Size Conversion Tool for 1С-Bitrix: Global Standards Support

Custom Size Converter (RU/EU/US/UK) for 1С-Bitrix

Returns due to wrong size—every online clothing or shoe store’s headache. Customer enters their US 8, gets an ill-fitting item, files a complaint. We build a size converter on 1С-Bitrix that instantly translates RU/EU/US/UK systems, lowering return rates by 15–30% (based on our project data). Source: Industry report on e-commerce returns reduction techniques (Wikipedia, 2023). Unlike a static table, the converter solves a specific user task: “I know my US size, tell me the Russian one.” These are different tools with different use cases, though both draw data from the same source.

Real Problems We Solve

• Size confusion across systems: A customer knows UK 6 but the store shows only EU sizes. Manual lookup from a static table is cumbersome and error-prone. Our converter does it in one click.
• Mobile friction: On mobile, switching between tabs and scrolling a huge table is painful. A compact inline or modal converter keeps the user on the product page.
• Integration with filtering: Without converter-to-filter linkage, customers often select a wrong size and then discover it later. We integrate so that entering e.g. US 8 auto-adjusts the filter to show only RU 40–41 items.
• Data maintenance: Sizing tables often come from suppliers in different formats. We normalize them into one unified structure, updatable via CommerceML from 1С.

How We Build It: Technical Details

We use a client-side approach for instant feedback. All size data is injected once from PHP as JSON during page load. The conversion logic runs entirely in JavaScript — no extra server requests.

Data Storage

The same table that powers a static size chart also drives the converter. We store all sizing columns in one row to enable bidirectional conversion:

SELECT size_ru, size_eu, size_us_m, size_us_w, size_uk, foot_length_mm
FROM b_shoe_size_rows
WHERE chart_id = ?
ORDER BY foot_length_mm ASC;

Core Conversion Logic

const sizeData = <?= json_encode($arResult['SIZES'], JSON_UNESCAPED_UNICODE) ?>;

function convertSize(fromSystem, value, toSystem) {
    const numValue = parseFloat(value);
    const row = sizeData.find(r => {
        const fieldName = `size_${fromSystem}`;
        return parseFloat(r[fieldName]) === numValue;
    });
    if (!row) return null;
    return row[`size_${toSystem}`];
}

Converter Widget (HTML)

<div class="size-converter">
    <select id="from-system">
        <option value="ru">RU</option>
        <option value="eu">EU</option>
        <option value="us_m">US (M)</option>
        <option value="us_w">US (W)</option>
        <option value="uk">UK</option>
    </select>
    <input type="text" id="size-input" placeholder="12">
    <button onclick="doConvert()">Convert</button>

    <div id="conversion-result" hidden>
        <table class="result-table">
            <tr><th>RU</th><th>EU</th><th>US M</th><th>US W</th><th>UK</th></tr>
            <tr id="result-row"></tr>
        </table>
    </div>
</div>

Autocomplete to Prevent Invalid Inputs

const input = document.getElementById('size-input');
input.addEventListener('input', function() {
    const from = document.getElementById('from-system').value;
    const query = this.value;
    const suggestions = sizeData
        .map(r => String(r[`size_${from}`]))
        .filter(v => v.startsWith(query));
    renderSuggestions(suggestions);
});

Integration with Smart Filter (Extended Case)

After conversion, the result can be pushed into the smart filter to show only matching offers:

function applyToFilter(sizeRu) {
    const filterCheckboxes = document.querySelectorAll(`[data-filter-size="${sizeRu}"]`);
    filterCheckboxes.forEach(cb => {
        cb.checked = true;
        cb.dispatchEvent(new Event('change'));
    });
}

One Concrete Case

For a shoe retailer selling European brands to a US audience, returns due to size mismatch were 18% of total orders. We implemented an inline converter on the product page (modal). The converter used a normalized table with data from their 1С system, synced nightly via CommerceML. Post-launch, returns from US customers dropped to 11% within two months. That’s a 39% reduction in return rate — better than any static chart solution. The converter handled 400+ conversions daily during peak season.

Service at a Glance

What’s Included in the Work

• Sizing data analysis and normalization
• Custom component with autocomplete
• Optional smart filter integration
• SEO page with static size table and Table Schema.org markup
• 1С/CommerceML exchange setup
• Staff training on data maintenance
• 2 weeks of post-launch support
• Full technical documentation and admin panel access

Company Metrics

• 10+ years of Bitrix development experience
• 100+ e-commerce projects delivered
• 50+ satisfied clients in retail and fashion
• Guarantee: 100% satisfaction or full refund within 14 days

Pricing Estimate

• Basic converter (form + conversion): $500–$800
• With autocomplete & mobile UX: $800–$1,200
• Smart filter integration: additional $300–$500
• Full cycle including SEO page: $1,500–$2,000

Next Steps

Contact us to discuss your project. We’ll evaluate your needs and propose the best solution with a fixed price. Our team has the experience and certificates to deliver a high-quality integration.

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.