{"id":1803,"date":"2026-07-20T17:00:00","date_gmt":"2026-07-20T22:00:00","guid":{"rendered":"https:\/\/tolinku.com\/blog\/?p=1803"},"modified":"2026-03-07T03:37:23","modified_gmt":"2026-03-07T08:37:23","slug":"analytics-for-marketing-teams","status":"publish","type":"post","link":"https:\/\/tolinku.com\/blog\/analytics-for-marketing-teams\/","title":{"rendered":"Deep Link Analytics for Marketing Teams"},"content":{"rendered":"\n

Marketing teams need answers, not data. "How many people clicked the deep link?" is not a useful metric on its own. "The email campaign drove 2,050 conversions at $4.88 CPA, outperforming paid social by 3x" is actionable. Deep link analytics give marketing teams the data to calculate ROI, compare channels, and allocate budget.<\/p>\n\n\n\n

This guide covers deep link analytics for marketing teams. For product-focused analytics, see deep link analytics for product teams<\/a>. For campaign reporting templates, see campaign performance reports for deep links<\/a>.<\/p>\n\n\n\n

\"Tolinku\nThe analytics dashboard with date range selector, filters, charts, and breakdowns.<\/em><\/p>\n\n\n\n

Metrics Marketing Teams Need<\/h2>\n\n\n\n

The Marketing Funnel<\/h3>\n\n\n\n

Deep links create a measurable funnel from impression to conversion:<\/p>\n\n\n\n

\n\n\n\n\n\n\n\n
Stage<\/th>\nMetric<\/th>\nWhat It Tells You<\/th>\n<\/tr>\n<\/thead>\n
Awareness<\/td>\nImpressions<\/td>\nHow many people saw the link<\/td>\n<\/tr>\n
Interest<\/td>\nClick-through rate (CTR)<\/td>\nHow compelling the message is<\/td>\n<\/tr>\n
Engagement<\/td>\nApp open rate<\/td>\nHow well the deep link works technically<\/td>\n<\/tr>\n
Action<\/td>\nConversion rate<\/td>\nHow relevant the landing experience is<\/td>\n<\/tr>\n
Value<\/td>\nRevenue per click<\/td>\nHow much each click is worth<\/td>\n<\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n

Key Metrics by Channel<\/h3>\n\n\n\n
\n\n\n\n\n\n\n\n\n
Channel<\/th>\nPrimary Metric<\/th>\nSecondary Metric<\/th>\nOptimization Target<\/th>\n<\/tr>\n<\/thead>\n
Email<\/td>\nCTR<\/td>\nConversion rate<\/td>\nSubject line, CTA copy<\/td>\n<\/tr>\n
Push<\/td>\nTap rate<\/td>\nAction completion<\/td>\nTiming, personalization<\/td>\n<\/tr>\n
Paid social<\/td>\nCost per install (CPI)<\/td>\nROAS<\/td>\nAudience targeting, creative<\/td>\n<\/tr>\n
Organic social<\/td>\nShares<\/td>\nViral coefficient<\/td>\nContent quality, share mechanics<\/td>\n<\/tr>\n
QR code<\/td>\nScan rate<\/td>\nConversion rate<\/td>\nPlacement, CTA on physical media<\/td>\n<\/tr>\n
SMS<\/td>\nCTR<\/td>\nConversion rate<\/td>\nMessage copy, timing<\/td>\n<\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n

Campaign Dashboard<\/h2>\n\n\n\n

Essential Dashboard Components<\/h3>\n\n\n\n

A marketing team dashboard should answer: "How are our campaigns performing?"<\/p>\n\n\n\n

1. Campaign Summary Cards<\/strong><\/p>\n\n\n\n

\n\n\n\n\n\n\n
Campaign<\/th>\nStatus<\/th>\nClicks<\/th>\nConversions<\/th>\nCPA<\/th>\nROAS<\/th>\n<\/tr>\n<\/thead>\n
Summer Sale<\/td>\nActive<\/td>\n12,000<\/td>\n1,440<\/td>\n$6.94<\/td>\n245%<\/td>\n<\/tr>\n
Referral Program<\/td>\nActive<\/td>\n5,200<\/td>\n936<\/td>\n$0<\/td>\nN\/A<\/td>\n<\/tr>\n
Re-engagement<\/td>\nActive<\/td>\n8,500<\/td>\n850<\/td>\n$8.24<\/td>\n180%<\/td>\n<\/tr>\n
Back to School<\/td>\nScheduled<\/td>\n0<\/td>\n0<\/td>\n–<\/td>\n–<\/td>\n<\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n

2. Channel Comparison<\/strong><\/p>\n\n\n\n

SELECT\n  source AS channel,\n  COUNT(*) AS clicks,\n  SUM(CASE WHEN outcome = 'app_opened' THEN 1 ELSE 0 END) AS app_opens,\n  ROUND(SUM(CASE WHEN outcome = 'app_opened' THEN 1 ELSE 0 END)::DECIMAL \/ COUNT(*) * 100, 1) AS open_rate,\n  SUM(CASE WHEN converted THEN 1 ELSE 0 END) AS conversions,\n  ROUND(SUM(CASE WHEN converted THEN 1 ELSE 0 END)::DECIMAL \/\n    NULLIF(SUM(CASE WHEN outcome = 'app_opened' THEN 1 ELSE 0 END), 0) * 100, 1) AS conv_rate,\n  ROUND(SUM(spend)::DECIMAL \/ NULLIF(SUM(CASE WHEN converted THEN 1 ELSE 0 END), 0), 2) AS cpa,\n  ROUND(SUM(revenue)::DECIMAL \/ NULLIF(SUM(spend), 0) * 100, 0) AS roas_pct\nFROM campaign_performance\nWHERE campaign = 'summer-sale'\nGROUP BY source\nORDER BY conversions DESC;\n<\/code><\/pre>\n\n\n\n
3. Daily Trend Line<\/strong><\/p>\n\n\n\n
Track clicks, conversions, and spend over time to spot trends and anomalies. A sudden drop in clicks from email may mean deliverability issues. A spike in paid social clicks without a corresponding conversion spike means targeting is off.<\/p>\n\n\n\n
Channel ROI Analysis<\/h2>\n\n\n\n
Calculating ROAS by Channel<\/h3>\n\n\n\n
Return on ad spend tells you which channels are profitable:<\/p>\n\n\n\n
SELECT\n  source,\n  medium,\n  SUM(spend) AS total_spend,\n  SUM(revenue) AS total_revenue,\n  SUM(CASE WHEN converted THEN 1 ELSE 0 END) AS conversions,\n  ROUND(SUM(revenue)::DECIMAL \/ NULLIF(SUM(spend), 0) * 100, 0) AS roas_pct,\n  ROUND(SUM(spend)::DECIMAL \/ NULLIF(SUM(CASE WHEN converted THEN 1 ELSE 0 END), 0), 2) AS cpa\nFROM campaign_performance\nWHERE timestamp >= '2026-07-01'\nGROUP BY source, medium\nORDER BY roas_pct DESC;\n<\/code><\/pre>\n\n\n\n
\n\n\n\n\n\n\n\n
Channel<\/th>\nMedium<\/th>\nSpend<\/th>\nRevenue<\/th>\nConversions<\/th>\nROAS<\/th>\nCPA<\/th>\n<\/tr>\n<\/thead>\n
Email<\/td>\nNewsletter<\/td>\n$2,000<\/td>\n$8,200<\/td>\n410<\/td>\n410%<\/td>\n$4.88<\/td>\n<\/tr>\n
Push<\/td>\nNotification<\/td>\n$500<\/td>\n$1,750<\/td>\n175<\/td>\n350%<\/td>\n$2.86<\/td>\n<\/tr>\n
QR<\/td>\nPrint<\/td>\n$1,500<\/td>\n$3,600<\/td>\n120<\/td>\n240%<\/td>\n$12.50<\/td>\n<\/tr>\n
Paid<\/td>\nFacebook<\/td>\n$5,000<\/td>\n$7,250<\/td>\n200<\/td>\n145%<\/td>\n$25.00<\/td>\n<\/tr>\n
Paid<\/td>\nInstagram<\/td>\n$3,000<\/td>\n$2,700<\/td>\n90<\/td>\n90%<\/td>\n$33.33<\/td>\n<\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n
Instagram paid ads are below breakeven (90% ROAS). Either optimize the targeting, improve the landing experience, or reallocate budget to email and push.<\/p>\n\n\n\n
Attribution Windows<\/h3>\n\n\n\n
How long after a deep link click should you attribute conversions?<\/p>\n\n\n\n
\n\n\n\n\n\n\n
Window<\/th>\nTypical Use<\/th>\nTrade-off<\/th>\n<\/tr>\n<\/thead>\n
1 hour<\/td>\nImmediate actions (purchases, sign-ups)<\/td>\nMisses delayed conversions<\/td>\n<\/tr>\n
24 hours<\/td>\nStandard for most campaigns<\/td>\nGood balance<\/td>\n<\/tr>\n
7 days<\/td>\nRe-engagement, consideration products<\/td>\nMay over-attribute<\/td>\n<\/tr>\n
30 days<\/td>\nHigh-consideration purchases (travel, finance)<\/td>\nRisk of false attribution<\/td>\n<\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n
Use shorter windows for impulse purchases and longer windows for products with research cycles.<\/p>\n\n\n\n
A\/B Testing with Deep Links<\/h2>\n\n\n\n
Testing Link Variations<\/h3>\n\n\n\n
Deep links make A\/B testing straightforward because each link variant can point to a different experience:<\/p>\n\n\n\n
\n\n\n\n\n\n\n
Test Element<\/th>\nVariant A<\/th>\nVariant B<\/th>\nWinner<\/th>\n<\/tr>\n<\/thead>\n
Landing screen<\/td>\nProduct list<\/td>\nFeatured product<\/td>\nB (22% higher conversion)<\/td>\n<\/tr>\n
CTA button<\/td>\n"Shop Now"<\/td>\n"See Your Offer"<\/td>\nB (15% higher CTR)<\/td>\n<\/tr>\n
Offer type<\/td>\n% discount<\/td>\n$ off<\/td>\nA (8% higher AOV)<\/td>\n<\/tr>\n
Personalization<\/td>\nGeneric greeting<\/td>\nName + history<\/td>\nB (30% higher conversion)<\/td>\n<\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n
Measuring Test Results<\/h3>\n\n\n\n
SELECT\n  campaign,\n  variant,\n  COUNT(*) AS clicks,\n  SUM(CASE WHEN converted THEN 1 ELSE 0 END) AS conversions,\n  ROUND(SUM(CASE WHEN converted THEN 1 ELSE 0 END)::DECIMAL \/ COUNT(*) * 100, 2) AS conv_rate,\n  ROUND(AVG(CASE WHEN converted THEN revenue END), 2) AS avg_order_value\nFROM ab_test_results\nWHERE campaign = 'summer-sale-landing-test'\nGROUP BY campaign, variant;\n<\/code><\/pre>\n\n\n\n
\n\n\n\n\n
Variant<\/th>\nClicks<\/th>\nConversions<\/th>\nConv Rate<\/th>\nAvg Order Value<\/th>\n<\/tr>\n<\/thead>\n
A (product list)<\/td>\n3,200<\/td>\n384<\/td>\n12.00%<\/td>\n$42.50<\/td>\n<\/tr>\n
B (featured product)<\/td>\n3,150<\/td>\n462<\/td>\n14.67%<\/td>\n$38.20<\/td>\n<\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n
Variant B has a higher conversion rate, but Variant A has a higher average order value. Revenue per click: A = $5.10, B = $5.61. Variant B wins on revenue per click.<\/p>\n\n\n\n
Audience Segmentation<\/h2>\n\n\n\n
Segmenting by Deep Link Behavior<\/h3>\n\n\n\n
Group your audience by how they interact with deep links:<\/p>\n\n\n\n
\n\n\n\n\n\n\n\n
Segment<\/th>\nDefinition<\/th>\nStrategy<\/th>\n<\/tr>\n<\/thead>\n
Active clickers<\/td>\nClicked 3+ deep links in 30 days<\/td>\nSend more targeted deep links<\/td>\n<\/tr>\n
One-time clickers<\/td>\nClicked 1 deep link, did not convert<\/td>\nRe-target with different content<\/td>\n<\/tr>\n
Converters<\/td>\nClicked and converted<\/td>\nUpsell, cross-sell, loyalty<\/td>\n<\/tr>\n
Lapsed<\/td>\nNo deep link click in 60+ days<\/td>\nRe-engagement campaign<\/td>\n<\/tr>\n
Non-clickers<\/td>\nReceived links but never clicked<\/td>\nTry different channels or timing<\/td>\n<\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n
Performance by Segment<\/h3>\n\n\n\n
SELECT\n  segment,\n  COUNT(*) AS users,\n  ROUND(AVG(clicks_30d), 1) AS avg_clicks,\n  ROUND(AVG(conversions_30d), 2) AS avg_conversions,\n  ROUND(AVG(revenue_30d), 2) AS avg_revenue,\n  ROUND(AVG(ltv), 2) AS avg_ltv\nFROM user_segments\nGROUP BY segment\nORDER BY avg_ltv DESC;\n<\/code><\/pre>\n\n\n\n
Budget Allocation<\/h2>\n\n\n\n
Data-Driven Budget Decisions<\/h3>\n\n\n\n
Use deep link analytics to decide where to spend:<\/p>\n\n\n\n
SELECT\n  source,\n  SUM(spend) AS current_spend,\n  SUM(revenue) AS revenue,\n  ROUND(SUM(revenue)::DECIMAL \/ NULLIF(SUM(spend), 0), 2) AS roas,\n  ROUND(SUM(spend)::DECIMAL \/ NULLIF(SUM(CASE WHEN converted THEN 1 ELSE 0 END), 0), 2) AS cpa,\n  -- Marginal efficiency: would more spend on this channel be profitable?\n  CASE\n    WHEN SUM(revenue)::DECIMAL \/ NULLIF(SUM(spend), 0) > 2.0 THEN 'Increase budget'\n    WHEN SUM(revenue)::DECIMAL \/ NULLIF(SUM(spend), 0) > 1.0 THEN 'Maintain budget'\n    ELSE 'Reduce\/cut budget'\n  END AS recommendation\nFROM campaign_performance\nWHERE timestamp >= '2026-07-01'\nGROUP BY source\nORDER BY roas DESC;\n<\/code><\/pre>\n\n\n\n
\n\n\n\n\n\n\n\n
Channel<\/th>\nCurrent Spend<\/th>\nRevenue<\/th>\nROAS<\/th>\nCPA<\/th>\nRecommendation<\/th>\n<\/tr>\n<\/thead>\n
Email<\/td>\n$2,000<\/td>\n$8,200<\/td>\n4.10<\/td>\n$4.88<\/td>\nIncrease budget<\/td>\n<\/tr>\n
Push<\/td>\n$500<\/td>\n$1,750<\/td>\n3.50<\/td>\n$2.86<\/td>\nIncrease budget<\/td>\n<\/tr>\n
QR codes<\/td>\n$1,500<\/td>\n$3,600<\/td>\n2.40<\/td>\n$12.50<\/td>\nIncrease budget<\/td>\n<\/tr>\n
Facebook<\/td>\n$5,000<\/td>\n$7,250<\/td>\n1.45<\/td>\n$25.00<\/td>\nMaintain budget<\/td>\n<\/tr>\n
Instagram<\/td>\n$3,000<\/td>\n$2,700<\/td>\n0.90<\/td>\n$33.33<\/td>\nReduce budget<\/td>\n<\/tr>\n<\/tbody><\/table><\/figure>\n\n\n\n
Diminishing Returns<\/h3>\n\n\n\n
As you increase spend on a channel, CPA tends to increase (you exhaust the most responsive audience first). Monitor marginal CPA, not just average CPA, to avoid overspending.<\/p>\n\n\n\n
Reporting for Stakeholders<\/h2>\n\n\n\n
Weekly Marketing Report<\/h3>\n\n\n\n
Keep it short and actionable:<\/p>\n\n\n\n
    \n
  1. Headline metric:<\/strong> "Deep link campaigns drove $18,500 in revenue this week, up 12% from last week."<\/li>\n
  2. Channel comparison:<\/strong> Table showing clicks, conversions, CPA, ROAS by channel.<\/li>\n
  3. Top performing campaign:<\/strong> Which campaign drove the most value?<\/li>\n
  4. Underperforming campaign:<\/strong> Which campaign needs attention?<\/li>\n
  5. Next week's plan:<\/strong> 2-3 specific actions based on the data.<\/li>\n<\/ol>\n\n\n\n
    Monthly Executive Summary<\/h3>\n\n\n\n
    Executives want business impact:<\/p>\n\n\n\n