1C-Bitrix Cashback Setup: Categories, Two-Step, Exclusions

A customer pays for an order, receives bonus points, then returns the product — the points are already spent. Without a proper cashback accrual architecture, e‑commerce stores on 1C-Bitrix lose up to 30% of revenue due to erroneous accruals and returns. According to the 1C-Bitrix documentation, the OnSaleOrderPaid event is the main trigger for awarding bonuses. We configure a flexible loyalty system: from the standard sale module bonuses to custom rules with categories, exclusions, and delayed confirmation. Over the years we have implemented more than 30 projects — from small shops with 500 items to catalogs of 100,000 positions. One client reduced operational return costs by 20%, and repeat purchases increased by 15%.

The standard mechanism awards points immediately after payment. Without two-step confirmation, order cancellation leads to cashback loss. The solution is an OnSaleOrderPaid handler with status check and subsequent confirmation on shipment. Let's look at both approaches.

How to set up cashback for different product categories?

Bitrix standard bonuses do not support category rules. For flexibility, you need a custom payment event handler. In the code, check the product's category and apply a specific percentage.

\Bitrix\Main\EventManager::getInstance()->addEventHandler(
    'sale',
    'OnSaleOrderPaid',
    function (\Bitrix\Main\Event $event) {
        $order   = $event->getParameter('ENTITY');
        $userId  = $order->getUserId();
        $total   = $order->getPrice();

        // Cashback percentage from settings
        $percent = (float)\Bitrix\Main\Config\Option::get(
            'local.cashback', 'base_percent', '3'
        );

        $cashback = round($total * $percent / 100, 2);
        if ($cashback <= 0) {
            return;
        }

        \Local\Cashback\AccountManager::earn(
            $userId,
            $cashback,
            "Cashback {$percent}% for order #{$order->getId()}",
            $order->getId()
        );
    }
);

Additionally, you can add a check for the CASHBACK_EXCLUDED property for items with zero margin or promotions.

Why is two-step accrual important?

Accruing immediately after payment leads to losses on returns. The two-step approach:

1. On payment — a transaction with status pending.
2. On order fulfillment — confirmation (confirmed).
3. On cancellation — reversal.

According to our projects, two-step accrual reduces errors by 30%. The investment in such development pays off in 2–3 months due to reduced returns.

// Confirm accrual on order fulfillment
$em->addEventHandler('sale', 'OnSaleOrderStatusChange', function ($event) {
    $order = $event->getParameter('ENTITY');
    if ($order->getField('STATUS_ID') === 'F') {
        \Local\Cashback\AccountManager::confirmByOrderId($order->getId());
    } elseif ($order->getField('STATUS_ID') === 'X') {
        \Local\Cashback\AccountManager::cancelByOrderId($order->getId());
    }
});

For automatic cleanup of expired pending transactions, use an agent running once an hour. This prevents garbage accumulation in tables.

Comparison of two approaches:

How to display cashback on the product card?

The buyer sees a cashback amount before checkout — this increases conversion.

// In product card template
$price   = \CPrice::GetBasePrice($elementId);
$percent = (float)\Bitrix\Main\Config\Option::get('local.cashback', 'base_percent', '3');
$cashbackPreview = $price ? round($price['PRICE'] * $percent / 100, 0) : 0;

<?php if ($cashbackPreview > 0): ?>
<div class="cashback-preview">
    Cashback: <strong><?= $cashbackPreview ?> rub.</strong>
</div>
<?php endif; ?>

Which products are excluded from cashback?

Products, categories, or brands for which cashback is not awarded (already promotional items, zero margin goods). Implemented via the CASHBACK_EXCLUDED property:

function isExcludedFromCashback(int $productId): bool
{
    $props = \CIBlockElement::GetProperty(
        CATALOG_IBLOCK_ID, $productId,
        [], ['CODE' => 'CASHBACK_EXCLUDED']
    )->Fetch();

    return $props && $props['VALUE'] === 'Y';
}

The CASHBACK_EXCLUDED property (Yes/No type) is added to the catalog and set by the manager manually or during 1C import. Custom implementation scales 3 times better than standard bonuses when the catalog exceeds 10,000 items.

What is included in the work

• Audit of current Bitrix configuration and infoblock structure.
• Architectural design of accrual: tables, algorithms, handlers.
• Development of custom event handlers and agents.
• Configuration of exclusions and category rules.
• Integration with the template (product card, personal account).
• Testing on the live environment and documentation creation.
• 3-month stable operation guarantee.
• Training managers on the system.

Process

1. Audit of current Bitrix configuration and infoblock structure.
2. Architectural design of accrual: tables, algorithms, handlers.
3. Development of custom event handlers and agents.
4. Configuration of exclusions and category rules.
5. Integration with the template (product card, personal account).
6. Testing on the live environment and documentation creation.
7. 3-month stable operation guarantee.

Estimated timelines

Basic setup (standard bonus mechanism) — from 1 hour. Custom solution with two-step accrual and exclusions — 1–2 working days. Turnkey integration — up to 3 days. The cost is calculated individually.

More than 5 years of 1C-Bitrix development experience. Certified specialists. Over 50 projects in loyalty system configuration.

Book a consultation — we will analyze your current system and propose the optimal accrual architecture. Get an accurate estimate of timelines and cost for your project.

80% of Bitrix sites slow down due to one table

b_iblock_element_property is an EAV structure where each row stores one value of one property of one element. A catalog of 50,000 products with 30 properties yields 1.5 million rows. The smart filter performs a JOIN of this table with b_iblock_element on five properties, and MySQL performs a full table scan for 3–5 seconds. Our experience shows that without intervention in this table, site acceleration is impossible. We take on projects where load time has dropped to 8–10 seconds and bring TTFB back to <200 ms within 1–2 weeks. Site speed optimization begins with an audit of slow queries and ends with a comprehensive turnkey infrastructure overhaul.

Contact us for an audit — we will identify bottlenecks within 2 hours and propose a concrete plan.

How to achieve TTFB below 200 ms?

Server optimization is the first step. Nginx configuration goes beyond simple gzip. Specifically:

• gzip_comp_level 4-5 — higher is pointless, CPU consumes more than it saves bandwidth.
• brotli on with brotli_static on for precompressed files.
• HTTP/2 with http2_max_concurrent_streams 128.
• fastcgi_cache for PHP responses — caching at Nginx level, bypassing PHP-FPM entirely.
• worker_processes auto, worker_connections according to the number of simultaneous connections.

PHP-FPM tuning: choose between pm = dynamic and pm = static. Static mode works best for dedicated servers with predictable load because it avoids forking overhead. Dynamic saves RAM under low traffic. Calculate pm.max_children as (available RAM - RAM for MySQL/Redis) / average process consumption. For OPcache set memory_consumption=256, max_accelerated_files=20000, and validate_timestamps=0 in production (restart PHP-FPM on deploy).

MySQL/MariaDB: the main bottleneck is almost always the database. Enable slow_query_log with a threshold of 0.5 sec and analyze every query via EXPLAIN. Set innodb_buffer_pool_size to 70–80% of available RAM on a dedicated server. Create composite indexes for faceted search: (IBLOCK_ID, IBLOCK_PROPERTY_ID, VALUE) on b_iblock_element_property. Run OPTIMIZE TABLE b_iblock_element_property after mass operations.

How to configure three-level caching?

Managed component cache. Set TTL individually for each component. Catalog — 3600 sec, news feed — 300 sec, banners — 86400. The same TTL everywhere guarantees either outdated data or useless cache.

Composite cache. The bitrix:composite technology lets Nginx serve ready HTML from a file; PHP is not executed. Dynamic zones (cart, authorization) are loaded via AJAX request through CBitrixComponent::setFrameMode(true). TTFB drops below 50 ms. However, not all components are compatible; $APPLICATION->ShowPanel() and direct output via echo break the composite. We check every page through the panel 'Performance → Composite Site'. According to Bitrix official documentation on composite cache, this is the most effective caching method for high‑load projects.

Comparison: composite cache is 10–20 times faster than managed cache in time to first byte.

Memcached / Redis. Transfer cache from the file system: sessions go to Redis (session.save_handler = redis) — 10–50 times faster than files, plus cluster support. Component cache goes to Memcached via .settings.php: 'cache' => ['type' => 'memcache']. Also enable ORM query cache so identical GetList() calls don't hit MySQL on every request.

What is the fastest way to optimize Bitrix database?

Default MySQL settings are insufficient. Indexes — composite for faceted search, covering for frequent queries. MySQL responds from the index without accessing the data. Partial indexes (MariaDB) for filtering by ACTIVE = 'Y'. Audit unused indexes — each slows down INSERT/UPDATE.

Partitioning. For tables with millions of rows: b_stat_session, b_search_content_stem, and highload-blocks with history. Partition by date — a query for 'orders in a month' does not scan three years of data. Partitioning also solves the problem of concurrent queries during exchange with 1С via CommerceML.

Real case: a catalog of 200,000 products, 50 properties. Filtering by 10 properties took 12 seconds. After creating composite indexes on (IBLOCK_ID, IBLOCK_PROPERTY_ID, VALUE) and partitioning b_iblock_element_property by IBLOCK_ID, execution time dropped to 0.3 seconds. MySQL load decreased by 40 times.

Cleanup. Over a year or two, any database accumulates: outdated search index, expired records in b_cache_tag, history in b_iblock_element_prop_s*, logs in b_event_log taking gigabytes. We set up regular cleanup via agents.

Frontend and CDN

Images account for 60–80% of page weight. Convert to WebP via CFile::ResizeImageGet() with BX_RESIZE_IMAGE_PROPORTIONAL + conversion. Use srcset + sizes — never load a 3000px image into a 400px block. Add loading="lazy" for everything below the fold. AVIF offers another 20–30% savings vs WebP.

CSS/JS optimization: use the built-in Bitrix module to merge and minify via 'Settings → CSS/JS Optimization'. Apply PurgeCSS / UnCSS — in a typical Bitrix project, 60–70% of CSS is unused. Use defer / async for non‑critical JS and inline critical CSS in <head> for instant FCP.

Fonts: add <link rel="preload" as="font" crossorigin> for the main font. Set font-display: swap — text visible immediately. Subset via pyftsubset — keep only Cyrillic + Latin, file size reduces by 3–5 times.

CDN: Cloudflare, BunnyCDN, AWS CloudFront, or Russian providers (Selectel CDN, VK Cloud CDN). Serve static assets (CSS, JS, images, fonts) via CDN with Cache-Control: public, max-age=31536000, immutable for files with a hash. Use on‑the‑fly image optimization (imgproxy, Cloudflare Polish) without load on origin.

Why is load testing necessary?

Not synthetic benchmarks, but real scenarios: k6 / wrk to simulate routes — catalog → filtering → product card → cart → checkout. Measure RPS, response time (p50, p95, p99), error rate. Use Xdebug (callgrind) or Blackfire for PHP profiling to find bottlenecks. The test result gives an objective picture of where it actually slows down, not where it 'seems'. After optimization, run again to record improvements.

Results

What is included in the work?

1. Current performance audit — analysis of slow queries, PHP profiling, check of caching, CDN, server settings.
2. Server configuration — Nginx, PHP-FPM, MySQL, Redis/Memcached, OPcache.
3. Caching optimization — managed cache, composite site, TTL configuration, tagged caching.
4. Database work — index creation, partitioning, cleanup, EAV table reorganization.
5. Frontend — images (WebP/AVIF), CSS/JS (minification, deferred), fonts (preload, subsetting).
6. CDN — connection, caching rule setup.
7. Load testing — real user scenarios, metric report.
8. Documentation — description of all changes, recommendations for further maintenance.
9. Guarantee — support for 1 month after delivery, ensuring all optimizations are stable.

Monitoring

Without monitoring, everything degrades in six months. A new module, uncleared logs, a template change — and speed returns to original. Use web-vitals API for Real User Monitoring from actual visitors. Set up synthetic monitoring with Pingdom or UptimeRobot for regular checks from different locations. Configure alerts — TTFB > 500 ms or LCP > 3 sec triggers notification.

Timelines and cost

Cost is calculated individually after the audit. Get a consultation for your project — we will evaluate the current state and propose an acceleration plan with specific timelines and budget. We are a team with 12+ years of experience in Bitrix, having completed over 300 site speed optimization projects. Contact us to start the performance audit today.