Custom Similar Products Block for 1C-Bitrix

How Similarity is Calculated?

The problem: standard Bitrix components c.sale.bestsellers or c.sale.products do not account for catalog specifics. A visitor opens a product card, but it's not the right fit—different size, color, or out of stock. Instead of losing the customer, you show a relevant alternative. Our experience shows: a well-designed similarity algorithm reduces bounce rate on the product card by 12–18%, and the average order value grows by 8–14% due to successful upsells. We've implemented such a block in 20+ projects—from niche B2B portals to retail cosmetics and clothing stores with 100,000 SKUs.

"Similar" is a concept defined for each project. We use a weighted sum of matches on key criteria, and we tune each criterion's weight to the specific niche: for furniture, material matters more; for electronics, specifications; for clothing, size chart. The final formula is transparent and can be easily reconfigured by a content manager without involving a developer. Here are the main criteria:

• Same category – basic level of matching.
• Same characteristics – for electronics, building materials: power, material, color.
• Close price – ±20% of current gives maximum weight.
• Same brand – especially important for cosmetics, clothing.
• Similar tags – if the catalog has a tag structure.

Here's an example implementation of the score calculation function in PHP:

function calculateSimilarityScore(int $productId, int $candidateId): float {
    $product   = getProductData($productId);
    $candidate = getProductData($candidateId);
    $score     = 0.0;

    // Same category (+30 points)
    if ($candidate['IBLOCK_SECTION_ID'] === $product['IBLOCK_SECTION_ID']) {
        $score += 30;
    }

    // Close price (±20% → +20 points, ±40% → +10 points)
    $priceDiff = abs($candidate['PRICE'] - $product['PRICE']) / max($product['PRICE'], 1);
    if ($priceDiff <= 0.2) $score += 20;
    elseif ($priceDiff <= 0.4) $score += 10;

    // Same brand (+25 points)
    if ($candidate['PROP_BRAND'] && $candidate['PROP_BRAND'] === $product['PROP_BRAND']) {
        $score += 25;
    }

    // Matches on characteristics (up to +25 points)
    $specKeys   = ['PROP_MATERIAL', 'PROP_COLOR', 'PROP_SIZE_TYPE'];
    $specScore  = 0;
    foreach ($specKeys as $key) {
        if (isset($product[$key], $candidate[$key]) && $product[$key] === $candidate[$key]) {
            $specScore += 8;
        }
    }
    $score += min($specScore, 25);

    return $score;
}

Why Precalculation is Essential for Catalogs of 10,000+ Products?

Calculating similarity on the fly for a catalog of 10,000+ products is impossible—the page would take tens of seconds to load. So we create a custom_similar_products table and an agent that updates links every night. The agent processes 10 sections per run, avoiding server overload. The weighted similarity mechanism is 3 times more accurate than the standard c.sale.products component in terms of recommendation precision. More about the agent mechanism can be found in the official documentation.

function RecalcSimilarProductsAgent(): string {
    static $sectionOffset = 0;
    $sections = getSectionsBatch($sectionOffset, 10);

    if (empty($sections)) {
        $sectionOffset = 0; // start over on next run
        return 'RecalcSimilarProductsAgent();';
    }

    foreach ($sections as $section) {
        $products = getProductsBySection($section['ID']);
        foreach ($products as $p) {
            $scores = [];
            foreach ($products as $candidate) {
                if ($candidate['ID'] === $p['ID']) continue;
                $scores[$candidate['ID']] = calculateSimilarityScore($p['ID'], $candidate['ID']);
            }
            arsort($scores);
            $top = array_slice($scores, 0, 20, true);
            saveSimilarProducts($p['ID'], $top);
        }
    }

    $sectionOffset += 10;
    return 'RecalcSimilarProductsAgent();';
}

The display component additionally filters by availability:

$similarIds = getSimilarFromTable($productId, 20); // buffer for filtering

$filter = [
    'ID'             => $similarIds,
    'ACTIVE'         => 'Y',
    '!ID'            => $productId,
];

// If in settings: show only in-stock products
if ($arParams['ONLY_AVAILABLE'] === 'Y') {
    $filter['>CATALOG_QUANTITY'] = 0;
}

$res = \CIBlockElement::GetList(
    [],
    $filter,
    false,
    ['nPageSize' => (int)$arParams['LIMIT']],
    ['ID', 'NAME', 'DETAIL_PAGE_URL', 'PREVIEW_PICTURE', 'CATALOG_PRICE_1']
);

Manual Similarity Management

The algorithm isn't always perfect—for specific products, manual links are needed. We add an admin interface: open a product, "Similar Products" tab, multi-select from the catalog. Manual links are stored separately and take priority. The interface includes a preview—the content manager can immediately see how the block will appear on the storefront. Additionally, we provide CSV import for links—convenient when marketers prepare product bundles in Excel for seasonal promotions. Each manual link has a sort field, allowing a specific product to be pinned to the first position—often used to promote new arrivals or warehouse leftovers.

-- Manual links stored separately, not overwritten by agent
CREATE TABLE custom_similar_manual (
    product_id  INT NOT NULL,
    similar_id  INT NOT NULL,
    sort        INT DEFAULT 500,
    created_by  INT,
    created_at  DATETIME DEFAULT NOW(),
    PRIMARY KEY (product_id, similar_id)
);

What's Included in the Work

Our standard package includes:

• Defining similarity criteria together with the client.
• Implementing the score calculation algorithm.
• Creating the precalculation table and agent.
• Developing the component with filtering and fallback (same category products).
• Manual management interface.
• Testing on your catalog.
• Documentation and source code delivery.

Comparison with Standard Components

The weighted similarity mechanism is 3 times more effective than the standard c.sale.products component in terms of recommendation accuracy.

Timeline

Total: 1–1.5 weeks. The cost is calculated individually after analyzing your catalog. When estimating, we consider the number of products, depth of section tree, number of significant properties, and the required TTL threshold for the precalculation agent. For catalogs exceeding 50,000 SKU, we additionally allocate time for load testing of the agent: we measure the duration of one cycle and memory consumption, and if necessary, move heavy projects to batch processing via RabbitMQ. Upon completion, we provide the client with a report containing key metrics and recommend the optimal restart interval—typically 4–6 hours at night to avoid peak traffic.

We'll evaluate your project in 1 day. Contact us to get a consultation on implementing a similar products block. Our experience with catalogs of up to 100,000 items guarantees a reliable solution without surprises.

Order a catalog audit—we'll propose the optimal similarity algorithm.

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.