Data Analysis for Marketing Campaigns: Measure What Matters

You're running marketing campaigns.

Facebook ads. Google ads. Email sequences. Social media posts. Influencer partnerships.

Money is going out. But is it working?

"We got 10,000 impressions!"

Great. Did anyone buy anything?

If you can't answer that question with confidence, you're flying blind.

The Problem with Marketing Data

Marketing generates more data than almost any other business function.

Every platform gives you:

• Impressions
• Clicks
• Engagement
• Reach
• Followers
• Opens
• CTR
• CPM
• CPC
• ROAS
• ... and 47 other metrics

The result? You're drowning in data but starving for insights.

You know something is working (revenue is coming in). But you don't know what.

The Only Marketing Metrics That Matter

Let's cut through the noise.

1. Customer Acquisition Cost (CAC)

What it is: How much you spend to get one customer

Formula: Total Marketing Spend ÷ New Customers Acquired

Example:

• Ad spend: $5,000
• New customers: 100
• CAC: $50

Why it matters: Tells you if your growth is profitable

What's good: Depends on your customer lifetime value (next metric)

2. Customer Lifetime Value (LTV)

What it is: Total revenue from one customer over their lifetime

Formula: Average Order Value × Average Orders per Customer

Example:

• AOV: $75
• Orders per customer: 3
• LTV: $225

Why it matters: Tells you how much you can spend to acquire a customer

The rule: LTV should be at least 3x CAC

3. Return on Ad Spend (ROAS)

What it is: Revenue generated per dollar spent on ads

Formula: Revenue from Ads ÷ Ad Spend

Example:

• Revenue from ads: $15,000
• Ad spend: $5,000
• ROAS: 3x (or 300%)

Why it matters: Direct measure of ad efficiency

What's good:

• Below 1x: Losing money
• 1-2x: Break even (depending on margins)
• 2-4x: Healthy
• 4x+: Excellent

4. Conversion Rate

What it is: Percentage of visitors who become customers

Formula: Customers ÷ Visitors × 100

Example:

• Visitors: 5,000
• Customers: 150
• Conversion rate: 3%

Why it matters: Shows how effective your funnel is

What's good:

• Ecommerce: 2-3% average, 5%+ excellent
• B2B: 1-2% average
• Landing pages: 5-15%

5. Revenue by Channel

What it is: How much money each marketing channel generates

Why it matters: Shows where to invest more (and where to cut)

Track:

• Organic search
• Paid search
• Social media (organic)
• Paid social
• Email
• Referral
• Direct

How to Analyze Campaign Performance

Step 1: Define Your Goal

Before looking at data, ask: What was this campaign supposed to do?

Awareness campaigns:

• Goal: Reach, impressions
• Success = more people know about you

Traffic campaigns:

• Goal: Website visitors
• Success = more people visit your site

Conversion campaigns:

• Goal: Sales, signups, leads
• Success = more customers

Different goals = different metrics.

Step 2: Track the Right Data

For every campaign, track:

• Spend (how much went in)
• Results (leads, sales, signups)
• Revenue (if applicable)
• Time period

Calculate:

• Cost per result (Spend ÷ Results)
• ROAS (Revenue ÷ Spend)
• Conversion rate (Results ÷ Visitors)

Step 3: Compare Performance

Compare campaigns to each other:

• Which has lowest cost per result?
• Which has highest ROAS?
• Which is scalable?

Compare to benchmarks:

• Industry averages
• Your historical performance
• Your targets

Compare over time:

• Is performance improving or declining?
• Are costs going up or down?

Step 4: Find the Winners and Losers

Winners (scale these):

• High ROAS
• Low CAC
• Consistent performance

Losers (cut these):

• Negative ROAS
• High CAC
• Declining performance

Experiments (test more):

• New channels
• New audiences
• New creative

Step 5: Reallocate Budget

Based on your analysis:

• Put more money into winners
• Cut losers immediately
• Keep a test budget for experiments

Simple. But most businesses don't do it.

Analyzing Different Campaign Types

Paid Ads (Facebook, Google, etc.)

Key metrics:

• ROAS
• Cost per purchase
• CTR (for optimization, not success)
• Frequency (ad fatigue indicator)

What to analyze:

• Which ad creative performs best?
• Which audience converts best?
• What's the optimal budget?
• When should you refresh creative?

Common mistake: Optimizing for clicks instead of conversions

Email Marketing

Key metrics:

• Revenue per email
• Conversion rate
• Revenue per subscriber
• List growth rate

What to analyze:

• Which emails drive most revenue?
• What subject lines get opened AND convert?
• What's the best send time?
• Which segments perform best?

Common mistake: Focusing on open rates (vanity) instead of revenue (reality)

Social Media

Key metrics:

• Traffic to website
• Conversions from social
• Revenue attributed to social
• Engagement that leads to action

What to analyze:

• Which posts drive traffic?
• Which platforms convert?
• What content type works best?
• Is organic reach worth the effort?

Common mistake: Chasing followers and likes instead of revenue

Content Marketing / SEO

Key metrics:

• Organic traffic
• Conversions from organic
• Revenue from organic
• Ranking positions

What to analyze:

• Which pages drive most conversions?
• What keywords bring buyers (not just browsers)?
• What's the ROI on content investment?

Common mistake: Measuring traffic instead of revenue

Building a Marketing Dashboard

The One-Page View

This Month Summary:

• Total marketing spend: $X
• Total revenue from marketing: $X
• Overall ROAS: X
• New customers acquired: X
• CAC: $X

By Channel:

• Paid search: Spend, Revenue, ROAS
• Paid social: Spend, Revenue, ROAS
• Email: Campaigns sent, Revenue
• Organic: Traffic, Conversions

Trends:

• CAC trend (3 months)
• ROAS trend (3 months)
• Revenue by channel trend

Actions:

• What to scale
• What to cut
• What to test

Review Frequency

Weekly:

• Check ad spend vs. budget
• Monitor ROAS
• Pause underperformers

Monthly:

• Full channel analysis
• CAC and LTV review
• Budget reallocation

Quarterly:

• Strategic review
• New channel evaluation
• Goal setting

Common Marketing Analysis Mistakes

Mistake 1: Last-Click Attribution Only

Problem: Giving all credit to the last touchpoint

Reality: Customers often see multiple touchpoints:

1. See Facebook ad
2. Google your brand
3. Read blog post
4. Get retargeted
5. Buy from email

Solution: Look at assisted conversions, not just last-click

Mistake 2: Short Time Windows

Problem: Judging campaigns after 3 days

Reality: B2B sales can take months. Even B2C needs 1-2 weeks.

Solution: Give campaigns enough time to mature before judging

Mistake 3: Ignoring Margins

Problem: Celebrating 2x ROAS on a product with 30% margin

Reality: After product cost, you're barely breaking even

Solution: Calculate ROAS targets based on actual profit margins

Mistake 4: No Control Groups

Problem: "We ran ads and sales went up!"

Reality: Maybe sales would have gone up anyway (seasonality, trend)

Solution: When possible, use holdout groups or geographic tests

Mistake 5: Vanity Metrics

Problem: Reporting impressions and clicks to feel good

Reality: Your business runs on revenue, not impressions

Solution: Always tie back to revenue or clear business outcomes

Getting Started This Week

Day 1: Audit Your Current Tracking

• What are you measuring?
• What's missing?
• Can you tie campaigns to revenue?

Day 2: Calculate Current CAC

• Total marketing spend (last month)
• New customers (last month)
• CAC = spend ÷ customers

Day 3: Calculate ROAS by Channel

For each channel:

• What did you spend?
• What revenue did it generate?
• What's the ROAS?

Day 4: Identify Winners and Losers

• Which channel has best ROAS?
• Which has worst?
• Where should you reallocate?

Day 5: Make One Change

• Increase budget on best performer
• Cut budget on worst performer
• Track the impact

Key Takeaways

1. Focus on revenue metrics — CAC, LTV, ROAS, not impressions
2. Compare channels — put money where it works
3. Track over time — trends matter more than snapshots
4. Cut losers fast — don't throw good money after bad
5. Test constantly — small experiments find big wins
6. Tie everything to revenue — vanity metrics don't pay bills

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