Looker Studio (Google Data Studio)

Expert-level guidance for Looker Studio — building dashboards, connecting data sources, designing visualizations, and creating automated marketing reports.

Install

git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/looker-studio ~/.claude/skills/

Core Capabilities

Dashboard Design

• Layout and visual hierarchy best practices
• Executive summary vs detailed operational dashboards
• Mobile-responsive report design
• Interactive controls: date range selectors, filters, drill-downs
• Consistent styling with themes and color palettes

Data Sources & Connectors

• Native (free): Google Analytics 4, Google Ads, Google Sheets, BigQuery, Search Console, YouTube Analytics
• Partner connectors: Facebook Ads, Microsoft Ads, LinkedIn Ads, HubSpot, Salesforce, Shopify, Klaviyo, Semrush
• Community connectors: Hundreds of third-party sources
• Data blending: Join multiple sources on shared dimensions
• Custom queries: BigQuery SQL, Google Sheets formulas as data sources

Calculated Fields & Metrics

• Regex-based field creation (REGEXP_MATCH, REGEXP_REPLACE, REGEXP_EXTRACT)
• CASE statements for custom groupings and bucketing
• Date functions for period-over-period comparisons
• Aggregation (SUM, AVG, COUNT_DISTINCT, MEDIAN)
• Blended field calculations across sources

Formula Syntax Rules

• No comments allowed — Looker Studio formulas do not support --, //, or /* */ style comments. Never include comments in formulas. Add context in the field description instead.
• No inline flags in simple cases — prefer CONTAINS_TEXT(), LOWER(), or exact match over regex when possible
• RE2 regex engine — supports (?i) for case-insensitive, but does NOT support lookaheads/lookbehinds
• String escaping — use \\ for literal backslash in regex patterns within string literals (e.g., "\\s" for whitespace, "\\|" for literal pipe)

Report Automation

• Scheduled email delivery (PDF snapshots)
• Embedded reports in websites and portals
• Template reports for client scaling
• Data freshness monitoring

Dashboard Templates by Use Case

Marketing Performance Dashboard

Page 1: Executive Summary
|- KPI scorecards (Revenue, ROAS, CPA, Spend, Conversions)
|- Period-over-period trend lines
|- Channel performance table (sortable)
|- Budget pacing gauge chart

Page 2: Paid Media Deep-Dive
|- Google Ads performance (campaign breakdown)
|- Meta Ads performance (campaign breakdown)
|- Microsoft Ads performance
|- Cross-channel spend allocation (pie/donut)
|- CPA trend by channel (combo chart)

Page 3: SEO & Organic
|- Google Search Console: impressions, clicks, CTR, position
|- Top queries table
|- Page-level performance
|- Organic landing page engagement (from GA4)

Page 4: Email & CRM
|- Email campaign metrics (opens, clicks, revenue)
|- List growth trend
|- Flow/automation revenue
|- Subscriber engagement tiers

Page 5: Conversion Funnel
|- Funnel visualization (awareness -> consideration -> conversion)
|- Landing page performance table
|- Device breakdown
|- Geographic heatmap

E-commerce Dashboard

Page 1: Revenue Overview
|- Revenue, Orders, AOV, Conversion Rate scorecards
|- Revenue trend (daily/weekly)
|- Revenue by channel
|- Top products table

Page 2: Customer Acquisition
|- New vs returning customer revenue
|- CAC by channel
|- LTV:CAC ratio
|- First-order source attribution

SEO Dashboard

Page 1: Organic Performance
|- Total clicks, impressions, CTR, avg position
|- Trend lines (90-day)
|- Top 20 queries (with position change)
|- Top landing pages
|- Device + country breakdown

Key Visualization Guidelines

Workflow: Build a Dashboard

When asked to create a Looker Studio dashboard:

1. Define Purpose — Who views it? How often? What decisions does it inform?
2. Identify Data Sources — Which platforms/connectors needed? Any blending?
3. Design KPI Framework — Primary metrics, secondary metrics, diagnostic metrics
4. Plan Layout — Page structure, visual hierarchy, interactivity
5. Create Calculated Fields — Custom metrics, CASE groupings, regex transformations
6. Build Visualizations — Chart types matched to data types, consistent formatting
7. Add Controls — Date range, filters, drill-down parameters
8. Style & Polish — Theme, colors, fonts, logos, white space
9. Test & Validate — Cross-reference numbers with source platforms
10. Set Up Delivery — Scheduled emails, sharing permissions, embedding

Calculated Field Recipes

Period-over-Period Comparison

CASE
  WHEN date_field >= DATE_DIFF(TODAY(), INTERVAL 30 DAY) THEN "Current Period"
  WHEN date_field >= DATE_DIFF(TODAY(), INTERVAL 60 DAY) THEN "Previous Period"
  ELSE "Older"
END

Channel Grouping (Custom)

CASE
  WHEN REGEXP_MATCH(source_medium, "google.*cpc|google.*paid") THEN "Google Ads"
  WHEN REGEXP_MATCH(source_medium, "facebook|fb|meta|instagram") THEN "Meta Ads"
  WHEN REGEXP_MATCH(source_medium, "bing.*cpc|microsoft") THEN "Microsoft Ads"
  WHEN REGEXP_MATCH(source_medium, "email|klaviyo|braze") THEN "Email"
  WHEN source_medium = "organic" THEN "Organic Search"
  WHEN REGEXP_MATCH(source_medium, "social") THEN "Organic Social"
  ELSE "Other"
END

ROAS Calculation

SUM(revenue) / SUM(cost)

How to Use This Skill

Ask me questions like:

• "Build a marketing performance dashboard in Looker Studio"
• "How do I connect Facebook Ads data to Looker Studio?"
• "Create a calculated field for custom channel grouping"
• "Design an executive summary page with KPI scorecards"
• "How do I blend Google Ads and GA4 data?"
• "Build an SEO dashboard with Search Console data"
• "What's the best way to show period-over-period comparisons?"
• "Help me set up automated email reports for my client"

For detailed Looker Studio function reference, connector setup guides, and advanced techniques, see REFERENCE.md.

DTC Dashboard Recipes

Dashboard templates designed for DTC e-commerce teams running Klaviyo + Shopify + GA4.

1. CRM Performance Dashboard

Track email and SMS marketing effectiveness with Klaviyo data.

Page 1: Email & SMS Overview
|- Scorecards: Total Revenue, Flow Revenue %, Campaign Revenue %, List Size
|- Revenue trend: flows vs campaigns over time (area chart)
|- Channel split: email vs SMS revenue (stacked bar)
|- Engagement tiers donut: Active / Warm / At-Risk / Lapsed

Page 2: Flow Performance
|- Flow revenue table (sortable by revenue, click rate)
|- Welcome Series funnel (sent -> opened -> clicked -> converted)
|- Abandoned Cart recovery rate trend
|- Flow-over-flow comparison (combo chart)

Page 3: Campaign Performance
|- Campaign table: send date, subject, open rate, click rate, revenue
|- A/B test results (winner highlighting)
|- Send time heatmap (day of week x hour)
|- Unsubscribe rate trend

Data source: Google Sheets (fed by data_pipeline.py --action sync-klaviyo)

2. Lifecycle Marketing Dashboard

Map flow performance across the customer journey.

Page 1: Journey Overview
|- Stage funnel: Prospect -> New Customer -> Active -> VIP -> At-Risk -> Lapsed
|- Revenue by stage (horizontal bar)
|- Stage transition rates

Page 2: Stage Deep-Dive
|- Filter control: select lifecycle stage
|- Flow performance for selected stage
|- C