Traffic sources

Overview

Traffic sources are the origin points where visitors come from. Knowing them helps identify which channels deliver value and where to spend.

Types

Visual overview

graph TD
    A[Website Traffic] --> B[Direct]
    A --> C[Organic Search]
    A --> D[Paid Search]
    A --> E[Social Media]
    A --> F[Referral]
    A --> G[Email]

    B --> B1[Bookmarks]
    B --> B2[Typed URL]

    C --> C1[Google]
    C --> C2[Bing]
    C --> C3[Other Search Engines]

    D --> D1[Google Ads]
    D --> D2[Bing Ads]
    D --> D3[Shopping Ads]

    E --> E1[Facebook]
    E --> E2[Twitter/X]
    E --> E3[LinkedIn]
    E --> E4[Instagram]

    F --> F1[Partner Sites]
    F --> F2[Blogs]
    F --> F3[News Sites]

    G --> G1[Newsletters]
    G --> G2[Promotional]
    G --> G3[Transactional]

Distribution example

pie title Traffic Source Distribution
    "Organic Search" : 40
    "Direct" : 25
    "Paid Search" : 15
    "Social Media" : 10
    "Referral" : 7
    "Email" : 3

Traffic flow

@startuml
!theme plain

actor User
participant "Search Engine" as SE
participant "Social Media" as SM
participant "Email Campaign" as EC
participant "Your Website" as WS
database "Analytics" as AN

User -> SE: Search Query
SE -> WS: Organic Traffic
WS -> AN: Log Visit (source=organic)

User -> SM: Click Ad/Post
SM -> WS: Social Traffic  
WS -> AN: Log Visit (source=social)

User -> EC: Open Email
EC -> User: Click Link
User -> WS: Email Traffic
WS -> AN: Log Visit (source=email)

note over AN: Track conversions\nby traffic source
@enduml

Customer journey

journey
    title Customer Journey by Traffic Source
    section Awareness
      Search Engine: 5: User
      Social Media Ad: 4: User
      Blog Reference: 3: User
    section Consideration
      Website Visit: 5: User
      Content Reading: 4: User
      Product Browse: 4: User
    section Decision
      Add to Cart: 3: User
      Checkout: 2: User
      Purchase: 5: User
    section Retention
      Email Follow-up: 4: User
      Return Visit: 5: User

Performance matrix

quadrantChart
    title Traffic Source Performance Matrix
    x-axis Low Traffic Volume --> High Traffic Volume
    y-axis Low Conversion Rate --> High Conversion Rate
    quadrant-1 High Volume, High Conversion
    quadrant-2 Low Volume, High Conversion  
    quadrant-3 Low Volume, Low Conversion
    quadrant-4 High Volume, Low Conversion
    Organic Search: [0.7, 0.8]
    Paid Search: [0.5, 0.7]
    Direct: [0.6, 0.9]
    Social Media: [0.4, 0.3]
    Email: [0.3, 0.85]
    Referral: [0.35, 0.6]

Attribution comparison

digraph G {
    rankdir=LR;
    node [shape=box, style="rounded,filled", fillcolor=lightblue];

    subgraph cluster_0 {
        label="First Touch Attribution";
        style=filled;
        color=lightgrey;
        "Facebook Ad" -> "100% Credit" [label="First Touch"];
    }

    subgraph cluster_1 {
        label="Last Touch Attribution";
        style=filled;
        color=lightgrey;
        "Email Campaign" -> "100% Credit " [label="Last Touch"];
    }

    subgraph cluster_2 {
        label="Linear Attribution";
        style=filled;
        color=lightgrey;
        "Facebook Ad " -> "33.3%" [label="Equal"];
        "Organic Search" -> "33.3%" [label="Equal"];
        "Email Campaign " -> "33.3%" [label="Equal"];
    }
}

Key metrics by source

Source	Avg session duration	Bounce rate	Conversion rate
Direct	3:45	35%	4.2%
Organic Search	2:30	45%	3.8%
Paid Search	2:15	50%	3.5%
Social Media	1:45	60%	2.1%
Email	4:20	25%	5.6%
Referral	2:50	40%	3.2%

Best practices

Diversify sources: don't rely on one channel
Track UTMs: consistent tagging
Watch quality: focus on engagement, not just volume
Optimize per source: tailor landing pages
Review weekly: regular analysis

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