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Level 3 - Reading Event Footprints

Goal: Learn to read event parameters like a “good hunter” (intermediate).

Raw data isn’t “developer shit”—it’s your job.


This level teaches you to read raw event data fluently.

You’ll learn:

  • What an event schema is
  • How to recognize traffic sources from parameters
  • Multi-dimensional filtering to find winners

By the end, you’ll look at JSON event data and instantly know: “This is Facebook campaign X, ad Y, retargeted via SMS.”


Lessons:

  • Lesson 3.1.1: Each event = name + timestamp + user ID + properties + parameters
  • Lesson 3.1.2: Parameters are what let us see attribution
  • Lesson 3.1.3: Exercise - Pull 5 sample events and label them

Based on: Encyclopedia - Event Schema


Module 3.2 - Recognizing Sources from Footprints

Section titled “Module 3.2 - Recognizing Sources from Footprints”

Lessons:

  • Lesson 3.2.1: How Facebook, Google, SMS, Email each “look” in parameters
  • Lesson 3.2.2: Why surface labels lie (e.g., “google ads” but actually SMS retargeting)
  • Lesson 3.2.3: Exercise - Classify events as FB / Google / SMS / Email, identify original vs last touch

Based on: Encyclopedia - Event Schema (Reading Event Footprints) + Encyclopedia - Practical Examples (November 20th Sales Investigation)

Key skill: Look at raw event JSON and determine the TRUE source (not the surface label).


Lessons:

  • Lesson 3.3.1: Filtering by landing page + affid + campaign_id
  • Lesson 3.3.2: Why “discount-01 + affid=1000 + campaign 120… = 44% conversion” is gold
  • Lesson 3.3.3: Exercise - Find a winner combo in your data

Based on: Encyclopedia - Practical Examples (Multi-Dimensional Filtering)

Key skill: Layer filters to isolate high-performing segments (not just single-dimension analysis).

💡 See Real Example: Funnel with landing page breakdown showing segmentation →


Event Footprints:

  • Facebook: utm_source: fb, campaign_id, ad_id, adset_id, affid: 1000, fbp
  • Google: utm_source: google, gclid, g_campaignid
  • SMS: sms_campaign, sms_message_id, original_utm_source
  • Email: source: email_crm, email_id, original_utm_source

Surface Labels Lie:

  • Label: “Google Ads”
  • Parameters: sms_campaign: sms_prospect_nov_20, original_utm_source: google
  • Reality: SMS retargeting of a Google Ads user

Multi-Dimensional Wins:

  • Landing page alone: 5.80% conversion
  • Landing page + affid + campaign: 44.21% conversion
  • 7.6x better by layering filters

After this level, you’ll be able to:

  • Read raw event JSON fluently
  • Identify traffic sources from parameters (not surface labels)
  • Perform multi-dimensional filtering to find campaign winners
  • Spot when parameters reveal hidden retargeting

You’re now a “good hunter”—comfortable with ugly data.


👉 Continue to Level 4: Level 4 - Cross-Validation & Reality Checks

Now you’ll learn to triangulate data across systems to catch lies.