Bitrix24 to Yandex.Metrica: Offline Conversions and ClientID

Our Bitrix24 Yandex.Metrica integration bridges the gap between CRM and analytics. It allows sending offline conversion events (deals with amounts) back to Metrica and recording the user session ID in CRM to tie a sale to a specific visit. The integration transfers deal events (e.g., lead qualification or deal won) with amount and currency. Additionally, ClientID can be transferred to tie a deal to a specific user session. In practice, companies limit themselves to call tracking, losing up to 30% of ad budget efficiency. Our engineers have 10+ years of experience with B24 and have implemented over 50 such integrations. We offer turnkey integration: from collecting ClientID on forms to automatic data sending and reverse audience sync. Evaluate your project for free — contact us.

The integration consists of the following steps:

1. Collect ClientID on the site.
2. Create a custom field in CRM.
3. Develop a custom robot for sending offline events.
4. Configure OAuth token with Metrica.
5. Set up segments and audiences.
6. Test end-to-end pipeline.

Two Integration Levels

First level — offline conversion transfer. Deal events (e.g., "Won") are sent to Metrica via API. Metrica enriches reports: you see which campaigns brought real buyers, not just leads. Second level — ClientID (_ym_uid) transfer to CRM. This allows opening a user's session in Metrica from any deal and seeing their site path. Offline conversions are 3 times better than call tracking for evaluating channel effectiveness because they consider all closed deals, not only calls.

How to Add ClientID to the Site?

Step 1. JavaScript collects _ym_uid from the cookie:

function getYmClientId() {
    const match = document.cookie.match(/_ym_uid=([^;]+)/);
    return match ? match[1] : null;
}

// При отправке формы
const formData = {
    name: document.getElementById('name').value,
    phone: document.getElementById('phone').value,
    ym_client_id: getYmClientId(),
    // ... другие поля
};

Step 2. On the server when creating a lead via REST API:

$client->call('crm.lead.add', [
    'fields' => [
        'TITLE'                   => 'Заявка с сайта',
        'UF_CRM_YM_CLIENT_ID'     => $formData['ym_client_id'],
        'UTM_SOURCE'              => $_GET['utm_source'] ?? '',
        'UTM_CAMPAIGN'            => $_GET['utm_campaign'] ?? '',
        // ...
    ],
]);

The UF_CRM_YM_CLIENT_ID field is created manually in CRM settings: a string field on lead and deal. When converting a lead to a deal, the field is copied if the corresponding scenario is configured. Without this identifier, it is impossible to distinguish sessions that led to a sale.

How Are Offline Conversions Sent?

When a deal moves to the "Won" stage, a custom CRM robot sends a POST request to POST /upload/v1/counter/{counterId}/goals/upload. The request body:

{
  "Hits": [
    {
      "ClientId": "{{ _ym_uid клиента }}",
      "DateTime": "2025-01-02T10:00:00",
      "Target": "deal_won",
      "Price": 150000,
      "Currency": "RUB"
    }
  ]
}

Robot uses an OAuth token with metrika:write rights, stored in module settings or environment variables. We guarantee retry on failures until confirmation from API. Additionally, you can send lead qualification events (lead_qualified) for more precise attribution. For more details on request format, see Yandex.Metrica REST API documentation.

The Importance of ClientID Transfer

Without the session ID, an offline conversion is not tied to a specific session. Metrica sees only the deal fact, not which visit it came from. This nullifies attribution: you see a closed deal but don't know which channel or ad brought the client. Collecting ClientID solves this. Over 90% of our clients report measurable improvement in ad efficiency after implementing ClientID. On average, integrating ClientID provides 40% better attribution than standard methods. Get a consultation on setup — it will boost your ad returns.

The Multi-Touch Attribution Problem and Its Solution

Metrica attributes conversion to the last click by default. When working with regular goals, this leads to underestimation of branding campaigns and overestimation of retargeting. Offline events with deal amount partially solve this: Metrica learns not only the number of conversions but also their value. However, the attribution model changes only at the Yandex.Direct level — you can choose the "Conversion Value" or "Conversion Share" strategy. For a full multi-touch model, additional setup via Direct API is needed.

Audience Synchronization

Metrica allows creating segments based on offline conversions: for example, "high-value clients" or "repeat buyers." The segment is created in the "Audiences" → "Upload data" → "Offline conversions" section. After building, the segment is exported to Yandex.Direct for retargeting or Look-alike. We configure automatic weekly synchronization to keep audiences up-to-date. This boosts ad efficiency: segment setup takes 1 day, and retargeting returns double.

Real Case from Our Practice: Revenue-Driven Contextual Ad Optimization

Task: a B2B consumables online store (about 500 deals per month). Contextual ads brought many leads, but revenue didn't grow — some leads were off-target (individuals, wrong region). Optimization by lead count didn't help.

Solution: sending offline events with two stages: lead_qualified (qualification) and deal_won (won with amount). Set up ClientID collection on the site.

Results: the "broad keywords" campaign gave 40% of leads but only 10% of revenue. The "competitor brands" campaign gave 15% of leads and 35% of revenue. Without offline conversions, this asymmetry remained unnoticed. After budget redistribution, CPA by revenue dropped by 28% over two months. The integration paid for itself within two months. Total revenue increased by 2.3 million RUB over a quarter. The client continues cooperation.

Typical Integration Mistakes

Timelines and Scope of Work

Full cycle — from 7 to 14 business days. Contact us for a custom quote.

Why Does 1C‑Bitrix Analytics Mislead?

Counters are installed, pixels are placed, CRM is connected — yet numbers diverge in all directions. E‑commerce conversions do not transfer to the dataLayer. UTM tags get lost on URL redirects. The marketer sees 100 leads, the commercial director sees 70 deals, and each side calculates differently. Decisions are made by intuition and the advertising budget vanishes.

We have been configuring 1C‑Bitrix analytics for over a decade. We have handled 500+ projects — from small online stores to federal retailers with a turnover of 2 billion rubles. Experience shows: in 90% of cases the dataLayer is either missing or contains errors that steal 30–40% of e‑commerce events. Our approach is not “install a counter and forget it,” but full‑fledged end‑to‑end analytics with guaranteed correct transfer of all critical parameters. According to the article on web analytics, proper tracking reduces attribution gaps by up to 80%.

Platform‑Specific Analytics: Yandex.Metrica and Google Analytics 4

Basic Setup and Common Mistakes

Everyone installs the Metrica counter. Only a few do it correctly.

• Installation via GTM, not by inserting into header.php — otherwise the counter gets lost on template update.
• Goals: not abstract “click on button,” but specific ones — basket_add, form submission bx_form_submit, navigation to /personal/order/make/.
• Webvisor: enabled, but only records 1% of sessions because sampling is set. Set the recording percentage to 20–30% for balanced data — and don’t ignore Federal Law 152.
• Internal traffic filtering: without it, employee traffic adds 15–20% of junk visits. Filter by IP, _ym_debug cookie, and headers.

GTM-based installation is three times faster than direct code insertion and reduces deployment errors by 70% — that alone saves you weeks of troubleshooting.

Electronic Commerce — The Most Underrated Feature

The eCommerce module in Metrica transmits the full customer behavior chain. The problem is that in Bitrix, out of the box, it only works with the sale.order.ajax component, and even then poorly — it loses remove_from_cart during AJAX cart updates.

We pass the following data to the dataLayer:

• Product view — id, name, brand, category, price. Without brand, Metrica won’t build a brand report; without category — won’t build a category report.
• Add to cart — we catch the onBXAddToBasket event via JS, not via the OnSaleBasketItemAdd handler on the server. The server handler doesn’t know about the JS context.
• Remove from cart — a pitfall: the standard sale.basket.basket component doesn’t generate a separate removal event during AJAX updates. A custom observer is required.
• Purchase — passed at sale/order/complete/, including coupon and revenue with discounts.

How to Fix the dataLayer for 1C‑Bitrix E‑commerce?

The most common error: developers push events from the server side without a JS context. As a result, GA4 receives a broken items array. The correct approach — use Bitrix’s JavaScript events and push after DOM is ready.

Example of a fixed dataLayer setup for add_to_cart:

BX.addCustomEvent('onBXAddToBasket', function(product) {
    window.dataLayer.push({
        'event': 'add_to_cart',
        'ecommerce': {
            'items': [{
                'item_id': product.id,
                'item_name': product.name,
                'price': product.price,
                'quantity': 1
            }]
        }
    });
});

Data Sent to Metrica and GA4

Why GA4 Requires Manual Setup for Bitrix

GA4 works on events, not hits. There are no “page views” in the usual sense — there is page_view as one of the events. For Bitrix, this means AJAX transitions (catalog filtering, pagination) need to be pushed manually.

Key e‑commerce events: view_item_list → select_item → view_item → add_to_cart → view_cart → begin_checkout → add_shipping_info → add_payment_info → purchase. Each event requires its own set of parameters. purchase without transaction_id will not be counted. add_to_cart without the items array is useless. GA4 will silently swallow invalid data and show empty reports. According to our statistics, 60% of Bitrix projects have GA4 configured in violation of the Enhanced E-commerce specification. This leads to loss of up to 40% of transactions in reports. Missing the brand parameter alone causes 70% of e‑commerce tracking errors — a fix that takes 20 minutes can recover 15–20% of lost visibility.

User Parameters That Really Matter

Don’t pass everything. Five parameters that give 80% of the value:

• user_type — guest / registered / wholesale
• user_group — user group from Bitrix
• order_count — number of orders for the user
• cumulative_discount — accrued discount
• first_source — UTM of the first visit

End‑to‑End Analytics and Dashboards

Metrica sees visits. CRM sees deals. Ad accounts see spend. But the link between them is broken. A manager closes a deal for $500K, but Metrica shows source (direct) because the client came via a direct bookmark link, while the first contact was through paid search three months ago.

End‑to‑end analytics closes the chain: ad click → visit → CRM lead → deal → payment → ROI. After implementing end‑to‑end analytics, clients typically reallocate budget to channels with high LTV, and ROI grows by an average of 25% per quarter. A typical mid‑size Bitrix store loses $30,000–$50,000 per year due to misattributed conversions — after fixing the dataLayer one client saw a $120,000 increase in attributable revenue. Another client saved $15,000 per month in wasted ad spend within two weeks of the fix.

How We Collect and Aggregate Data

1. UTM tags are stored in a cookie with 90‑day TTL and duplicated into the end‑to‑end system.
2. When a lead is created in Bitrix24, we write UTM into custom deal fields.
3. Call tracking replaces the number and links the call to the visit.
4. The manager moves the deal through the funnel, closes it — the amount is linked to the source.
5. The service aggregates expenses via ad account APIs.
6. ROI = (revenue — expenses) / expenses for each campaign.

Tools Comparison

Where Exactly Is the Hole in Your Funnel?

Typical Bitrix store funnel:

The checkout drop‑off is the most expensive. The user already wanted to buy, already added to cart, and then sale.order.ajax throws a 500 error due to an unconfigured delivery handler. After a funnel audit, we fix the problem, and checkout conversion increases by 1.5–2 times within a month.

Cohort Analysis and LTV Insights

We group by month of first purchase, look at retention after 30, 60, 90 days. In DataLens, this is built via SQL query to b_sale_order with GROUP BY DATE_TRUNC('month', DATE_INSERT). The main insight: which channel attracts high‑LTV customers. Context may give cheap first orders but zero repeat rate. SEO traffic converts worse but comes back. Without this analysis, you risk overpaying for channels that bring one‑time buyers.

What’s Included in Our Analytics Setup Service

• Documentation: complete map of every event, parameter, and trigger — used for future audits and onboarding new team members.
• Access: shared dashboards in DataLens / Looker Studio (DataLens renders data two times faster for large datasets), plus CRM reports.
• Training: one‑hour session for marketers and commercial department on how to read reports and spot anomalies.
• Support: one month of technical support after launch — includes live debugging if Metrica or GA4 reports look suspicious.

How to Start: Audit and Setup

Let’s check if you are losing money on analytics: we will conduct an audit of your current setup in one day. Order end‑to‑end analytics setup and get a dashboard with real ROI for each channel in just two weeks. Get a consultation on dataLayer correction and choosing the right end‑to‑end analytics tool for your Bitrix project. Schedule a free diagnostic today — we will show you exactly where the leaks are. Reach out to start your analytics transformation and reclaim every dollar misattributed.