Marketing Analytics

UTM Tracking Setup

UTM Parameter Standartlari

https://example.com/landing?
  utm_source=google           # Trafik kaynagi (google, facebook, newsletter)
  &utm_medium=cpc             # Kanal tipi (cpc, email, social, organic)
  &utm_campaign=spring_2026   # Kampanya adi
  &utm_term=saas+analytics    # Arama terimi (paid search)
  &utm_content=hero_banner    # Reklam varyanti (A/B test)

UTM Naming Convention

Parameter	Format	Ornekler
source	lowercase, platform adi	google, facebook, linkedin, newsletter
medium	lowercase, kanal tipi	cpc, cpm, email, social, organic, referral
campaign	snake_case, tarih dahil	spring_sale_2026, product_launch_q1
term	+ ile ayrilmis	saas+analytics, project+management
content	snake_case, varyant	hero_banner, sidebar_cta, email_v2

UTM Builder (TypeScript)

interface UTMConfig {
  baseUrl: string;
  source: string;
  medium: string;
  campaign: string;
  term?: string;
  content?: string;
}

function buildUTMUrl(config: UTMConfig): string {
  const params = new URLSearchParams();
  params.set("utm_source", config.source.toLowerCase());
  params.set("utm_medium", config.medium.toLowerCase());
  params.set("utm_campaign", config.campaign.toLowerCase().replace(/\s+/g, "_"));
  if (config.term) params.set("utm_term", config.term.toLowerCase());
  if (config.content) params.set("utm_content", config.content.toLowerCase());

  const separator = config.baseUrl.includes("?") ? "&" : "?";
  return `${config.baseUrl}${separator}${params.toString()}`;
}

// UTM parametrelerini parse et ve kaydet
function captureUTM(): UTMParams | null {
  const params = new URLSearchParams(window.location.search);
  const utm: UTMParams = {
    source: params.get("utm_source") || undefined,
    medium: params.get("utm_medium") || undefined,
    campaign: params.get("utm_campaign") || undefined,
    term: params.get("utm_term") || undefined,
    content: params.get("utm_content") || undefined,
  };

  if (utm.source) {
    // First-touch ve last-touch ayri kaydet
    if (!localStorage.getItem("utm_first_touch")) {
      localStorage.setItem("utm_first_touch", JSON.stringify({ ...utm, timestamp: Date.now() }));
    }
    localStorage.setItem("utm_last_touch", JSON.stringify({ ...utm, timestamp: Date.now() }));
    return utm;
  }
  return null;
}

Attribution Modeling

Attribution Modelleri

Model	Aciklama	Ne Zaman Kullan
First Touch	Ilk temas %100 kredi alir	Awareness kampanyalari
Last Touch	Son temas %100 kredi alir	Direct response kampanyalari
Linear	Tum temaslar esit kredi alir	Tum kanallari esit degerlendirme
Time Decay	Son temaslara daha cok kredi	Uzun satis dongusu
U-Shaped	Ilk ve son temas %40, orta %20	Balanced B2B attribution
W-Shaped	Ilk, lead, opportunity %30, geri kalan %10	Full-funnel B2B
Data-Driven	Algoritmik (Markov chain, Shapley)	Yeterli veri varsa (10K+ conversion)

Multi-Touch Attribution Query

-- U-Shaped Attribution
WITH touchpoints AS (
  SELECT
    conversion_id,
    user_id,
    channel,
    touch_timestamp,
    ROW_NUMBER() OVER (PARTITION BY conversion_id ORDER BY touch_timestamp) AS touch_order,
    COUNT(*) OVER (PARTITION BY conversion_id) AS total_touches
  FROM marketing_touches
  WHERE conversion_id IS NOT NULL
),
attributed AS (
  SELECT
    conversion_id,
    channel,
    CASE
      WHEN total_touches = 1 THEN 1.0
      WHEN total_touches = 2 THEN 0.5
      WHEN touch_order = 1 THEN 0.4                            -- first touch
      WHEN touch_order = total_touches THEN 0.4                -- last touch
      ELSE 0.2 / (total_touches - 2)                           -- middle touches
    END AS attribution_weight
  FROM touchpoints
)
SELECT
  channel,
  ROUND(SUM(attribution_weight), 2) AS attributed_conversions,
  ROUND(SUM(attribution_weight * c.revenue), 2) AS attributed_revenue
FROM attributed a
JOIN conversions c ON a.conversion_id = c.id
GROUP BY channel
ORDER BY attributed_revenue DESC;

Markov Chain Attribution

interface TransitionMatrix {
  [fromState: string]: {
    [toState: string]: number;  // probability
  };
}

// Removal effect: Her kanalin conversion'a katki oranini hesapla
function calculateRemovalEffect(
  matrix: TransitionMatrix,
  channels: string[]
): Record<string, number> {
  const baseConversionRate = simulateConversions(matrix, channels);
  const effects: Record<string, number> = {};

  for (const channel of channels) {
    const withoutChannel = channels.filter(c => c !== channel);
    const reducedRate = simulateConversions(matrix, withoutChannel);
    effects[channel] = (baseConversionRate - reducedRate) / baseConversionRate;
  }

  // Normalize to sum to 1
  const total = Object.values(effects).reduce((a, b) => a + b, 0);
  for (const channel of channels) {
    effects[channel] = effects[channel] / total;
  }

  return effects;
}

CAC (Customer Acquisition Cost)

CAC Hesaplama

interface CACMetrics {
  totalMarketingSpend: number;        // Toplam marketing harcamasi
  totalSalesSpend: number;            // Toplam sales harcamasi (maas dahil)
  newCustomers: number;               // Kazanilan musteri sayisi
  period: string;                     // "2026-Q1"
}

function calculateCAC(metrics: CACMetrics): {
  blendedCAC: number;
  paidCAC: number;
  organicCAC: number;
} {
  const totalSpend = metrics.totalMarketingSpend + metrics.totalSalesSpend;
  return {
    blendedCAC: totalSpend / metrics.newCustomers,
    paidCAC: metrics.totalMarketingSpend / (metrics.newCustomers * 0.6),  // %60 paid
    organicCAC: (metrics.totalSalesSpend * 0.3) / (metrics.newCustomers * 0.4),
  };
}

CAC by Channel Query

SELECT
  channel,
  SUM(spend) AS total_spend,
  COUNT(DISTINCT conversion_user_id) AS new_customers,
  ROUND(SUM(spend) / NULLIF(COUNT(DISTINCT conversion_user_id), 0), 2) AS cac,
  ROUND(AVG(first_order_value), 2) AS avg_first_order
FROM (
  SELECT
    a.channel,
    a.spend,
    c.user_id AS conversion_user_id,
    c.revenue AS first_order_value
  FROM ad_spend a
  LEFT JOIN conversions c ON c.attributed_channel = a.channel
    AND c.conversion_date BETWEEN a.date AND a.date + INTERVAL '30 days'
  WHERE a.date >= CURRENT_DATE - INTERVAL '90 days'
) channel_data
GROUP BY channel
ORDER BY cac;

CAC Benchmarks

Industry	Median CAC	Iyi CAC	Target LTV:CAC
SaaS B2B (SMB)	$200-500	< $200	3:1+
SaaS B2B (Enterprise)	$5K-20K	< $5K	5:1+
SaaS B2C	$20-100	< $30	3:1+
E-commerce	$10-50	< $15	3:1+
Fintech	$100-500	< $100	4:1+
Marketplace	$50-200	< $50	3:1+

ROAS (Return on Ad Spend)

ROAS Calculator

function calculateROAS(
  revenue: number,
  adSpend: number
): { roas: number; roasPercentage: number; profitable: boolean } {
  const roas = revenue / adSpend;
  return {
    roas: Math.round(roas * 100) / 100,
    roasPercentage: Math.round(roas * 100),
    profitable: roas > 1,
  };
}

// Hedef ROAS hesapla (break-even icin)
function targetROAS(grossMargin: number): number {
  // Minimum ROAS = 1 / Gross Margin
  // %70 margin -> minimum 1.43 ROAS
  return Math.round((1 / grossMargin) * 100) / 100;
}

ROAS Dashboard Query

SELECT
  campaign_name,
  channel,
  SUM(impressions) AS impressions,
  SUM(clicks) AS clicks,
  ROUND(100.0 * SUM(clicks) / NULLIF(SUM(impressions), 0), 2) AS ctr_pct,
  SUM(spend) AS spend,
  SUM(conversions) AS conversions,
  ROUND(SUM(spend) / NULLIF(SUM(conversions), 0), 2) AS cost_per_conversion,
  SUM(revenue) AS revenue,
  ROUND(SUM(revenue) / NULLIF(SUM(spend), 0), 2) AS roas,
  ROUND(SUM(revenue) - SUM(spend), 2) AS profit
FROM campaign_performance
WHERE date >= CURRENT_DATE - INTERVAL '30 days'
GROUP BY campaign_name, channel
ORDER BY roas DESC;

ROAS Benchmarks

Platform	Ortalama ROAS	Iyi ROAS	Mukemmel ROAS
Google Search	2:1	4:1	8:1+
Google Display	0.5:1	1.5:1	3:1+
Facebook/Instagram	1.5:1	3:1	6:1+
LinkedIn	1:1	2.5:1	5:1+
TikTok	1:1	2:1	4:1+
Email Marketing	10:1	30:1	40:1+

Conversion Tracking

Conversion Event Setup

interface ConversionEvent {
  event_name: string;
  value: number;
  currency: string;
  conversion_type: "micro" | "macro";
  attribution_window_days: number;
}

const conversionEvents: ConversionEvent[] = [
  // Macro conversions (primary goals)
  { event_name: "purchase_completed", value: 0, currency: "USD", conversion_type: "macro", attribution_window_days: 30 },
  { event_name: "subscription_started", value: 0, currency: "USD", conversion_type: "macro", attribution_window_days: 30 },

  // Micro conversions (leading indicators)
  { event_name: "trial_started", value: 0, currency: "USD", conversion_type: "micro", attribution_window_days: 14 },
  { event_name: "demo_requested", value: 50, currency: "USD", conversion_type: "micro", attribution_window_days: 7 },
  { event_name: "email_subscribed", value: 5, currency: "USD", conversion_type: "micro", attribution_window_days: 7 },
];

// Server-side conversion tracking
async function trackConversion(
  event: ConversionEvent,
  userId: string,
  metadata: Record<string, unknown>
): Promise<void> {
  // 1. Internal analytics
  await analytics.track(event.event_name, {
    ...metadata,
    conversion_type: event.conversion_type,
    value: metadata.value || event.value,
  });

  // 2. Facebook Conversions API
  await sendFacebookConversion(event, userId, metadata);

  // 3. Google Ads offline conversion
  await sendGoogleOfflineConversion(event, userId, metadata);
}

Conversion Funnel Query

-- Marketing funnel: Visit -> Lead -> MQL -> SQL -> Customer
SELECT
  'Visit' AS stage, COUNT(DISTINCT session_id) AS count, 100.0 AS pct
FROM sessions WHERE date >= CURRENT_DATE - INTERVAL '30 days'
UNION ALL
SELECT
  'Lead', COUNT(DISTINCT user_id),
  ROUND(100.0 * COUNT(DISTINCT user_id) /
    (SELECT COUNT(DISTINCT session_id) FROM sessions WHERE date >= CURRENT_DATE - INTERVAL '30 days'), 1)
FROM leads WHERE created_at >= CURRENT_DATE - INTERVAL '30 days'
UNION ALL
SELECT
  'MQL', COUNT(DISTINCT user_id),
  ROUND(100.0 * COUNT(DISTINCT user_id) /
    (SELECT COUNT(DISTINCT user_id) FROM leads WHERE created_at >= CURRENT_DATE - INTERVAL '30 days'), 1)
FROM leads WHERE status = 'mql' AND created_at >= CURRENT_DATE - INTERVAL '30 days'
UNION ALL
SELECT
  'SQL', COUNT(DISTINCT user_id),
  ROUND(100.0 * COUNT(DISTINCT user_id) /
    (SELECT COUNT(DISTINCT user_id) FROM leads WHERE status = 'mql' AND created_at >= CURRENT_DATE - INTERVAL '30 days'), 1)
FROM leads WHERE status = 'sql' AND created_at >= CURRENT_DATE - INTERVAL '30 days'
UNION ALL
SELECT
  'Customer', COUNT(DISTINCT user_id),
  ROUND(100.0 * COUNT(DISTINCT user_id) /
    (SELECT COUNT(DISTINCT user_id) FROM leads WHERE status = 'sql' AND created_at >= CURRENT_DATE - INTERVAL '30 days'), 1)
FROM conversions WHERE date >= CURRENT_DATE - INTERVAL '30 days'
ORDER BY
  CASE stage
    WHEN 'Visit' THEN 1 WHEN 'Lead' THEN 2 WHEN 'MQL' THEN 3
    WHEN 'SQL' THEN 4 WHEN 'Customer' THEN 5
  END;

Landing Page Optimization

Key Metrics

Metrik	Formul	Iyi Deger
Bounce Rate	single_page_sessions / total_sessions	< %40
Conversion Rate	conversions / visitors	%3-5 (B2C), %2-3 (B2B)
Time on Page	avg(exit_time - entry_time)	> 60 saniye
Scroll Depth	avg(max_scroll_percentage)	> %60
CTA Click Rate	cta_clicks / visitors	> %5
Form Completion	form_submits / form_starts	> %30

Landing Page A/B Test Template

interface LandingPageTest {
  name: string;
  hypothesis: string;
  element: "headline" | "cta" | "hero_image" | "social_proof" | "pricing" | "layout";
  control: string;
  treatment: string;
  primary_metric: string;
  traffic_split: number;
  duration_days: number;
}

const tests: LandingPageTest[] = [
  {
    name: "headline_benefit_vs_feature",
    hypothesis: "Benefit-focused headline, feature-focused'a gore %15 daha yuksek conversion verir",
    element: "headline",
    control: "AI-Powered Analytics Dashboard",
    treatment: "Get Insights 10x Faster With AI",
    primary_metric: "cta_click_rate",
    traffic_split: 0.5,
    duration_days: 14,
  },
];

Email Marketing Metrics

KPI Dashboard

Metrik	Formul	Iyi Deger	Aksiyonlar
Open Rate	opens / delivered	%20-30	Subject line A/B test
CTR	clicks / delivered	%2-5	CTA ve icerik optimize
CTOR	clicks / opens	%10-15	Icerik kalitesini olc
Unsubscribe Rate	unsubs / delivered	< %0.5	Frekans ve segmentasyon
Bounce Rate	bounces / sent	< %2	Liste temizligi
Conversion Rate	conversions / clicks	%1-5	Landing page optimize
Revenue per Email	total_revenue / delivered	Varies	Segmentasyon iyilestir

Email Performance Query

SELECT
  campaign_name,
  sent_at::date AS send_date,
  COUNT(*) AS sent,
  SUM(CASE WHEN delivered THEN 1 ELSE 0 END) AS delivered,
  SUM(CASE WHEN opened THEN 1 ELSE 0 END) AS opens,
  ROUND(100.0 * SUM(CASE WHEN opened THEN 1 ELSE 0 END) /
    NULLIF(SUM(CASE WHEN delivered THEN 1 ELSE 0 END), 0), 1) AS open_rate,
  SUM(CASE WHEN clicked THEN 1 ELSE 0 END) AS clicks,
  ROUND(100.0 * SUM(CASE WHEN clicked THEN 1 ELSE 0 END) /
    NULLIF(SUM(CASE WHEN delivered THEN 1 ELSE 0 END), 0), 1) AS ctr,
  SUM(CASE WHEN converted THEN 1 ELSE 0 END) AS conversions,
  SUM(revenue) AS total_revenue,
  ROUND(SUM(revenue) / NULLIF(SUM(CASE WHEN delivered THEN 1 ELSE 0 END), 0), 2) AS revenue_per_email
FROM email_campaigns
WHERE sent_at >= CURRENT_DATE - INTERVAL '90 days'
GROUP BY campaign_name, send_date
ORDER BY send_date DESC;

Social Media Analytics

Platform Metrics

Platform	Key Metrics	Engagement Formula
Twitter/X	Impressions, Engagement Rate, Link Clicks	(likes + retweets + replies) / impressions
LinkedIn	Impressions, CTR, Follower Growth	(likes + comments + shares + clicks) / impressions
Instagram	Reach, Saves, Shares	(likes + comments + saves + shares) / followers
TikTok	Views, Watch Time, Shares	(likes + comments + shares) / views
YouTube	Views, Watch Time, CTR	(likes + comments) / views

Social ROI Template

interface SocialROI {
  platform: string;
  totalSpend: number;           // paid + organic (time cost)
  impressions: number;
  engagements: number;
  websiteTraffic: number;
  conversions: number;
  revenue: number;
}

function calculateSocialROI(data: SocialROI): {
  cpm: number;                  // Cost per 1000 impressions
  cpe: number;                  // Cost per engagement
  cpc: number;                  // Cost per click (to website)
  cpa: number;                  // Cost per acquisition
  roi: number;                  // Return on Investment %
} {
  return {
    cpm: (data.totalSpend / data.impressions) * 1000,
    cpe: data.totalSpend / data.engagements,
    cpc: data.totalSpend / data.websiteTraffic,
    cpa: data.totalSpend / data.conversions,
    roi: ((data.revenue - data.totalSpend) / data.totalSpend) * 100,
  };
}

SEO Metrics

Core SEO KPIs

Metrik	Kaynak	Hedef
Organic Traffic	Google Search Console / GA	+10% MoM
Keyword Rankings	Ahrefs / SEMrush	Top 10 icin hedef keyword
Click-Through Rate	Search Console	> %3 ortalama
Domain Authority	Ahrefs / Moz	Rakiplerden yuksek
Backlink Growth	Ahrefs	+5% MoM
Core Web Vitals	PageSpeed Insights	LCP < 2.5s, CLS < 0.1, INP < 200ms
Indexed Pages	Search Console	Sitemap'teki sayfa sayisina yakin
Organic Conversion Rate	GA	> %2

Content Performance Scoring

interface ContentScore {
  url: string;
  organic_traffic_30d: number;
  avg_position: number;
  ctr: number;
  conversions: number;
  backlinks: number;
  word_count: number;
  last_updated: string;
}

function scoreContent(content: ContentScore): {
  score: number;
  action: "keep" | "update" | "consolidate" | "remove";
} {
  let score = 0;

  // Traffic (0-30)
  if (content.organic_traffic_30d > 1000) score += 30;
  else if (content.organic_traffic_30d > 100) score += 20;
  else if (content.organic_traffic_30d > 10) score += 10;

  // Rankings (0-25)
  if (content.avg_position <= 3) score += 25;
  else if (content.avg_position <= 10) score += 15;
  else if (content.avg_position <= 20) score += 5;

  // Conversions (0-25)
  if (content.conversions > 10) score += 25;
  else if (content.conversions > 1) score += 15;
  else if (content.conversions > 0) score += 5;

  // Freshness (0-10)
  const daysSinceUpdate = (Date.now() - new Date(content.last_updated).getTime()) / 86400000;
  if (daysSinceUpdate < 90) score += 10;
  else if (daysSinceUpdate < 180) score += 5;

  // Backlinks (0-10)
  if (content.backlinks > 10) score += 10;
  else if (content.backlinks > 0) score += 5;

  let action: "keep" | "update" | "consolidate" | "remove";
  if (score >= 70) action = "keep";
  else if (score >= 40) action = "update";
  else if (score >= 20) action = "consolidate";
  else action = "remove";

  return { score, action };
}

Marketing Funnel Optimization

Funnel Stage Metrics

TOFU (Awareness)           MOFU (Consideration)        BOFU (Decision)
-------------------        ----------------------      ------------------
Impressions                Email subscribers            Demo requests
Website visitors           Content downloads            Trial signups
Social followers           Webinar attendees            Quote requests
Blog readers               Return visitors              Free trial users
                           Newsletter opens             Pricing page visits

Channel Efficiency Matrix

SELECT
  channel,
  SUM(spend) AS spend,
  COUNT(DISTINCT visitor_id) AS visitors,
  COUNT(DISTINCT lead_id) AS leads,
  COUNT(DISTINCT customer_id) AS customers,
  ROUND(SUM(spend) / NULLIF(COUNT(DISTINCT visitor_id), 0), 2) AS cost_per_visit,
  ROUND(SUM(spend) / NULLIF(COUNT(DISTINCT lead_id), 0), 2) AS cost_per_lead,
  ROUND(SUM(spend) / NULLIF(COUNT(DISTINCT customer_id), 0), 2) AS cac,
  ROUND(100.0 * COUNT(DISTINCT lead_id) / NULLIF(COUNT(DISTINCT visitor_id), 0), 1) AS visit_to_lead_pct,
  ROUND(100.0 * COUNT(DISTINCT customer_id) / NULLIF(COUNT(DISTINCT lead_id), 0), 1) AS lead_to_customer_pct,
  SUM(customer_revenue) AS revenue,
  ROUND(SUM(customer_revenue) / NULLIF(SUM(spend), 0), 2) AS roas
FROM marketing_data
WHERE date >= CURRENT_DATE - INTERVAL '90 days'
GROUP BY channel
ORDER BY roas DESC;

Anti-Patterns

Anti-Pattern	Dogru Yol
UTM'siz kampanya	Her kampanyada tutarli UTM kullan
Sadece last-touch attribution	Multi-touch modelleme yap
CAC'i toplam baz al	Kanal bazli CAC hesapla
ROAS'i revenue ile hesapla	Profit-based ROAS (POAS) kullan
Vanity metrics raporu (impressions)	Conversion-focused metriklere odaklan
Email herkese ayni icerik	Segmentasyon + kisisellesetirme
SEO sadece keyword	Technical SEO + Content + Backlink
Kanal silolari	Cross-channel attribution