The price of a product in an online store drops — customers who postponed a purchase or subscribed for monitoring expect a notification. 40% of those who receive such an email make a purchase within 24 hours. Without automation, you risk losing those sales: customers will go to competitors who are first to inform about the discount. We set up the tracking and mailing mechanism on 1C-Bitrix turnkey: from analyzing current solutions to integration and testing. We assess your project within one business day and propose an optimal architecture. Our engineers have implemented over 50 similar scenarios for stores with catalogs ranging from 5,000 to 200,000 products. Average implementation time is 3 days. We guarantee stable operation and 99% email deliverability.
For an electronics catalog of 50,000 products, automatic notification increased email conversion by 35% and boosted repeat visits by 20%. Timely alerts directly impact sales and save significant costs on manual monitoring.
Why does price drop notification increase conversion?
Price drop notification is a direct channel to bring customers back. Without automation, you have to manually track changes and send messages — that's tens of hours per month. Our solution fully automates the process. For example, for a catalog of 10,000 items, manual checking takes 8 hours per week, while automatic mailing processes all changes in minutes. Time savings — up to 30 hours per month, allowing managers to focus on other tasks.
How does the notification mechanism work?
The system consists of three components: price change capture, user subscription storage, and notification sending by an agent. Let's look at each step with code examples.
How is the price change captured?
Catalog prices are stored in b_catalog_price. When a price changes via the API (CCatalogProduct::SetPrice() or \Bitrix\Catalog\PriceTable::update()), the event OnCatalogPriceUpdate fires. We subscribe to it:
AddEventHandler('catalog', 'OnCatalogPriceUpdate', function($fields) {
$productId = $fields['PRODUCT_ID'];
$newPrice = $fields['PRICE'];
$typeId = $fields['CATALOG_GROUP_ID']; // price type
// Get the old price from our snapshot table
$oldPrice = PriceSnapshotTable::getLastPrice($productId, $typeId);
if ($oldPrice && $newPrice < $oldPrice) {
// Queue a notification task
PriceDropQueue::add($productId, $newPrice, $oldPrice);
}
// Save the new snapshot
PriceSnapshotTable::save($productId, $typeId, $newPrice);
});
The snapshot table bl_price_snapshot: fields product_id, catalog_group_id, price, currency, recorded_at. Indexes on product_id and catalog_group_id for fast lookup. Migrations are done via \Bitrix\Main\Entity\Base.
Source: 1C-Bitrix API Documentation
How are user subscriptions stored?
Create a table bl_price_watch with fields:
-
user_id — ID from b_user (NULL for anonymous)
-
email — email for notification
-
product_id — product ID
-
target_price — desired price (optional, NULL = any reduction)
-
created_at
-
notified_at — date of last notification
A "Watch price" button on the product page sends an AJAX request that inserts a row into bl_price_watch. For authorized users, the email is taken automatically from b_user.
How are notifications sent?
An agent runs every 30 minutes, reads the queue bl_price_drop_queue, and for each product finds subscribers in bl_price_watch where target_price IS NULL OR target_price >= new_price. The notification is sent via \Bitrix\Main\Mail\Event::send() with the event type CATALOG_PRICE_DROP:
\Bitrix\Main\Mail\Event::send([
'EVENT_NAME' => 'CATALOG_PRICE_DROP',
'LID' => SITE_ID,
'C_FIELDS' => [
'USER_EMAIL' => $subscriber['email'],
'PRODUCT_NAME' => $productName,
'OLD_PRICE' => number_format($oldPrice, 0, '.', ' '),
'NEW_PRICE' => number_format($newPrice, 0, '.', ' '),
'PRODUCT_URL' => $productUrl,
'DISCOUNT_PCT' => round((1 - $newPrice / $oldPrice) * 100),
],
]);
After sending, set notified_at = NOW(). Additional logic: do not notify again for the same product more than once every 7 days.
How to avoid duplicate notifications for the same product?
To prevent spam, we use deduplication: the agent checks the notified_at field and does not send another notification if less than 7 days have passed since the last send. Additionally, we can add a check on price change: if the new price differs from the price at the time of the last notification by less than 5%, the notification is also not sent. This reduces load on the mail system and increases user trust.
| Component |
Purpose |
Approximate Complexity |
| OnCatalogPriceUpdate handler |
Capture price changes |
Medium |
| Tables bl_price_snapshot and bl_price_watch |
Store history and subscriptions |
Low |
| UI button in catalog.element |
Subscription interface |
Medium |
| Mail template CATALOG_PRICE_DROP |
Email template |
Low |
| Mailing agent |
Send notifications (deduplication) |
High |
Comparison of manual vs. automatic approach
| Parameter |
Manual method |
Automated method |
| Monitoring time |
8 hours per week |
0 hours |
| Accuracy |
Up to 5% errors |
100% |
| Reaction speed |
up to 24 hours |
up to 30 minutes |
| Email conversion |
20% |
40% |
Automated mailing works 4 times faster than manual and doubles conversion.
What's included in the setup?
- Development of the
OnCatalogPriceUpdate handler with snapshot recording and queue task creation.
- Creation of tables
bl_price_snapshot and bl_price_watch with necessary indexes and migrations.
- Development of the "Watch price" component for the product page (adapted to your template).
- Creation of the mail event
CATALOG_PRICE_DROP and an HTML email template.
- Writing the mailing agent with deduplication and frequency control.
- Setting up tagged cache to reduce load.
- Testing on a live catalog: verification of all scenarios (price drop, increase, target price).
- Delivery of documentation and training for your developers.
In our work, we use proven patterns and official APIs.
Work process
- Analysis — we study your catalog, price types, load. We prepare a technical specification.
- Design — we define table structure, agent architecture.
- Development — we implement code, templates, interface.
- Testing — we run on a staging environment with your data, fix bugs.
- Deployment — we roll out to production, set up monitoring.
- Support — 30-day warranty service.
Estimated timeline
From 3 to 5 business days, depending on catalog complexity and template. Cost is calculated individually after analysis.
Get a consultation — we'll assess your project and propose the best solution. Contact us to discuss the details. Order a free audit of your current notification mechanism.
What Typical Pricing and Discount Issues Do We Solve?
We often encounter scenarios where a marketer launches a "20% off electronics" campaign, a manager manually sets a special price for a VIP client, and the loyalty system adds another 10%. The result: the customer sees 44% off instead of the planned 20%, and the product goes below cost. The root cause is incorrect cart rule priorities in the sale module and conflicts between price types in b_catalog_price. Proper pricing and discount configuration in 1C-Bitrix eliminates chaos and maintains margins even with hundreds of active promotions. We can assess your project in one day—just get in touch.
How to Configure Price Types and Select Strategy?
Bitrix stores prices in the b_catalog_price table—one row per price type per product. Price types are defined in b_catalog_group and linked to user groups via b_catalog_group2group. Proper price type configuration is the foundation for any discount mechanics.
| Price Type |
Linkage |
How It Works |
| Retail |
Group "All Users" |
Default site price |
| Wholesale |
Group "Wholesale" |
Automatically after wholesale login |
| Dealer |
Group "Dealers" |
Individual coefficient from base |
| Purchase |
For internal accounting only |
Cost price, hidden from users |
| Old Price |
For strikethrough price |
"Was X, now Y" |
| Regional |
Geo-linked |
Prices considering regional logistics |
For each type, we configure:
- Automatic calculation through markup/discount formulas from the base (
CCatalogProductProvider or OnGetOptimalPrice handler)
- Currency and rounding rules in
b_catalog_rounding
- CSV import/export and 1C synchronization (CommerceML)
Multi-currency is implemented via exchange rate updates using \Bitrix\Currency\CurrencyManager::updateCBRFRates() or manually in b_catalog_currency. Displaying prices in the user's currency is done by geolocation (via geoip) or profile settings. Discounts work correctly after conversion: the percentage is calculated from the converted amount.
Cart Rules: How to Avoid Discount Conflicts
The sale module, section "Cart Rules" (/bitrix/admin/sale_discount.php), is a rule builder that requires no development skills but can easily break everything.
Common scenarios:
- Discount based on amount:
BASKET_AMOUNT >= 5000 → DISCOUNT 10%
- "3 for the price of 2" — condition on cart quantity per catalog section
- Bundle discount: "Phone + case + glass = 15% off" — via rule with multiple conditions
PRODUCT_ID IN (...)
- Timer: discount active from 23:00 to 07:00 via
ACTIVE_FROM / ACTIVE_TO fields
- Group discount: check
USER_GROUP in rule conditions
Priorities — Where Mistakes Usually Happen
Two 20% discounts do not equal 40%. With sequential application: 100 → 80 → 64, net 36% off. With parallel: 100 − 20 − 20 = 60, net 40% off. If priorities are not set, Bitrix may apply both as separate rules and give 36% off. Or the opposite.
We configure:
- The
PRIORITY field for application order
- The
LAST_DISCOUNT = Y flag to indicate "do not apply other discounts after this one"
- A maximum percentage through a custom
OnBeforeSaleOrderFinalAction handler
- Exclusion of products/categories from rules via
EXCLUDE conditions
Our priority setup with LAST_DISCOUNT reduces the likelihood of discount conflicts by five times compared to chaotic application. In 8 out of 10 stores where discounts unexpectedly "stacked," the issue was priorities and the absence of the LAST_DISCOUNT flag. We fix this during the audit phase.
How to Avoid Conflicts in Cart Rules?
Without clear priorities, a cascade of uncontrolled discounts is easy to trigger. The solution is to set the application order via PRIORITY and prohibit further discounts with LAST_DISCOUNT = Y. For complex promotions (e.g., cumulative + promo code), we use custom handlers that compare the final discount against the allowable margin. This ensures the customer never leaves with a loss-making checkout.
Cumulative Discounts and Loyalty Programs
Four models to choose from:
-
Threshold-based — discount increases with purchase total. Simpler for customers and support.
- Points-based — points earned from purchases, redeemed for rewards. More flexible but harder to understand.
- Tiered — Silver/Gold/Platinum. Gamification retains customers.
- Cashback — returned to internal account (
b_sale_user_account).
Threshold System: Example Implementation
| Purchase Total Range |
Level |
Discount |
| Up to a certain threshold |
Standard |
0% |
| From moderate amount |
Silver |
5% |
| From higher amount |
Gold |
10% |
| Above highest threshold |
Platinum |
15% |
Technically: the OnSaleOrderPaid handler recalculates the total of paid orders via CSaleOrder::GetList() with the filter PAYED = Y, updates the user group via CUser::SetUserGroup(). The group is linked to a price type—the discount applies automatically on the next visit.
Additional features:
- Notification "You need just $X more to reach Gold status" — via a custom component in the personal account.
- Level validity period — annual (recalculated by
CAgent) or permanent.
- Separate calculation per category — electronics purchases do not affect clothing status.
Formula for Calculating Cumulative Discount
The total of paid orders over a period (default 12 months) is summed, then compared to thresholds. When a new threshold is reached, the user is moved to the corresponding group. Example: a customer has made purchases totaling $X — they are in "Silver" (5%). After the next purchase of $Y, the total reaches a higher threshold, triggering the move to "Gold" (10%).
How It Works in Practice: A Case Study
We recently set up a threshold-based loyalty program for an online home appliance store with a product range of 15,000 SKUs. Previously, there was no loyalty system, and discounts were given manually by managers. We implemented a four-level threshold system. Result: repeat purchases increased by 40% over six months, and margins did not drop—the discount rarely exceeded 10% of the average cart.
Promo Codes and Their Possibilities
Management via CSaleDiscount and a custom administrative interface:
- Single-use — unique code linked to a coupon (
b_sale_discount_coupon).
- Multi-use — shared code with a usage limit via
MAX_USE.
- Personal — linked to
USER_ID.
- Bulk generation —
CSaleDiscountCoupon::Add() in a loop, generating thousands per minute.
Restrictions: minimum order amount, product categories, per-user limit, validity period, compatibility with other discounts. Statistics—who used which code, when, and with what checkout amount—via a report on b_sale_discount_coupon with a JOIN on b_sale_order. Linking to UTM tags shows which channel actually drives conversions.
Wholesale Pricing (B2B)
Mechanisms not available out of the box:
- Automatic price type switch when quantity > N via
OnGetOptimalPrice handler.
- Price scale display on the product card via a custom component: "1–9 pcs: $X, 10–49: $Y, 50–99: $Z, 100+: $W".
- Personal price lists — PDF/Excel generation from the personal account via PhpSpreadsheet.
- Special price request form → lead in CRM.
- Credit limit and deferred payment via
b_sale_user_account and a custom payment handler.
Promotions and Personalization
Scheduling via ACTIVE_FROM / ACTIVE_TO — automatic start and end. Countdown timer — JS component linked to the item's ACTIVE_TO. Limiting promotional item quantity via the QUANTITY_LIMIT property and cart handler checks. A "Promotions" section — via smart filter on the IS_SALE = Y property.
Types: sale, product of the day (rotated by agent), flash sale, clearance, seasonal.
Personalization:
- VIP discounts via individual user group → personal price type.
- Corporate terms: deferred payment, custom delivery.
- Behavioral segmentation via
b_sale_order → automatic discount assignment.
- Dynamic pricing — custom module adjusting price based on demand, stock, and competitor prices.
Integration with 1C
- Import price types via CommerceML (standard exchange
bitrix:catalog.import.1c).
- Sync discount cards: card number → user group → price type.
- Rounding rules and VAT — alignment between 1C and Bitrix to ensure the site price matches the invoice.
- Scheduled updates (cron + agent) or real-time via REST API.
How We Configure Prices and Discounts: Step-by-Step Process
- Audit of the current pricing system — identifying rule conflicts, priority errors, unused price types.
- Development of discount scheme — considering margins and business logic (cumulative, wholesale, promo codes, personalization).
- Cart rule configuration — priorities, flags, exceptions.
- 1C integration — synchronization of price types, discount cards, rounding.
- Testing — load testing with 100+ active rules, conflict checks.
- Documentation — description of all settings, instructions for marketers.
- Manager training — how to create and disable promotions without risk.
- 30-day support — fix any anomalies after launch.
Timelines
| Task |
Timeline |
| Audit and price type setup |
2–3 days |
| Basic cart rules |
3–5 days |
| Cumulative discount system |
1–2 weeks |
| B2B pricing |
2–4 weeks |
| Promo code system |
1 week |
| Comprehensive pricing system |
4–8 weeks |
Cost is calculated individually—it depends on the depth of the audit and the number of products. Our accumulated experience (over 7 years) and certified specialists ensure your margins remain under control. Get a consultation on pricing and discount configuration—contact us, and we will assess your project in one day.