Bitrix eSputnik Integration: Code, Sync, Personalization

eSputnik is a Customer Data Platform focused on ecommerce: omnichannel chains, dynamic recommendations, abandoned cart. Integrating it with Bitrix via REST API requires understanding eSputnik's event model — without a clear data schema, synchronization quickly becomes chaotic. We have completed over 20 such integrations. Typical case: a store with 50,000 products where manual segmentation took 10 hours per week. After integration — automatic triggers and real-time personalization.

eSputnik API Features

eSputnik provides REST API v1 with Basic Auth (account login/password). Base URL: https://esputnik.com/api/v1/. Key difference from other ESPs: events as the main trigger mechanism. Instead of direct campaign management, we send events (order placed, cart updated, page viewed) — eSputnik builds automations on their own. This resembles webhooks but with its own queue and retries. Compare: manual trigger setup in MailChimp takes hours, in eSputnik — minutes.

How to Sync Contacts via REST API?

First step: API client for upserting contacts. In our code, we wrap the call in ESputnikClient class and pass channels (email) and fields (custom fields). Field IDs (id: 1, 2, 3) are taken from eSputnik account settings (Contacts → Additional fields). Important: if a field is not filled, do not pass it — eSputnik overwrites existing value with empty.

class ESputnikClient {
    private string $login;
    private string $password;
    private string $baseUrl = 'https://esputnik.com/api/v1/';

    public function upsertContact(array $contactData): array {
        $http = new \Bitrix\Main\Web\HttpClient();
        $auth = base64_encode($this->login . ':' . $this->password);
        $http->setHeader('Authorization', 'Basic ' . $auth);
        $http->setHeader('Content-Type', 'application/json');
        $http->setHeader('Accept', 'application/json');

        $payload = [
            'contacts' => [[
                'channels' => [
                    ['type' => 'email', 'value' => $contactData['email']],
                ],
                'fields'   => [
                    ['id' => 1, 'value' => $contactData['first_name'] ?? ''],
                    ['id' => 2, 'value' => $contactData['last_name'] ?? ''],
                    ['id' => 3, 'value' => $contactData['phone'] ?? ''],
                ],
            ]],
        ];

        return json_decode($http->post($this->baseUrl . 'contact', json_encode($payload)), true);
    }
}

Why Are eSputnik Events More Effective Than Standard Email Triggers?

Typical ESPs force you to manually build segments and attach campaigns. eSputnik uses an event bus: you simply send an event with parameters, and the platform decides who and when gets the email. This allows chains like "If user didn't click in recommendation email within 3 days, send SMS with coupon" without writing code on the Bitrix side. Additionally, eSputnik automatically deduplicates contacts and manages sending frequency, reducing spam risk.

Here's how we send ecommerce events:

public function sendEvent(string $email, string $eventTypeKey, array $params): void {
    $http = new \Bitrix\Main\Web\HttpClient();
    // ... auth headers

    $payload = [
        'eventTypeKey' => $eventTypeKey,
        'keyValue'     => $email,
        'params'       => array_map(fn($k, $v) => ['name'=>$k,'value'=>$v],
                          array_keys($params), $params),
    ];

    $http->post($this->baseUrl . 'event', json_encode($payload));
}

// Event: order placed
$esp->sendEvent($email, 'OrderCreated', [
    'orderId'    => $orderId,
    'orderTotal' => $orderTotal,
    'currency'   => 'RUB',
    'items'      => json_encode($orderItems),
]);

// Event: product added to cart
$esp->sendEvent($email, 'CartUpdated', [
    'cartTotal' => $cartTotal,
    'items'     => json_encode($cartItems),
]);

Case Study: Dynamic Recommendations in Emails

Situation. A sports nutrition store with 15,000 active buyers. Task: personalized emails with recommendations based on purchase history.

Implementation. We generated a product feed in XML/Google Shopping format from the Bitrix catalog and published it under a secure URL. eSputnik consumes the feed and uses collaborative filtering to select products. In the email editor, the "Recommendations" block automatically populates a selection for each recipient at open time (real-time rendering).

// /bitrix/components/custom/esputnik.feed/component.php
$products = CIBlockElement::GetList(
    ['SORT' => 'ASC'],
    ['IBLOCK_ID' => CATALOG_IBLOCK_ID, 'ACTIVE' => 'Y', 'CATALOG_AVAILABLE' => 'Y'],
    false, ['nTopCount' => 10000],
    ['ID', 'NAME', 'DETAIL_PAGE_URL', 'PREVIEW_PICTURE', 'PROPERTY_PRICE_RRP', 'PROPERTY_BRAND']
);

header('Content-Type: application/xml');
// ...

Result: CTR grew from 2.1% to 6.8% over three months. ROI was 5:1 due to automation and segmentation. Average open rate increased by 15%.

How to Set Up Product Feed for eSputnik?

The product feed is an XML file that eSputnik periodically loads for recommendations. We generate it on the fly via a Bitrix component, filtering only active and available products. Feed includes ID, name, URL, image, price, and brand. Example structure:

<feed>
  <entry>
    <id>12345</id>
    <name>Whey Gold Protein</name>
    <url>https://example.com/product/12345</url>
    <image>https://example.com/upload/iblock/abc.jpg</image>
    <price currency="RUR">1990.00</price>
    <brand>Optimum Nutrition</brand>
  </entry>
</feed>

The feed updates every 60 minutes via a Bitrix agent. eSputnik supports up to 100,000 products in the feed — for larger catalogs, we use incremental loading via API.

Contact Groups and Segmentation

eSputnik supports segmentation by contact fields and events. From Bitrix we pass fields: last order date (for reactivation), total purchase amount (VIP segment), purchased categories (thematic campaigns). Example segment: "users with more than 3 purchases totaling > 10,000 RUB in the last 90 days."

public function upsertContactWithRetry(array $data, int $retries = 3): array {
    for ($i = 0; $i < $retries; $i++) {
        try {
            return $this->upsertContact($data);
        } catch (\Exception $e) {
            if ($i === $retries - 1) throw $e;
            sleep(pow(2, $i));
        }
    }
}

What's Included

• development of an API client with recursive sync support (error handling, retries, logging)
• setup of ecommerce events: order placed, cart, product view, registration
• product feed generation with custom fields (brand, category, price)
• segment creation in eSputnik and linking to chains
• scenario testing and delivery monitoring
• system administration documentation

We guarantee correct data transmission and proper handling of all states (order cancellation, return). After handover, we remain on support — fix errors, update for new API versions.

Contact us — we will evaluate your store in 1 day and propose the optimal integration architecture. Order a pilot: we will connect one event sending and show how it works in your environment.

eSputnik API Documentation: https://esputnik.com/api/v1/docs

CommerceML: Why Standard Exchange Is Both a Lifesaver and a Trap

Standard exchange via CommerceML 2.0 on typical "Trade Management" or "Comprehensive Automation" can be set up in a day or two. Products, prices, stock, orders—all via XML files on a schedule. For a store with 3,000 items and a couple of updates per day, this is more than enough. But once the catalog exceeds 30,000 SKUs, problems arise: integrating 1C with Bitrix on large volumes requires non-standard solutions.

Why does CommerceML slow down with catalogs over 100,000 items?

bitrix_1c_exchange.php generates XML on the Bitrix side, and 1C retrieves and parses it. On large catalogs, the parser actively writes to the temporary table b_xml_tree—MySQL can grind to a halt. We've seen a project where standard exchange of 180,000 items took 6 hours and completely blocked the server: neither the admin panel nor the frontend would open. The solution is incremental exchange. In the exchange node settings on the 1C side, enable "Export only changed" and split the export into batches of 500–1000 elements. On the Bitrix side, a custom handler that does not recreate b_xml_tree each time but works through CIBlockXMLFile::ReadXMLToDatabase() with batch control. A catalog of 200,000 SKUs updates in 8–12 minutes.

Another pitfall is EXTERNAL_ID. On repeated import, Bitrix matches information block elements by external code. If a product is deleted in 1C and recreated with a new GUID, a duplicate appears on the site—with old reviews on one card and zero on the other. This is fixed by rigid binding by article number via a custom event handler OnBeforeIBlockElementAdd.

How to avoid duplicates during repeated import?

We bind products not by GUID but by article number. Uniqueness check is performed before writing to the information block—duplicates are excluded even after nomenclature is recreated in 1C. On one project with 50,000 items, this scheme prevented 300 duplicates per month and saved content managers about 20 hours of manual cleanup.

Custom 1C Configurations: When CommerceML Falls Short

"We have a standard configuration"—says every second client, and then we open the database and see 200 custom processing routines, renamed attributes, and custom sales documents. CommerceML works with a fixed XML structure. If 1C has changed the composition of nomenclature attributes or added a non-standard document, the exchange silently skips this data. Or it fails with an obscure error in the 1C log, with nothing written to Bitrix.

In such cases, we implement custom export. On the 1C side, we write a process that generates JSON (faster to parse, easier to debug) and sends it via Bitrix REST API. Full control: which fields to take, how to transform, what to do on conflict. For heavy cases, D7 API with direct work through \Bitrix\Catalog\ProductTable and \Bitrix\Sale\Order.

What are the key steps to set up 1C integration?

Custom REST is justified when:

• Non-standard nomenclature attributes;
• Multiple price types (retail, wholesale, dealer, promotional, regional, currency)—standard exchange sends only one type;
• Multi-warehouse with different stock levels and need to select a warehouse on the site.

Prices, Stock, and Multi-Warehouse

Standard exchange can transfer one price type. In reality, there may be 15: each with its own buyer group and priority. Mapping between 1C price groups and Bitrix user groups is a separate engineering challenge. Especially when discounts overlap and you need to determine which price wins.

Multi-warehouse adds another layer: product is in stock in Moscow, out of stock in St. Petersburg, and "on order" in Novosibirsk. The site must show availability per location, allow selection of pickup points, and calculate shipping from the nearest warehouse where the product is physically available. The standard Bitrix warehouse module (catalog.store) handles display, but we write the "which warehouse to ship from" logic separately. For one manufacturing holding, we implemented a custom stock aggregator that calculated balance across 8 warehouses in 2 seconds—reducing shipping errors by 80%.

Orders and Document Flow

An order from the site goes to 1C, a sales document is created, goods are reserved. Statuses come back. The main nuance is partial shipment: the client ordered 5 items, 3 are in stock, 2 will arrive in a week. 1C creates two sales documents. Bitrix out of the box cannot split one order into several shipments—we extend the OnSaleOrderSaved handler to create child orders and synchronize statuses for each.

Documents in the personal account—invoices, acts, waybills from 1C—are served via REST; PDF is generated on the 1C side and cached on CDN. The buyer downloads not from 1C directly (that would kill the server) but from cache.

Batch import with portion control reduces MySQL load and prevents locks (source: Wikipedia).

Monitoring: Not "Set and Forget"

Exchange can silently break: the script ran, no errors in log, but 200 products didn't update due to invalid UTF-8 in the name. Or 1C changed the date format in an update—all prices came in as zero.

Minimum set we install on every project:

• Telegram alert if exchange time increases 3+ times from average.
• Stock discrepancy check: script compares b_catalog_product.QUANTITY with what 1C provides, and alerts when delta exceeds 5%.
• Dashboard: last sync, number of processed items, queue, errors.

For high-load projects, we add async queues on Redis or RabbitMQ. Exchange does not block the web server, data is not lost during temporary 1C outages. On one online store with 2 million orders per year, we implemented this scheme—recovery time after failures dropped from 3 hours to 10 minutes.

Linking with Bitrix24 for Document Flow Automation

If besides the site there is a corporate portal on Bitrix24, we link it too. Counterparties from CRM go to 1C, invoices from 1C appear in deal cards. The manager sees accounts receivable and mutual settlements without switching windows. Deal closed—documents generated automatically.

Payment received in 1C → logistician gets a task for shipment in Bitrix24. Goods shipped → manager sees notification. Automatic tasks based on events from 1C—via Bitrix24 REST API webhooks. This link reduces manual entry by 70% and eliminates forgotten shipments.

How We Set Up Integration: Step-by-Step Process

1. Audit of 1C Configuration. Review the structure of directories, documents, attributes. Identify custom modifications. Assess data volume (number of SKUs, orders, warehouses).
2. Design Exchange Schema. Agree on data set: products, prices, stock, orders, documents. Determine sync interval and mechanism—CommerceML or custom REST.
3. Configure Standard Exchange. Set up CommerceML, batch mode, binding by article. Verify data transfer correctness on a test catalog.
4. Extended Integration. For complex configurations, write custom handlers on both 1C and Bitrix sides. Incorporate multi-warehouse, multiple prices, partial shipment.
5. Monitoring and Warranty. Set up alerts, dashboard, documentation. Train operators. After launch, warranty support.

Timelines and What's Included

Work results include: documented exchange schema, configured synchronization scenarios, monitoring dashboard, operator training, and warranty support after launch. Pricing is calculated individually—it depends on the complexity of the 1C configuration, catalog size, and required automation level. We'll evaluate your project in 1 day—write to us, let's discuss. Order integration and get stable exchange in 1–2 weeks.

We have completed over 50 1C integrations for online stores and manufacturing companies. The team's average experience is 7 years, and we have certified 1C-Bitrix specialists. Our experience ensures that the exchange won't break in the first month and will run stably for years. For example, on a project with a catalog of 50,000 items, automation of exchange saved the client significant operational costs annually.

Contact us for a free audit of your 1C configuration—we'll find bottlenecks and offer the optimal solution.