Behavior-Based Personalized Recommendations in 1C-Bitrix

When in an online store the standard bitrix:catalog.recommended component shows the same products to all visitors, the conversion of the recommendation block drops by 30–60%. The user sees items they already bought or viewed, and leaves for a competitor with an accurate "Customers also bought" block. We, a team with 10+ years of experience and over 50 implementations in 1C-Bitrix, built a personalized recommendation system based on behavior — without ML, only PHP + SQL. Turnkey in 2–5 days. Get a consultation for your project — we'll assess the possibilities for free.

What problems do we solve?

The standard bitrix:catalog.recommended component does not use user behavior. It offers the same to everyone. We implement behavioral signals: views, purchases, cart. Typical mistakes — ignoring event weight (purchase is 10x more important than view) and lack of personal category boost. Our solution fixes these issues, increasing recommendation CTR by 30–60%. In one project with a catalog of 15,000 products, we raised the recommendation block conversion from 1.2% to 3.8% in a week.

How behavior-based recommendations work

We collect events in the b_user_behavior table. Assign weights:

Weights are stored in configuration — easy to adjust for your business. Analysis window — 60 days (configurable).

$weights = [
    'purchase' => 10,
    'cart_add' => 5,
    'favorite_add' => 4,
    'view_long' => 2,
    'view_short' => 1,
    'search_click' => 3,
];

Why item-based collaborative filtering?

It's the sweet spot between random products and ML. The idea is simple: "those who viewed product A also viewed B, C, D." We compute it directly from the database. Item-based filtering gives 3–5 times more accurate recommendations compared to popular products. It requires no separate ML server and is easily scalable.

Comparison of approaches:

Optimal query to find related products:

SELECT
    b2.ENTITY_ID AS recommended_id,
    COUNT(DISTINCT b2.USER_ID) AS co_view_count
FROM b_user_behavior b1
JOIN b_user_behavior b2
    ON b1.USER_ID = b2.USER_ID
    AND b1.ENTITY_ID != b2.ENTITY_ID
    AND b2.EVENT_TYPE IN ('view', 'cart_add', 'purchase')
    AND b2.DATE_CREATE > NOW() - INTERVAL '60 days'
WHERE
    b1.ENTITY_ID = :current_item_id
    AND b1.EVENT_TYPE IN ('view', 'cart_add', 'purchase')
GROUP BY b2.ENTITY_ID
ORDER BY co_view_count DESC
LIMIT 20;

This query runs once per hour via a Bitrix agent. We cache the result in a separate table:

CREATE TABLE b_item_recommendations (
    ITEM_ID          INT NOT NULL,
    RECOMMENDED_ID   INT NOT NULL,
    SCORE            FLOAT NOT NULL,
    UPDATED_AT       TIMESTAMP DEFAULT NOW(),
    PRIMARY KEY (ITEM_ID, RECOMMENDED_ID)
);
CREATE INDEX idx_item_recs_item ON b_item_recommendations(ITEM_ID, SCORE DESC);

Personal scoring and candidate selection

From the 20 candidates, we apply a boost based on the user's favorite categories:

function getPersonalizedRecs(int $itemId, int $userId, int $limit = 8): array {
    // 1. Get candidates from item-based table
    $candidates = getCandidates($itemId, 20);

    if (empty($candidates) || !$userId) {
        return array_slice($candidates, 0, $limit);
    }

    // 2. Get categories from user history
    $userCategoryIds = getUserTopCategories($userId, 10);

    // 3. Boosting: raise products from preferred categories
    foreach ($candidates as &$candidate) {
        $sectionId = getElementSectionId($candidate['id']);
        if (in_array($sectionId, $userCategoryIds)) {
            $candidate['score'] *= 1.5;
        }
    }

    // 4. Remove already purchased products
    $purchased = getUserPurchasedIds($userId);
    $candidates = array_filter($candidates,
        fn($c) => !in_array($c['id'], $purchased)
    );

    usort($candidates, fn($a, $b) => $b['score'] <=> $a['score']);
    return array_column(array_slice($candidates, 0, $limit), 'id');
}

Caching and display

Custom component local:catalog.recommendations accepts ELEMENT_ID. The main block is cached by item_id — same candidates for all. Personal boost is applied via a separate AJAX request after page load. This gives high speed: Bitrix-level cache, minimal SQL at render. 1C-Bitrix caching documentation.

Transferring history after authorization

Bitrix does not automatically transfer anonymous behavioral history to an authorized user. We add an OnAfterUserLogin handler:

AddEventHandler('main', 'OnAfterUserLogin', function($fields) {
    $fuserId = \CSaleUser::GetAnonymousUserID();
    if (!$fuserId) return;

    $DB->Query("
        UPDATE b_user_behavior SET USER_ID = " . (int)$fields['USER_ID'] . "
        WHERE SESSION_ID = '" . $DB->ForSql(session_id()) . "'
          AND USER_ID IS NULL
    ");
});

Monitoring recommendation effectiveness

Key metric: recommendation block CTR — ratio of clicks to impressions. Baseline without personalization: 0.5–1.5%. After switching to item-based with personal boost: 2.5–4.0%. Track via purchase events and a custom click counter in localStorage or through Yandex.Metrica goals.

Additional metrics: conversion of recommended product to purchase, average order value for orders with recommendations vs. without, user return rate with repeated clicks on the block. These data help regularly adjust event weights and the analysis window to the specifics of a particular catalog.

Every quarter we review the weight configuration: if the share of short views grows, reduce their weight. If purchases concentrate in a narrow category, add seasonal boosting by product flags.

What's included in the work

• Audit of current catalog and behavioral data sources.
• Design of b_user_behavior schema and weight configuration.
• Development of SQL queries for item-based filtering and PHP logic for personal boost.
• Integration of recommendation component and AJAX handler.
• Testing on real users with CTR measurement.
• Documentation on weight configuration and support.
• Training your team to work with the system.
• 30-day warranty for correct operation after delivery.

Timelines and guarantees

Estimated timeline: 2 to 5 business days depending on catalog complexity. Time savings compared to developing from scratch: up to 40%. We provide a warranty for correct operation of recommendations for 30 days after delivery. Order a free audit of your catalog — we'll assess the possibilities.

What Professional 1C-Bitrix Installation Includes

We start by checking innodb_buffer_pool_size. The default MySQL value (128 MB) is a death sentence for an online store with a catalog of 10,000+ items. We set 70–80% of available RAM on a dedicated server, 50% on VPS. This single setting speeds up the site by 2–3 times compared to the default. We'll assess your project in one day — get a consultation. Contact us to order turnkey installation with performance guarantee.

How to Choose Hosting and Edition for 1C-Bitrix Installation?

BitrixVM is a virtual machine with a pre-installed stack: nginx + Apache, PHP-FPM, MySQL/MariaDB, Sphinx, Push server. For VPS — the best start. Everything is already configured for Bitrix, including OPcache, log rotation, and firewall. Management via web panel on port 8890. Bitrix documentation recommends starting with BitrixVM for predictable performance.

VPS/VDS is the sweet spot. Minimum configuration for a medium online store: 2 vCPU, 4 GB RAM, SSD. Optimal: 4 vCPU, 8 GB RAM. OS: Ubuntu 22.04 or Debian 12. If not BitrixVM, we configure the stack manually for the task. Virtual hosting — only for business cards and landing pages. Requirements: PHP 8.0+, MySQL 5.7+ / MariaDB 10.0+, 512 MB RAM, .htaccess. 1C-Bitrix hosting partners guarantee compatibility. Dedicated server — for highload. Typical architecture: web server separate, database separate, Redis/Memcached separate. For Enterprise edition — web cluster with load balancer. Cloud (Yandex Cloud, VK Cloud, Selectel) — when load spikes: sales, seasonal peaks. Autoscaling via Managed Kubernetes or simple VM vertical scaling.

Choosing the edition is equally important. A common mistake: choosing "Small Business" for a store that grows to B2B with wholesale prices and three warehouses in six months. Upgrading to "Business" — pay the difference, data is not lost, but it's better to plan ahead. Our specialists select the edition for current tasks and with room for growth. For example, the "Business" license (about 35,000 RUB) pays off through multi-warehouse and 1C exchange, while the wrong choice can lead to a loss of up to 30,000 RUB monthly on excess resources.

What Server Settings Are Critical for 1C-Bitrix?

Web Server and PHP

nginx as reverse proxy + Apache (mod_php) or nginx + PHP-FPM directly. The second option saves memory — Apache is not needed. But some Bitrix modules use .htaccess, so for compatibility we sometimes keep Apache. nginx configuration: fastcgi_read_timeout 300 — for long operations (1C import), client_max_body_size 1024m — large file uploads. Block access to .settings.php, .settings_extra.php, bitrix/.settings.php — they contain database passwords. Rewrite rules from urlrewrite.php — Bitrix generates them, but with nginx + PHP-FPM they need to be duplicated. PHP 8.0–8.2 with extensions: mbstring, curl, gd, xml, json, opcache, redis/memcached. Key php.ini settings: opcache.memory_consumption=256, opcache.max_accelerated_files=20000, max_execution_time=300, memory_limit=512M, upload_max_filesize=100M, post_max_size=128M.

Database and Caching

MySQL/MariaDB. Key my.cnf parameters: innodb_buffer_pool_size — 70–80% RAM, innodb_log_file_size=256M, tmp_table_size=256M, max_heap_table_size=256M, thread_pool_size — number of CPU cores. Encoding utf8mb4 mandatory, otherwise emoji and special characters break. Redis is preferable to Memcached for Bitrix — supports persistent connections and is more reliable. In production, Redis handles concurrent writes three times faster than Memcached under typical load. Configure in .settings_extra.php:

'cache' => ['value' => ['type' => ['class_name' => '\\Bitrix\\Main\\Data\\CacheEngineRedis']]]
'session' => ['value' => ['mode' => 'default', 'handlers' => ['general' => ['type' => 'redis']]]]

sudo apt install redis-server
sudo systemctl enable redis

SSL, Email, and Cron

SSL — Let's Encrypt via certbot in 90% of cases. Redirect HTTP → HTTPS (301), HSTS, TLS 1.2/1.3, OCSP Stapling. In Bitrix, switch to HTTPS in the main module settings. Email: abandon mail() — connect SMTP (Yandex.Mail for domain, Mail.ru for Business). Be sure to configure SPF, DKIM, DMARC. Without SPF, emails go to spam. Test deliverability via mail-tester.com — score 9+/10. Cron: Bitrix agents switch to system cron — * * * * * /usr/bin/php /var/www/bitrix/modules/main/tools/cron_events.php. Schedule 1C exchange (15–60 min), search reindex, backups (mysqldump + rsync, rotation 7+4), temporary file cleanup.

Security and Administration

File system: owner www-data, directories 755, files 644, upload 775. nginx blocks access to configuration files. Enable Bitrix Proactive Protection — WAF, activity control (block after 5 failed attempts), kernel integrity check. For admin panel: two-factor authentication via Google Authenticator or OTP, restrict access by IP via nginx for paranoid.

How Long Does 1C-Bitrix Installation and Configuration Take?

Post-Installation Checklist

1. Performance Monitor (/bitrix/admin/perfmon_panel.php) — aim for 30+ points. Below 20 means serious configuration issues.
2. System Check — automatic check of all parameters. Red items must be fixed, yellow — case by case.
3. Security Scanner — check for typical vulnerabilities.
4. PageSpeed Insights — TTFB < 200ms on VPS, LCP < 2.5s.
5. Test 1C exchange — if integration is planned, verify CommerceML exchange before launch.

Additionally, check software versions, caching settings, cron operation, SSL certificate, SPF/DKIM/DMARC, access rights, delete default users and pages. For projects with 54-FZ, ensure fiscalization is configured via OFD provider.

Deliverables

• Fully configured server for 1C-Bitrix with MySQL, PHP, nginx optimization.
• Installed and activated license of the required edition.
• SSL certificate, email settings, cron and backups.
• Documentation: all configuration parameters, access credentials, cron tasks.
• Content manager training: how to log into admin panel, add products, upload images.
• Post-installation support for 30 days — consultations on settings.

Why Trust Professionals with Installation?

Incorrect installation means lost time and money. We've seen projects where a store on "Start" couldn't handle 50 visitors because innodb_buffer_pool_size wasn't configured. After migrating to VPS with correct configuration, the site "flew". Incorrect configuration can cost 30,000 RUB monthly due to excessive resource consumption. You get a ready-made architecture that scales. Order turnkey 1C-Bitrix installation — get a reliable platform for business growth. Contact us for a free consultation: we'll calculate the cost and time for your project. Over 7 years of experience, 120+ Bitrix projects implemented, including highload stores with million-item catalogs. Get in touch — we'll help configure Bitrix for your project.