Why I Switched to Looker Studio - Read the blog to know more

Why I Switched to Looker Studio (And Why Excel Was Killing Us)

I was running a small agency with eight clients. Each wanted weekly reports. My team was spending 20+ hours a week just moving data around. The breaking point came when a client called asking about their "amazing" 15x ROAS, and I realized we'd accidentally included their email marketing revenue in the Google Ads report.

The old process looked like this:

• Log into Google Ads → export data → paste into Excel

• Log into Facebook → export data → paste into different tab

• Log into GA4 → export data → try to make it match the other platforms

• Spend 2 hours formatting and making charts

• Email PDF to client

• Client emails back with questions about why numbers don't match last week

What I needed: One place where all the data lived and updated automatically.

Setting Up Your First Automated Dashboard (The Right Way)

Week 1: Start Simple - Just Google Ads

Don't try to build everything at once. I learned this the hard way.

Step 1: Connect Google Ads

• Open Looker Studio

• Click "Create" → "Data Source"

• Select "Google Ads"

• Choose your account and campaigns

Step 2: Build Your Core Metrics Table Create a simple table with these columns:

• Campaign Name

• Impressions

• Clicks

• Cost

• Conversions

• Cost per Conversion

Why this works: Your client can immediately see which campaigns are spending money and which are getting results.

Pro tip: Add a calculated field for Click-Through Rate right away:

Clicks / Impressions

Format it as a percentage. Clients love CTR because it's easy to understand.

Week 2: Add Date Controls and Comparison

The date range selector is crucial. Put it at the top of your dashboard. Make the default "Last 7 days" because that's what most people want to see first.

Add comparison periods:

• This week vs last week

• This month vs last month

• Year over year (if you have the data)

Real example: I have a client who checks their dashboard every Tuesday morning. They want to see how Monday performed vs the previous Monday. The comparison feature makes this instant.

Week 3: Layer in GA4 Data

This is where it gets tricky. GA4 and Google Ads count things differently.

What I include from GA4:

• Sessions (not users - sessions make more sense for marketing)

• Goal completions

• Revenue (if e-commerce tracking is set up)

• Bounce rate by traffic source

The challenge: GA4 sessions will never match Google Ads clicks exactly. I solve this by putting them in separate sections with a text box explaining why they're different.

Text I actually use: "Google Ads clicks = people who clicked your ad. GA4 sessions = visits to your website that lasted more than 10 seconds. The numbers won't match, and that's normal."

The Dashboard Layouts That Actually Work

Layout 1: The Executive Summary (For People Who Don't Have Time)

Top section: Big numbers in scorecards

• Total Spend This Month

• Total Conversions This Month

• Cost Per Conversion

• Return on Ad Spend (if you have revenue data)

Middle section: Simple line charts showing trends

• Daily spend and conversions for last 30 days

• Week-over-week performance

Bottom section: Campaign breakdown table

• Just the essential metrics

• Sorted by spend (highest first)

Why this works: Executives can get the full picture in 30 seconds.

Layout 2: The Campaign Manager View (For Daily Optimization)

Left side: Filters

• Campaign type

• Date range

• Device type

• Geographic location

Center: Detailed performance table with these columns:

• Campaign Name

• Status (Active/Paused)

• Budget vs Actual Spend

• Impressions, Clicks, CTR

• Conversions, CPA

• Quality Score (for Google Ads)

Right side: Charts showing:

• Hour-of-day performance

• Day-of-week patterns

• Device performance breakdown

The secret: Add conditional formatting. If CPA goes above your target, the cell turns red. If it's under target, it turns green.

Automation Features That Save Actual Time

Email Delivery Setup

Here's how I set up automated emails:

• Go to "Share" → "Schedule email delivery"

• Set frequency: Weekly, every Monday at 7 AM

• Recipients: Client and your team

• Subject: "Weekly Performance Report - [Date]"

• Include message: "Your automated report is attached. Reply with questions."

Why Monday at 7 AM: Clients see their weekend performance first thing Monday morning. Sets the tone for the week.

Data Refresh Timing

What refreshes when:

• Google Ads: Every 4 hours

• GA4: Once daily (usually overnight)

• Facebook Ads: Every 6 hours

Important: Tell clients about the delay. I add a text box: "Data is current as of 4 hours ago."

Alert System Using Conditional Formatting

Set up visual alerts for:

• CPA increase of 25% or more (red background)

• Conversion rate drop of 30% or more (red text)

• ROAS above target (green background)

• Daily budget exceeded (yellow highlight)

How to set this up:

• Select your metric field

• Go to "Style" → "Conditional Formatting"

• Set your rules with colors

Real Examples from Client Dashboards

E-commerce Client Dashboard

Challenge: They sell seasonal products. Performance swings wildly based on weather and holidays.

Solution: Added year-over-year comparison charts and weather data context.

Specific metrics I track:

• Revenue per session (from GA4)

• Average order value (calculated field)

• Return customer rate

• Cart abandonment rate

Calculated field example:

Revenue per Session = Total Revenue / Sessions

Result: Client can see if low conversion days are due to traffic quality or external factors.

Lead Generation Client Dashboard

Challenge: They have a long sales cycle. Leads from Google Ads might not close for 6 months.

Solution: Connected their CRM (HubSpot) to track lead-to-customer conversion.

What I track:

• Marketing Qualified Leads (MQLs)

• Sales Qualified Leads (SQLs)

• Closed Won deals

• Time from click to close

The game-changer: I can show which campaigns generate leads that actually become customers, not just which campaigns generate the most leads.

Mistakes I Made (So You Don't Have To)

Mistake 1: Too Many Metrics

My first dashboard had 47 different charts. Nobody looked at it.

Fix: Limit to 8-10 key metrics per dashboard. If you need more detail, create a second dashboard.

Mistake 2: Not Testing Mobile View

Half my clients check dashboards on their phones.

Fix: Always preview on mobile before sharing. Reorganize if charts don't display well.

Mistake 3: Ignoring Data Discrepancies

I spent weeks trying to make Google Ads and GA4 numbers match perfectly. They never will.

Fix: Explain why numbers are different instead of trying to force them to match.

Advanced Techniques That Impress Clients

Custom Attribution Windows

Problem: Google Ads uses 30-day attribution, Facebook uses 7-day, GA4 uses 90-day.

Solution: Create calculated fields that normalize everything to the same attribution window.

Cohort Analysis for Campaigns

What it shows: How campaigns perform over time, not just immediately.

Example: Track how many people from a specific campaign convert in weeks 1, 2, 3, and 4 after clicking.

Competitive Intelligence Integration

If you have access to competitor data:

• Impression share trends

• Average position changes

• Search impression share loss due to budget

The ROI Math on This Investment

Time to build initial dashboard: 12 hours Time to build advanced features: Additional 8 hours Weekly time savings: 6 hours per client Break-even point: After 3.5 weeks

For 8 clients:

• Old way: 48 hours per week on reporting

• New way: 4 hours per week reviewing automated reports

• Annual time savings: 2,288 hours

What I did with the extra time: Took on 6 more clients without hiring additional staff.

Getting Started Tomorrow

Day 1: Set up Looker Studio account and connect one data source (start with Google Ads) Day 2: Build basic metrics table and add date controls Day 3: Create simple line charts for trend analysis Day 4: Add conditional formatting for performance alerts Day 5: Set up automated email delivery

Week 2: Add second data source (GA4 or Facebook) Week 3: Build client-specific dashboards Week 4: Train your team and refine based on feedback