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Analytics & Reporting

Rinku provides real-time analytics to track campaign performance, identify profitable segments, and spot losing traffic sources at a glance.

Key Metrics

Clicks

The total number of visitors who clicked your campaign tracking link. Each click generates a unique click record with full visitor data.

Conversions

Actions taken by visitors after clicking (e.g., sign-up, purchase, app install). Conversions are linked to clicks via a unique click_id sent in the postback.

Cost

Total amount spent on traffic, calculated based on your pricing model:

  • CPC (Cost Per Click): Cost × Clicks
  • CPA (Cost Per Acquisition): Actual cost per conversion (via postback data)

Payout

Revenue received for each conversion. Sourced from your affiliate network's postback data.

ROI (Return on Investment)

Profit calculation: (Payout - Cost) / Cost × 100%

  • Positive ROI = Profitable campaign
  • Negative ROI = Losing money on that segment
  • ROI = 0 = Breaking even

What You Can Track

Rinku automatically collects and segments data by:

Visitor Geography

  • Country — where the visitor is located
  • City — city-level geo-targeting
  • Region — state/province level

Device & Browser

  • Device Type — Mobile, Desktop, Tablet
  • OS — iOS, Android, Windows, macOS, etc.
  • Browser — Chrome, Safari, Firefox, Edge, etc.
  • Language — Browser language setting

Network Parameters

  • Zone ID ({net_pid}) — Ad zone or publisher ID
  • Source ({net_source}) — Traffic source identifier
  • Creative ({net_creative}) — Ad creative ID
  • Campaign ({net_campaign}) — Network campaign ID

Custom Tokens

Any values you pass via {token_1} through {token_30}. Common uses:

  • Publisher subcampaign ID
  • Ad placement location
  • Traffic quality tier
  • Internal reference IDs

Filtering & Drilling Down

In the Analytics section, you can:

  1. Select date range — view data for any period
  2. Add filters — narrow down by any dimension (e.g., only mobile, only US)
  3. Group by dimension — see metrics broken down by zone, country, device, etc.
  4. Compare segments — side-by-side ROI analysis
  5. Sort results — by clicks, conversions, cost, ROI, or payout

Identifying Problem Areas

Common filtering patterns to find losing segments:

Find unprofitable zones

Filter by Zone ID, sort by ROI (ascending) → see which zones are losing money

Find low-converting countries

Group by Country, filter conversions < 2% → see which geos have poor conversion rates

Test bot traffic impact

Filter by is_bot = Yes/No → compare conversion rates with and without bots

Analyze by device

Group by Device Type → identify if mobile or desktop is more profitable

Export & Analysis

You can export filtered data as:

  • CSV — for spreadsheet analysis
  • XLSX — for Excel with formatting
  • PDF — for reports and sharing

What's Next?