Line charts showing trends over time] - **Layout**: [2-column grid with multiple trend charts] - **Filters applied**: [Date range, channel] ### 3.2 Wireframe / Layout ``` ┌─────────────────────────────────────────────────────────────────────┐ │ EXECUTIVE MARKETING DASHBOARD [Date Filter ▼] │ ├─────────────────────────────────────────────────────────────────────┤ │ EXECUTIVE SUMMARY │ ├───────────┬───────────┬───────────┬───────────┬───────────┐ │ │ MQLs │ Pipeline │ Revenue │ CAC │ ROAS │ │ │ 487 │ $487k │ $125k │ $52 │ 3.2x │ │ │ ↑ 12% │ ↑ 18% │ ↓ 5% │ ↓ 8% │ ↑ 15% │ │ └───────────┴───────────┴───────────┴───────────┴───────────┘ │ ├─────────────────────────────────────────────────────────────────────┤ │ FUNNEL PERFORMANCE │ │ Impressions → Clicks → Leads → MQLs → SQLs → Opps → Closed-Won │ │ 1.2M 18k 1.5k 487 146 58 12 │ │ 1.5% 8.3% 32.5% 30.0% 39.7% 20.7% │ └─────────────────────────────────────────────────────────────────────┘ ├─────────────────────────────────────────────────────────────────────┤ │ CHANNEL PERFORMANCE │ ├──────────────────────────────┬──────────────────────────────────────┤ │ Channel Comparison (ROAS) │ Trend (Conversions Over Time) │ │ ┌────────────────────────┐ │ ┌────────────────────────────────┐ │ │ │ Paid Search ████ 4.2x │ │ │ ╱╲ │ │ │ │ Paid Social ███ 3.5x │ │ │ ╱╲╱ ╲ ╱╲ │ │ │ │ Email ██ 2.8x │ │ │ ╱╲╱ ╲╱ ╲ │ │ │ │ Organic █ 2.1x │ │ │ ╱╱ ╲ │ │ │ └────────────────────────┘ │ └────────────────────────────────┘ │ └──────────────────────────────┴──────────────────────────────────────┘ ├─────────────────────────────────────────────────────────────────────┤ │ CAMPAIGN DETAILS (below fold) │ │ Campaign | Spend | Impressions | Clicks | Conv | ROAS │ │ Q1 Launch | $15,000 | 450,000 | 6,750 | 135 | 3.8x │ │ Webinar Promo | $5,000 | 120,000 | 1,800 | 45 | 4.2x │ │ Retargeting | $3,000 | 80,000 | 1,200 | 30 | 5.1x │ └─────────────────────────────────────────────────────────────────────┘ ``` ### 3.3 Visual Design Specifications **Color Palette**: - **Primary brand color**: [Hex code - e.g., #0066CC for headers, key metrics] - **Positive trend color**: [Green - e.g., #28A745 for upward trends, targets met] - **Negative trend color**: [Red - e.g., #DC3545 for downward trends, targets missed] - **Neutral color**: [Gray - e.g., #6C757D for secondary text, borders] - **Background**: [White #FFFFFF or light gray #F8F9FA] **Typography**: - **Headers**: [Font family, size, weight - e.g., "Inter, 24px, Bold"] - **Metric values**: [Font family, size, weight - e.g., "Inter, 36px, Bold"] - **Metric labels**: [Font family, size, weight - e.g., "Inter, 14px, Regular"] - **Body text**: [Font family, size, weight - e.g., "Inter, 12px, Regular"] **Chart Styles**: - **Line charts**: [2px line thickness, smooth curves, data point markers on hover] - **Bar charts**: [12px bar height, 4px spacing, rounded corners (2px radius)] - **Funnel charts**: [Gradient fill, stage conversion % labels inside each stage] - **Scorecards**: [Large value (36px), small label (12px), trend indicator (arrow + %)] **Spacing & Grid**: - **Section padding**: [24px top/bottom, 16px left/right] - **Tile spacing**: [16px gap between tiles] - **Grid**: [12-column responsive grid] --- ## 4. Interactivity & Filters ### 4.1 Global Filters **Date Range Picker**: - **Default**: [Last 30 days] - **Presets**: [Today, Yesterday, Last 7 days, Last 30 days, Last 90 days, Month-to-date, Quarter-to-date, Year-to-date, Custom range] - **Behavior**: [All charts update when date range changes] **Channel Filter**: - **Options**: [All channels (default), Paid Search, Paid Social, Email, Organic Search, Content, Events, Partnerships] - **Type**: [Multi-select dropdown] - **Behavior**: [Charts filter to selected channels only] **Campaign Filter** (optional): - **Options**: [All campaigns (default), list of active campaigns] - **Type**: [Multi-select dropdown or search box] - **Behavior**: [Dashboard shows selected campaign(s) only] **Region Filter** (if applicable): - **Options**: [All regions (default), North America, EMEA, APAC, etc.] - **Type**: [Single-select dropdown] - **Behavior**: [Charts filter to selected region] ### 4.2 Chart-Level Interactions **Hover Tooltips**: - **Display**: [Metric name, value, change vs previous period] - **Example**: ["MQLs: 487 (↑12% vs last month)"] **Click-Through / Drill-Down**: - **Scorecard click**: [Navigate to detailed report for that metric] - **Funnel stage click**: [Drill down to list of leads/opportunities in that stage] - **Channel bar click**: [Navigate to channel-specific dashboard] - **Campaign row click**: [Navigate to campaign deep-dive dashboard] **Sorting** (for data tables): - **Columns**: [All columns sortable by clicking header] - **Default sort**: [By spend (descending)] **Export**: - **Formats**: [CSV, PDF, PNG (screenshot)] - **Button location**: [Top-right corner of dashboard] --- ## 5. Performance & Technical Requirements ### 5.1 Performance Targets **Load Time**: - **Initial load**: [<3 seconds for dashboard with default filters] - **Filter change**: [<1 second to update all charts] - **Drill-down**: [<2 seconds to navigate to detail view] **Data Refresh**: - **Real-time data**: [<5 minute latency for GA4, CRM] - **Ad platform data**: [<1 hour latency for Google Ads, Meta Ads] - **Aggregated data**: [Pre-aggregated in data warehouse for faster queries] **Concurrency**: - **Simultaneous users**: [Support 100+ concurrent users without performance degradation] ### 5.2 Technical Stack **BI Platform**: [e.g., "Looker Studio", "Tableau", "Power BI", "Metabase"] **Data Warehouse**: [e.g., "BigQuery", "Snowflake", "Redshift", or "Direct connections to source systems"] **Data Pipeline**: [e.g., "Fivetran for ETL", "dbt for transformations", "Airflow for orchestration"] **Hosting**: [e.g., "Cloud-hosted (GCP/AWS/Azure)" or "On-premise"] **Access Control**: [e.g., "SSO via Google Workspace", "Role-based access in Looker"] ### 5.3 Data Transformations **Pre-Aggregations** (for performance): - [Daily aggregation of campaign metrics (spend, impressions, clicks, conversions)] - [Hourly aggregation of real-time metrics (website visits, form submissions)] - [Weekly aggregation for historical trend charts] **Calculated Metrics** (computed in dashboard): - [ROAS = Revenue / Ad Spend] - [Cost per MQL = Total Spend / MQL Count] - [MQL → SQL % = SQL Count / MQL Count] - [Budget Pacing % = (Spend to Date / Days Elapsed) / (Total Budget / Total Days)] **Data Quality Checks** (before displaying): - [Validate no negative spend values] - [Validate conversion counts match between GA4 and CRM (within 10% tolerance)] - [Flag missing UTM parameters] --- ## 6. Insights & Alerts ### 6.1 Automated Insights **Trend Insights** (auto-generated): - [e.g., "MQLs up 12% vs last month - driven by Paid Search (+25%)"] - [e.g., "ROAS declining for Paid Social - cost per conversion up 18%"] - [e.g., "Organic traffic up 30% - attributed to new blog content"] **Anomaly Detection**: - [Alert when metric deviates >20% from 7-day average] - [Example: "Warning: Website traffic down 35% today vs 7-day average"] **Recommendations** (AI-driven or rule-based): - [e.g., "Reallocate budget from Email (2.8x ROAS) to Paid Search (4.2x ROAS)"] - [e.g., "Paid Social campaign 'Q1 Launch' is pacing 15% over budget - consider reducing spend"] ### 6.2 Alert Configuration **Performance Alerts**: | Alert | Condition | Delivery Method | Recipients | |-------|-----------|-----------------|------------| | [e.g., "Daily MQL target missed"] | [MQL count <80% of daily target] | [Email, Slack] | [Demand Gen Lead, Marketing Ops] | | [e.g., "ROAS drops below 2.0x"] | [ROAS <2.0 for any channel] | [Email, Slack] | [Paid Media Manager, VP Marketing] | | [e.g., "Budget overspend"] | [Spend pacing >110% of budget] | [Email] | [Campaign Manager, Finance] | | [e.g., "Data quality issue"] | [GA4-CRM conversion discrepancy >10%] | [Slack] | [Analytics Team] | **Alert Frequency**: [Real-time for critical alerts, daily digest for others] **Alert Suppression**: [Allow users to snooze alerts for 24 hours, 7 days, or dismiss permanently] --- ## 7. User Access & Permissions ### 7.1 Role-Based Access | Role | Access Level | Permissions | Users | |------|--------------|-------------|-------| | **Admin** | [Full access] | [Edit dashboard, manage data sources, manage users] | [Analytics Lead, Marketing Ops] | | **Editor** | [Edit access] | [Modify filters, create custom views, cannot edit data sources] | [Campaign Managers, Paid Media Specialists] | | **Viewer** | [Read-only] | [View dashboard, use filters, export data] | [All marketing team] | | **Executive** | [Read-only with executive summary] | [View high-level KPIs, cannot drill down to granular data] | [VP Marketing, CMO, CFO] | ### 7.2 Data Visibility **Row-Level Security** (if applicable): - [Campaign Managers see only their campaigns] - [Regional Managers see only their region's data] - [Leadership sees all data] **Sensitive Data Handling**: - [No PII (names, email addresses) displayed in dashboard] - [Aggregate data only - no user-level data] - [Revenue data visible only to Finance + Marketing Leadership] --- ## 8. Testing & Validation ### 8.1 Pre-Launch Testing **Data Accuracy Testing**: - [ ] Compare dashboard metrics to source system reports (GA4, CRM, ad platforms) - [ ] Validate calculations for computed metrics (ROAS, conversion rates, etc.) - [ ] Test date range filtering (ensure correct data returned for all date presets) - [ ] Verify channel filter correctly includes/excludes campaigns **Performance Testing**: - [ ] Load test with 50+ concurrent users - [ ] Test load time with 90 days of data (max expected date range) - [ ] Test filter performance (ensure <1 second update time) **Cross-Browser/Device Testing**: - [ ] Test on Chrome, Firefox, Safari, Edge - [ ] Test on mobile (iOS Safari, Android Chrome) - [ ] Test on tablet (iPad, Android tablet) - [ ] Verify responsive design works on all screen sizes **User Acceptance Testing (UAT)**: - [ ] Walkthrough with 3-5 target users (campaign managers, leadership) - [ ] Collect feedback on usability, clarity, missing metrics - [ ] Iterate on design based on feedback ### 8.2 Post-Launch Monitoring **Usage Metrics**: - [Track weekly active users] - [Track most-used filters and date ranges] - [Track drill-down click patterns (which charts get most interaction)] **Data Quality Monitoring**: - [Daily check for data freshness (<15 min latency)] - [Weekly check for metric discrepancies vs source systems] - [Monthly audit of calculated metrics] **User Feedback**: - [Feedback form linked in dashboard footer] - [Quarterly user survey on dashboard effectiveness] - [Office hours for users to ask questions, request features] --- ## 9. Maintenance & Iteration ### 9.1 Maintenance Schedule **Daily**: - [Monitor data freshness alerts] - [Check for data quality anomalies] **Weekly**: - [Review automated insight accuracy] - [Review alert performance (false positives/negatives)] **Monthly**: - [Review usage metrics] - [Prioritize user feedback and feature requests] - [Update dashboard with new campaigns/channels] **Quarterly**: - [Full data accuracy audit (compare to source systems)] - [Review KPI relevance (are we measuring what matters?)] - [Dashboard design refresh (update layout, add new insights)] ### 9.2 Iteration Roadmap **Phase 1: Launch** (Current): - [Core KPIs, basic filters, static insights] **Phase 2: Enhancements** (3 months post-launch): - [AI-driven recommendations] - [Anomaly detection alerts] - [Custom views per user] **Phase 3: Advanced Features** (6 months post-launch): - [Predictive analytics (forecast MQLs, pipeline)] - [Cohort analysis (track campaign performance over time)] - [A/B test result integration] **Phase 4: Optimization** (12 months post-launch): - [Natural language queries (ask "What's my ROAS this month?")] - [Mobile app for on-the-go monitoring] - [Integration with Slack for conversational analytics] --- ## 10. Appendix ### 10.1 Metric Definitions | Metric | Definition | Calculation | Example | |--------|------------|-------------|---------| | **Impressions** | Number of times ad/content was displayed | COUNT(ad_views) | 1,200,000 | | **Clicks** | Number of times users clicked ad/link | COUNT(clicks) | 18,000 | | **CTR** | Click-through rate | Clicks / Impressions | 1.5% | | **MQLs** | Marketing-qualified leads | COUNT(leads WHERE status='MQL') | 487 | | **Cost per MQL** | Cost to acquire one MQL | Total Spend / MQL Count | $52 | | **MQL → SQL %** | Conversion rate from MQL to SQL | SQLs / MQLs | 30% | | **Pipeline Created** | Total opportunity value from marketing | SUM(opp_value WHERE source='Marketing') | $487,000 | | **ROAS** | Return on ad spend | Revenue / Ad Spend | 3.2x | | **CAC** | Customer acquisition cost | (Marketing Spend + Sales Spend) / New Customers | $52 | ### 10.2 Data Dictionary [Link to full data dictionary with field names, data types, sources] **Example fields**: - `campaign_id` (STRING): Unique campaign identifier - `channel` (STRING): Marketing channel (paid_search, paid_social, email, organic, etc.) - `spend` (FLOAT): Total advertising spend in USD - `impressions` (INTEGER): Number of ad impressions - `clicks` (INTEGER): Number of ad clicks - `conversions` (INTEGER): Number of conversion events (form submissions, purchases, etc.) - `revenue` (FLOAT): Revenue attributed to marketing source in USD ### 10.3 FAQs **Q: Why don't GA4 and CRM conversion numbers match exactly?** A: Small discrepancies (5-10%) are normal due to differences in attribution models, tracking delays, and spam filtering. We alert when discrepancy exceeds 10%. **Q: How often is data refreshed?** A: GA4 and CRM data updates in real-time (<5 min latency). Ad platform data syncs hourly. Data warehouse aggregations run every 15 minutes. **Q: Can I create a custom view for my team?** A: Yes. Users with Editor access can save custom filter combinations and share with their team. Contact Analytics Team for help. **Q: How do I report a data issue?** A: Use the feedback form in the dashboard footer or message #marketing-analytics in Slack. **Q: Can I export this data?** A: Yes. Click the Export button (top-right) to download CSV, PDF, or PNG. Note: Exports respect your access permissions. --- ## Document Control **Version History**: | Version | Date | Author | Changes | |---------|------|--------|---------| | 1.0 | YYYY-MM-DD | [Name] | Initial dashboard specification | | 1.1 | YYYY-MM-DD | [Name] | Added mobile responsive design section | **Approval**: - **Analytics Lead**: [Name, Date] - **Dashboard Designer**: [Name, Date] - **Marketing Leadership**: [Name, Date] - **IT/Security** (if required): [Name, Date] **Dashboard URL**: [Link to live dashboard] **Next Review Date**: [YYYY-MM-DD]