Operator guideEN

Analytics / Opt-In Clicks

Operator documentation for the low-frequency Opt-In Clicks analytics page, including embedded summary cards, trend blocks, filters, export, and delete actions.

How to use this guide

Start with the main guide

Follow the explanation and examples first. Extra definitions and formulas are available below when you need them.

What this module is for

Use Analytics / Opt-In Clicks to inspect how often CRM opt-in links or feature prompts were viewed and clicked. The page is mainly for support, product operations, or low-frequency investigations when someone needs to confirm whether a feature was shown, whether users clicked it, and which feature names generated traffic.

Real operator surface

  • Analytics / Opt-In Clicks / List is the only verified Backoffice surface for this module.

The current operator page is one combined surface:

  • top summary cards
  • feature performance block
  • daily trend block
  • filter bar
  • paginated raw record table

There is no separate CRM create, edit, or detail page for this module today. Operators work from the combined analytics page only.

What operators need to know first

  • The summary cards are calculated from grouped stats rows rather than returned as one ready-made totals payload.
  • Only the date range is shared between the summary section and the table. Feature, Status, and User ID change the table request, but they do not change the top stats block.
  • The Feature dropdown counts are generated from source aggregation that respects only the date filter. Those counts are not narrowed by User ID or Status.
  • The page is effectively read-mostly. The only destructive operator action on the current route is deleting selected raw records.

Source ownership summary

The CRM page reads and exports stored opt-in interaction records from the admin service. Public opt-in views and clicks are recorded by the player-facing flow, then appear here for investigation and reporting.

Common caveats

  • Unique Users on the top cards is currently a sum of per-feature unique-user counts. That means it can overcount users who interacted with more than one feature in the selected date window.
  • Click Rate on the top cards is calculated from summed views and clicks.
  • The table shows raw records, while the top section shows aggregated statistics. They answer different questions even though they are on the same route.
More help

Related pages

Analytics / Opt-In Clicks / List

Combined analytics surface with summary cards, feature and daily trend blocks, filters, export, bulk delete, and a paginated raw opt-in record table.

Players / Banking

Banking tab inside the player workspace with transaction filters, a paginated banking grid, analytics cards, CSV export, and automatic-withdrawal availability.

Referrals Overview

Operator guide for the low-frequency referrals list that reuses the shared players grid to review referred users and jump into player profiles.

Transactions / Banking

Filterable banking transaction dashboard with weekly summary cards, backend stats charts, CSV export, and a detailed ledger-style table.

Transactions / Casino

Game transaction dashboard with real-time list mode, monthly analytics mode, filterable table, and a dedicated transaction detail route.

Actions / Merchant Balance

Operator workspace for reviewing the merchant-balance transaction journal and creating manual debit or credit adjustments.