Co-purchase block on 1C-Bitrix: development and integration

Emptiness on a product card or a 'similar by properties' block – conversion drops. The buyer sees no value: products with similar characteristics don't reflect real behavior. The co-purchase block solves this differently – it relies on order statistics. This approach yields 2–3 times more clicks and increases the average check by 15–30%. We have implemented it on 1C-Bitrix for dozens of projects – from catalogs of 500 products to marketplaces with a million items. The solution is suitable for any edition: 'Small Business', 'Business', or 'Enterprise'. Want to estimate the effect on your catalog? Contact us – we'll show you a demo.

How does the 'customers who bought this also bought' block work?

Logic: for each product A, we find all orders where it was purchased and check which other products appear in the same orders. The more often a pair appears, the higher the recommendation score. We use a threshold of 3 joint purchases over the last 90 days to filter out random coincidences.

Data sources and SQL

The main information resides in the b_sale_order (orders) and b_sale_basket (items) tables. The query gathers products bought together over the last 90 days – this is enough for assortment changes to reflect quickly.

SELECT
    b2.product_id                       AS recommended_id,
    COUNT(DISTINCT b2.order_id)         AS co_purchase_count
FROM b_sale_basket b1
JOIN b_sale_order o ON b1.order_id = o.id
    AND o.canceled = 'N'
    AND o.status_id NOT IN ('F')
JOIN b_sale_basket b2 ON b1.order_id = b2.order_id
    AND b2.product_id != b1.product_id
    AND b2.product_id IS NOT NULL
WHERE
    b1.product_id = :productId
    AND o.date_insert >= DATE_SUB(NOW(), INTERVAL 90 DAY)
GROUP BY b2.product_id
HAVING co_purchase_count >= 3
ORDER BY co_purchase_count DESC
LIMIT 20;

Results are saved into a separate table custom_co_purchases with a primary key (product_id, recommended_id). This allows fast lookups without heavy queries each time. More details on the sale module table structure can be found in Bitrix documentation.

Pre-calculation via agent

Running such SQL on every product card view is deadly for performance. Therefore, we pre-calculate for the top 500 products using an agent that runs nightly.

// Agent in local/php_interface/init.php
function RecalcCoPurchasesAgent(): string {
    $topProducts = getTopSellingProducts(500);
    foreach ($topProducts as $productId) {
        $recs = calcCoPurchases($productId);
        saveToCoPurchases($productId, $recs);
    }
    return 'RecalcCoPurchasesAgent();';
}

The agent recalculates data once a day. For non top products we use a fallback.

Component with tagged caching

The block output is implemented via the component company:catalog.co_purchases. The component uses tagged caching so that product card pages are not recalculated on every visit. The cache is tied to the tag co_purchases, enabling invalidation when orders change.

// component.php
if (!\Bitrix\Main\Loader::includeModule('iblock') || !\Bitrix\Main\Loader::includeModule('catalog')) {
    return;
}

$productId = (int)$arParams['PRODUCT_ID'];
$limit     = (int)($arParams['LIMIT'] ?? 8);

$cache = \Bitrix\Main\Data\Cache::createInstance();
if ($cache->initCache(3600, "co_purchases_{$productId}_{$limit}", '/co_purchases')) {
    $arResult = $cache->getVars();
} elseif ($cache->startDataCache()) {
    $cache->registerTag('co_purchases');
    $recommendedIds = getFromCoPurchasesTable($productId, $limit);
    $arResult       = getProductsByIds($recommendedIds);
    $cache->endDataCache($arResult);
}

$this->IncludeComponentTemplate();

Filtering and cold start

Before displaying, recommendations are filtered: only active products with non-zero stock. If there's insufficient data for a product (new item or just launched store), we use a content-based fallback – show products from the same category. This solves the cold start problem.

function getRecommendations(int $productId, int $limit): array {
    $coPurchases = getFromCoPurchasesTable($productId, $limit);

    if (count($coPurchases) >= $limit) {
        return $coPurchases;
    }

    $needed    = $limit - count($coPurchases);
    $exclude   = array_merge([$productId], $coPurchases);
    $categoryFill = getSameCategoryProducts($productId, $needed, $exclude);

    return array_merge($coPurchases, $categoryFill);
}

Cart block

The same mechanism can be applied to the cart: show 'frequently bought with items in your cart'. We take all products from the cart, gather their recommendations, sum up the scores, and exclude already added items.

$basketItems = \Bitrix\Sale\Basket::loadItemsForFUser(\Bitrix\Sale\FUser::getId());
$basketIds   = [];
foreach ($basketItems as $item) {
    $basketIds[] = $item->getProductId();
}

$allRecs = [];
foreach ($basketIds as $id) {
    $recs = getFromCoPurchasesTable($id, 20);
    foreach ($recs as $rec) {
        $allRecs[$rec['recommended_id']] = ($allRecs[$rec['recommended_id']] ?? 0) + $rec['score'];
    }
}

foreach ($basketIds as $id) unset($allRecs[$id]);
arsort($allRecs);
$topRecs = array_slice(array_keys($allRecs), 0, 8);

Why co-purchases are more effective than similar products?

Comparison of approaches in the table below. The co-purchase block relies on real buyer behavior, not formal properties. We guarantee stable operation on any Bitrix version (starting from 17.0) and provide a code warranty.

We recommend running an A/B test: show co-purchases to half the traffic and standard recommendations to the other half. In 80% of projects, the co-purchase block wins with a 30-50% higher CTR.

What's included in the work?

1. Analysis of current orders and data structure
2. SQL query optimized for your volume
3. Pre-calculation agent development
4. Component with caching and fallback
5. Cart block integration
6. Deployment and configuration documentation
7. Post-release consultation

Development timeline

Example calculation: with a 20% increase in average check, additional revenue from every 1000 visitors grows significantly. Over a year on traffic of 10,000 visitors per month, this yields a substantial increase.

Order development of the 'customers who bought this also bought' block – get a ready component with documentation and post-release consultation. Contact us to evaluate your project.

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.