Developing an Analytics Module for 1C-Bitrix Administrator

Imagine: every morning the director spends 30 minutes gathering reports from different admin sections. Revenue — in order reports, conversion — in statistics, returns — in the change log. Data is scattered, no consolidated picture. We developed a module that collects everything into one dashboard in seconds.

Over 10+ years we've completed over 500 projects on 1C-Bitrix, and custom analytics is one of the most requested customizations. The module is built on aggregation tables that provide loading speeds 100 times faster than direct SQL. Let's see how it works.

Why standard reports aren't enough

Built-in Bitrix reports are designed for universal scenarios, but every business has its own KPIs. For example, in grocery retail it's critical to track product turnover, while for digital goods — time between order and payment. Without custom analytics, you either tolerate scattered data or spend budget on scripts and Excel summaries.

Data for analytics is spread across several tables:

Direct queries to these tables in real time for a dashboard is a bad idea: b_sale_order on an active store contains millions of records. The solution is aggregation tables recalculated nightly and incrementally as needed. This architecture yields read speeds 100 times faster than direct SQL.

Stages of analytics module development

The module implementation process consists of several stages:

1. Business requirements analysis — identifying key metrics and usage scenarios. We gather manager's wishes and determine what data is needed on the dashboard.
2. Data schema design — creating aggregation tables with indexes and partitioning for fast loading.
3. Agent and event development — setting up background tasks for aggregate recalculation and incremental updates every 15 minutes.
4. Dashboard creation — interface with filters, charts, and tables. Top panel shows key metrics for today.
5. External API integration — connecting Yandex.Metrica, CRM, mailing services as needed.
6. Testing and access rights configuration — differentiating report visibility for different roles.
7. Documentation and training — schema description, agents, admin manual.
8. Warranty support — 1 month after delivery.

How aggregation works

Create a separate table with daily totals:

-- Daily aggregates
CREATE TABLE myvendor_analytics_daily (
    date        DATE NOT NULL,
    orders      INT DEFAULT 0,
    revenue     DECIMAL(14,2) DEFAULT 0,
    avg_check   DECIMAL(14,2) DEFAULT 0,
    new_users   INT DEFAULT 0,
    canceled    INT DEFAULT 0,
    PRIMARY KEY (date)
);

An agent at 02:00 recalculates the previous day and updates the row. Current day data updates every 15 minutes incrementally — from the last processed record by b_sale_order.DATE_STATUS. For more on agent mechanics, see the 1C-Bitrix documentation.

Dashboard structure

Top panel — key metrics for today:

• Revenue (and % change vs yesterday / last week)
• Number of orders
• Average check
• Conversion: visitors → orders (if Metrica connected)

"Top products" block for selected period: by sales count, revenue, returns count. Data from aggregation table myvendor_analytics_product_daily.

Order funnel. Shows losses at each stage:

• Added to cart (from b_sale_fuser + b_sale_basket)
• Proceeded to checkout
• Paid
• Received (delivery status)

This is the most valuable report — it shows exactly where money is lost.

Detailed: cohort report

Cohort analysis — how well the store retains customers. A cohort is a group of users who made their first order in the same period (week or month). Cohort analysis objectively evaluates retention.

-- First order of each user
WITH first_orders AS (
    SELECT user_id, MIN(DATE_TRUNC('month', date_insert)) AS cohort_month
    FROM b_sale_order
    WHERE canceled = 'N' AND user_id > 0
    GROUP BY user_id
),
-- All subsequent orders
repeat_orders AS (
    SELECT o.user_id, fo.cohort_month,
           DATE_TRUNC('month', o.date_insert) AS order_month
    FROM b_sale_order o
    JOIN first_orders fo ON o.user_id = fo.user_id
    WHERE o.canceled = 'N'
)
SELECT
    cohort_month,
    order_month,
    COUNT(DISTINCT user_id) AS users
FROM repeat_orders
GROUP BY cohort_month, order_month
ORDER BY cohort_month, order_month;

The result is displayed as a heatmap: rows — cohorts, columns — months after first purchase, value — retention percentage.

Export and report scheduling

Each report exports to Excel (via PhpSpreadsheet or internal tools) and CSV. The module supports scheduling: send a selected report to the manager's email once a week. Scheduling is implemented through Bitrix agents with settings stored in myvendor_analytics_schedule.

Typical mistakes in analytics development

• Direct SQL queries to b_sale_order in real time — load the database and slow down the store. Use aggregations.
• Missing indexes on date — without an index, a monthly selection takes minutes.
• Synchronous aggregate recalculation — better done asynchronously via agents.
• Ignoring access rights — dashboard should only show data allowed for the role.

What's included

• Business requirements analysis and architecture design
• Module development with source code and documentation
• Integration with external systems (if needed)
• Testing and access rights configuration
• Administrator training and password handover
• 1-month warranty support

Timelines and cost

Cost is calculated individually based on aggregation complexity and number of integrations. We guarantee transparent estimation without hidden charges. Automating analytics saves up to 40 hours per month — 20% of a manager's working time. If you want a similar dashboard, get a one-day estimate — contact us. Receive a consultation right now.

1C-Bitrix Module Development and Setup

The main trap of Bitrix is init.php. You add an OnBeforeIBlockElementUpdate handler there, then another one — a year later the file is 2000 lines, and on every hit all that code executes. We move business logic into full-fledged modules with D7 ORM, custom tables, and administrative interface. The module can be disabled, transferred to another project, covered with tests — none of that is possible with init.php. Our team has 10+ years of Bitrix experience, certified specialists, and a 6-month code guarantee. Request a consultation — we'll explain how to migrate legacy code to a modular architecture.

Why is init.php the worst place for business logic?

Init.php does not support class autoloading, lacks an isolated namespace, cannot be unit tested, and cannot be disabled without editing the file itself. Every handler written there runs on every request, even if not needed. In a module, you register handlers through EventManager, and they only execute when the event occurs. Performance difference: up to 3x with 10+ handlers.

Standard Modules: Typical Problems and Solutions

Information blocks. IBlock architecture is the first thing we review on any project. A classic mistake: one catalog infoblock with 80 properties, 30 of which are multiple. The b_iblock_element_property table swells to millions of rows, and CIBlockElement::GetList with filtering on three properties does a full scan. We move reference data to Highload-blocks, eliminate multiple properties where possible, and design the structure for 5x growth.

e-Store (sale). Cart business rules are a separate story. We set discount priorities to prevent two campaigns from giving 60% instead of 30%, connect payment handlers, and write custom validation via OnSaleOrderBeforeSaved.

Search. The built-in search module with morphology works up to 10–15 thousand elements. Beyond that — Elasticsearch. We configure it via the Bitrix search module API, indexing through CSearchFullText or custom indexers.

Highload-blocks for dictionaries, logs, user data — instead of bloated IBlocks. Direct queries via Bitrix\Highloadblock\HighloadBlockTable, custom tables instead of the EAV structure of standard infoblocks. A million records — no degradation.

Mail events. Configuration is not just templates in b_event_message. The key is SPF, DKIM, DMARC on the DNS, otherwise transactional emails go to spam. We check deliverability and set up bounce handling.

How to Design Infoblocks for Performance?

We use Highload-blocks for reference data (colors, sizes, manufacturers) that are not involved in complex queries. For SKUs — a separate infoblock with linking via IBLOCK_ELEMENT_PROPERTY. Enable INDEX_PROPERTY for frequently filtered properties. Tagged caching: when an element changes, only the related cache is cleared. Highload-blocks process up to 10x faster than infoblocks with multiple properties on volumes of 100,000 records.

Custom Module Development

Each module follows the structure /local/modules/vendor.modulename/:

• install/index.php — setup class, create tables via $DB->RunSQLBatch()
• lib/ — D7 ORM classes, extending Bitrix\Main\ORM\Data\DataManager
• admin/ — administrative pages using CAdminList, CAdminForm
• include.php — autoloading, event handler registration via EventManager::getInstance()->registerEventHandler()
• REST API endpoints via \Bitrix\Rest\RestManager

The module registers in the system, appears in the "Installed Solutions" list, and has its own settings at /bitrix/admin/settings.php?mid=vendor.modulename. It can be enabled, disabled, and updated through UpdateSystem or custom migration mechanics.

Examples of implemented tasks:

• Campaign management — visual condition builder via CAdminCalendar, timers via agents (CAgent::AddAgent), analytics linked to the sale module
• Cost calculator — React widget on the frontend, REST API in the module, formulas stored in a Highload-block
• Booking system — real-time calendar, locking via $DB->StartTransaction() / $DB->Commit() on concurrent requests, integration with channel manager via webhook

Components and Composite Cache

Component customization via result_modifier.php and component_epilog.php, not by editing template.php of the standard template. This way core updates are painless.

Composite cache ("Composite Site" technology) — the server sends ready HTML, bypassing PHP routing. Dynamic areas (cart, authorization) are loaded via CBitrixComponent::setFrameMode(true) and AJAX. TTFB drops to 30–50 ms. But there are caveats: not all components are compatible, $APPLICATION->ShowPanel() breaks composite, and careful markup of <div id="bx-composite-..."> is required.

What to Check Before Installing a Marketplace Module?

Before installing a module from the marketplace, an audit is mandatory. We check: SQL queries without prepared statements (hello SQL injection), direct use of $_REQUEST without filtering, use of outdated kernel API instead of D7, conflicts with the composite cache module. A module with no updates for over a year and a few dozen installations is likely a problem on the next PHP update. A typical case: a module calls CIBlockElement::GetList with no cache reset — the site crashes with 5000 elements.

Migration to D7

When upgrading PHP or switching to a new edition — refactor outdated calls:

• CIBlockElement::GetList() → Bitrix\Iblock\Elements\ElementTable::getList()
• CSaleOrder::GetList() → Bitrix\Sale\Order::getList()
• CModule::IncludeModule() → Bitrix\Main\Loader::includeModule() Testing on staging, rollback via git on issues.

According to official 1C-Bitrix documentation, D7 ORM is the recommended tool for working with data, providing type safety and automatic query generation.

Comparison: Init.php vs Module

Module Development Scope and Cost

What is included in module development?

• Technical specification and architectural plan
• Code following PSR-4 and Bitrix code style
• Unit tests (PHPUnit) for business logic
• Integration tests for events and REST API
• Installation, configuration, and API documentation
• Repository and documentation access
• Administrator training for module usage
• 6-month warranty support

Estimated timelines and complexity:

Cost is calculated individually — contact us for a project estimate.

Module Testing

Unit tests via PHPUnit cover business logic: discount calculation, validation, document generation. Mocks for Bitrix\Main\Application::getConnection() allow tests to be DB-independent. Integration tests verify event handlers on a real database — OnAfterIBlockElementAdd, OnSaleOrderSaved, etc. REST API endpoints are tested via curl or PHPUnit HTTP client. Critical for modules working with b_sale_order, b_catalog_price — where errors cost money.

Compatibility is checked on PHP 7.4, 8.0, 8.1, 8.2 and editions: Standard, Small Business, Business. We check conflicts with popular marketplace modules — they often intercept the same events. Load testing: measurements on 10K, 100K, 1M records, profiling via Xdebug for memory leaks and N+1 queries.

Practical Examples

Campaign module for an electronics chain. The built-in sale module discounts did not cover scenarios like "2+1", a gift with purchase over a certain amount, or combined conditions. We built a visual builder: marketers create rules via drag-and-drop without development tickets. Campaign calendar, auto-deactivation via agents, analytics linked to b_sale_order — conversion, average check, usage count. Time to launch a new campaign dropped from two days to half an hour.

Calculator for builders. Parameters (area, materials, number of floors) → formula → preliminary estimate → lead to CRM via CRest::call('crm.lead.add'). Regional coefficients and seasonal markups from a Highload-block, material prices from 1C exchange. The number of target leads increased by a third: clients see a breakdown before calling a manager.

Booking for a hotel chain. Real-time availability via AJAX requests to a custom table vendor_booking_slots, seasonal tariff calculation, synchronization with Booking.com via channel manager API. Room locking on concurrent booking via SELECT ... FOR UPDATE in transactions. Timezones handled via \DateTimeZone — a guest from Vladivostok and a manager from Moscow see the same picture.

We will evaluate your project within one day. Write to us — we'll tell you what is included in turnkey development. Contact us for a consultation on your project. Order a custom module development — get a ready solution with documentation and support.