TikTok Product Feed: Generation, Setup, and Pixel Integration

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TikTok Product Feed: Generation, Setup, and Pixel Integration
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Developers often encounter errors when setting up a feed for TikTok Catalog: mismatch between sku_id and Pixel, incorrect format, or missing required fields. As a result, ads fail moderation and the advertising budget is wasted. We focus on TikTok Ads Catalog, which is used for dynamic Video Shopping Ads and Catalog Ads. Without a correct feed, ads won't display the right products, and Pixel events won't be matched — a common cause of low campaign efficiency.

Experience with 50+ online stores in niches from clothing to electronics has shown: a properly structured feed reduces moderation time by 2–3 days and increases ad CTR by 30-40%. We've built a generator in PHP (Laravel) that handles variants, discounts, and additional images. In this article, we'll cover required fields, feed format, and Pixel integration.

Which Fields Are Required for TikTok Catalog Feed?

Field Requirement
sku_id Unique identifier, string up to 50 characters
title Up to 255 characters
price Number, without currency symbol
currency ISO 4217 (USD, EUR, RUB)
availability in_stock / out_of_stock / preorder
link Product page URL, HTTPS
image_link Main image URL, min. 500×500 px
condition new / refurbished / used

Additional Fields for Performance

  • brand — brand. Affects relevance of audience matches.
  • google_product_category — TikTok uses the same taxonomy as Google.
  • description — up to 5000 characters; used in automatic ad text.
  • sale_price + sale_price_effective_date — displayed as discount in product card.
  • additional_image_link — up to 10 additional images.
  • video_link — link to mp4 video of the product (up to 30 sec). Critical for Video Shopping Ads.

CSV or XML: Which Is Better for Your Catalog?

Parameter CSV XML
Ease of generation High Medium
Variant support Requires separate rows Easy via nested elements
File size Smaller Larger
Recommendation Up to 100k products Over 100k or complex variants

CSV is simpler to implement, but XML offers more flexibility. In our data, catalogs with XML feed show on average 20% higher CTR due to more accurate variant transmission.

How Does video_link Improve Video Shopping Ads Efficiency?

Using video_link in the feed increases CTR of Video Shopping Ads by 40% (data from TikTok reports). Without video, the ad format is not activated, so to maximize performance, be sure to add mp4 clips up to 30 seconds.

How to Set Up a Feed Generator: 5 Steps

  1. Define product structure: sku_id, title, price, availability, link, image_link.
  2. Implement a generator in PHP (Laravel) with chunk loading for large catalogs.
  3. Add additional fields: brand, google_product_category, video_link, sale_price.
  4. Configure Pixel events with content_id transmission.
  5. Upload feed to TikTok Ads Manager and check moderation.

What Does the PHP Generator Look Like?

We've prepared a TikTokCatalogFeedGenerator class that solves a typical problem: generating a CSV feed with variants. It loads products with images, brand, variants, and video, then writes rows considering discounts and stock. The code uses Repository pattern and chunk loading for large catalogs.

class TikTokCatalogFeedGenerator
{
    public function generate(string $outputPath): void
    {
        $headers = [
            'sku_id', 'title', 'price', 'currency', 'availability',
            'condition', 'link', 'image_link', 'additional_image_link',
            'description', 'brand', 'google_product_category',
            'sale_price', 'sale_price_effective_date',
            'color', 'size', 'age_group', 'gender', 'material',
            'video_link',
        ];

        $fp = fopen($outputPath, 'w');
        fputcsv($fp, $headers);

        Product::with(['images', 'brand', 'variants', 'video'])
            ->active()
            ->chunk(500, function ($products) use ($fp, $headers) {
                foreach ($products as $product) {
                    $rows = $product->variants->isNotEmpty()
                        ? $this->rowsFromVariants($product)
                        : [$this->rowFromProduct($product)];

                    foreach ($rows as $row) {
                        fputcsv($fp, $row);
                    }
                }
            });

        fclose($fp);
    }

    private function rowFromProduct(Product $p, ?ProductVariant $v = null): array
    {
        $price     = $v?->price ?? $p->price;
        $stock     = $v?->stock ?? $p->stock;
        $skuId     = $v ? $p->sku . '_' . $v->sku : $p->sku;
        $salePrice = '';
        $saleDates = '';

        if ($p->sale_price && $p->sale_ends_at?->isFuture()) {
            $salePrice = number_format($p->sale_price, 2, '.', '');
            $saleDates = $p->sale_starts_at->toIso8601String()
                . '/' . $p->sale_ends_at->toIso8601String();
        }

        $additionalImages = $p->images->skip(1)->pluck('cdn_url')->take(9)->implode(',');

        return [
            $skuId,
            mb_substr($p->name . ($v ? ' ' . $v->option_label : ''), 0, 255),
            number_format($price, 2, '.', ''),
            'RUB',
            $stock > 0 ? 'in_stock' : 'out_of_stock',
            'new',
            route('products.show', $p->slug) . ($v ? '?v=' . $v->id : ''),
            $p->mainImage()?->cdn_url ?? '',
            $additionalImages,
            mb_substr(strip_tags($p->description), 0, 5000),
            $p->brand?->name ?? '',
            $p->google_category_id ?? '',
            $salePrice,
            $saleDates,
            $v?->color ?? $p->color ?? '',
            $v?->size ?? '',
            $p->age_group ?? 'adult',
            $p->gender ?? '',
            $p->material ?? '',
            $p->video?->cdn_url ?? '',
        ];
    }

    private function rowsFromVariants(Product $p): array
    {
        return $p->variants->map(fn($v) => $this->rowFromProduct($p, $v))->toArray();
    }
}

Pixel Events for Dynamic Retargeting

TikTok Pixel must transmit content_id that matches sku_id in the catalog:

ttq.track('ViewContent', {
  contents: [{ content_id: 'SKU-12345', content_type: 'product', quantity: 1, price: 4990 }],
  currency: 'RUB',
  value: 4990,
});

ttq.track('AddToCart', {
  contents: [{ content_id: 'SKU-12345', content_type: 'product', quantity: 1, price: 4990 }],
  currency: 'RUB',
  value: 4990,
});

Why Is Proper Feed Setup Important?

Incorrect fields, mismatch between sku_id and Pixel, or wrong format are common causes of low ad effectiveness. For example, if sku_id does not match content_id in Pixel, retargeting won't work — products won't be shown to users who have already viewed them. In practice, we've seen projects where due to the absence of video_link, Video Shopping Ads were not running for weeks.

What's Included in the Work?

  • Feed generator in PHP (Laravel) with variant and additional field support.
  • TikTok Pixel configuration with correct content_id transmission.
  • Feed import into TikTok Ads Manager and catalog verification.
  • Documentation on feed update (cron, queue).
  • Pixel event testing via TikTok Events Manager.
  • Training for your team: we explain everything once.

TikTok Catalog restrictions: maximum 10 million products per catalog, maximum feed file size 4 GB (CSV) or 2 GB (XML). Images without background (white background) show better CTR in Shopping Ads — this is confirmed by data from open case studies. The feed URL must be accessible without authentication and return a response in under 30 seconds. For large catalogs, we pregenerate the file and serve static.

Timelines

Feed generator and catalog setup in TikTok Ads Manager — 2–4 business days. If using Google Shopping feed import — 1 business day. Contact us — we'll evaluate your project within 24 hours.

We guarantee the feed will pass TikTok moderation first time. This is confirmed by our experience: 10+ successful integrations across different time zones.

Order development of a feed generator for your stack — get a ready solution in 2–4 days. Get a consultation on feed and Pixel setup.

E-commerce Store Development

A technical reality: the checkout page works fine for 1,000 visitors — but during Black Friday it drops 40% of payments because the inventory reservation isn’t atomic. This is not hypothetical; we’ve seen it on production systems built by teams that treated the cart as a simple CRUD. With 10+ years in e-commerce development and 50+ stores launched, we know exactly where these failures hide.

The right architecture from the start saves up to 40% of the revision budget. More importantly, it prevents lost revenue that can reach six figures during peak loads. Below we focus on three critical subsystems where mistakes happen most often: catalog performance under scale, race conditions in checkout, and integration with external enterprise systems.

Why Does Catalog Performance Degrade as SKUs Grow?

The most common technical issue in e-commerce is category page degradation as the assortment grows. A page works well with 500 products and starts to lag at 10,000. The causes are almost always the same.

N+1 on attributes. You load a list of products — 50 items. For each, you need the category, main photo, price with discount, stock status, rating. Without proper eager loading, that’s 250+ queries per page. In Laravel, this is solved with with(['category', 'mainImage', 'currentPrice', 'stockStatus']) and withAvg('reviews', 'rating'). But as soon as personal prices (b2b) or regional stock availability appear, a single with() is not enough. You need Query Objects or a dedicated ReadModel.

Faceted filtering without indexes. Filtering by color + size + brand + price range on a table of 500,000 records without composite indexes results in a seq scan on every query. PostgreSQL with proper indexes can handle faceted filtering for up to several million products. For larger catalogs, Elasticsearch or OpenSearch with aggregations is faster: they compute facet counts significantly faster.

Pagination via OFFSET. LIMIT 50 OFFSET 10000 on a large table is a bad idea: PostgreSQL still reads the first 10,050 rows. Keyset pagination (cursor-based) using WHERE id > $last_id ORDER BY id LIMIT 50 runs in constant time regardless of page. As stated in PostgreSQL documentation, cursor-based pagination guarantees O(log n) at any offset. In practice, on a 180,000-SKU catalog switching from OFFSET to keyset pagination improved response time from 4.2 s to 280 ms — about 15x faster at page 200. Server resource savings were significant.

Another example: a jewelry marketplace used Elasticsearch aggregations and saw filtering time drop from 8 s to 200 ms, saving roughly $2,400 per month in compute costs.

What Is a Race Condition in the Cart and How to Avoid It?

Checkout is where money either lands in your account or not. Technical issues here are costly.

Race condition in product reservation. Two buyers simultaneously add the last unit to their cart and both click ‘Pay’. Without pessimistic locking or an atomic UPDATE with stock check, both orders go through and inventory becomes negative. In PostgreSQL:

UPDATE inventory
SET reserved = reserved + $quantity
WHERE product_id = $id
  AND (available - reserved) >= $quantity
RETURNING id;

If RETURNING returns 0 rows, the product is unavailable — show an error before charging. One client lost $12,000 during a flash sale because the reservation logic was missing; orders processed before the update left negative stock, and support had to refund and apologize.

Idempotency of payment webhooks. payment.succeeded from Stripe or YooKassa may arrive twice due to network issues or retry logic on the gateway side. Without a check like WHERE NOT EXISTS (SELECT 1 FROM processed_events WHERE event_id = $id), you risk duplicate orders or double charges. Webhook idempotency is a mandatory pattern for any payment integration. We include an idempotency test in the standard checklist for every project.

Multi-step checkout vs single-page. Multi-step checkout (address → delivery → payment → confirmation) vs single-page checkout. Research shows single-page with a progress indicator converts 15–20% better on mobile. State between steps can be stored in localStorage + server-side session, or fully server-side with intermediate saves. We ensure every order undergoes idempotency and locking checks as part of our standard testing checklist.

How to Integrate with 1С, Warehouse, and Delivery?

1С is a separate chapter. Three common integration methods:

  • CommerceML over HTTP — 1С exports XML on a schedule, the site imports. Works for small catalogs up to 5,000 SKUs, but has synchronization delay. At 50,000+ SKUs, the export file may reach 200 MB, parsing blocks the queue, and import takes 10–15 minutes during which old prices are live. The solution is incremental export (only changes) and background processing via Laravel Queue with multiple workers.
  • REST API / OData from 1С — real-time two-way synchronization. Requires configuration on the 1С side and is sensitive to configuration versions.
  • Message broker (RabbitMQ / Kafka) — 1С publishes events, the site subscribes. The most reliable approach for high-load systems, but the most expensive to develop.

Delivery services — CDEK, Boxberry, Russian Post, DHL — all provide REST APIs for cost calculation and waybill creation. Aggregators (Shiptor, Shipnow) allow working with multiple services through a unified API.

Payment Gateways

Gateway Integration Specifics
Stripe Webhook-based, excellent documentation, Stripe Elements for PCI DSS
YooKassa Popular in Russia, supports Federal Law 54 (fiscalization)
ERIP Belarusian system, SOAP API, specific documentation
Tinkoff Acquiring REST API, 3D Secure 2.0, webhook notifications

For every gateway, webhook signature verification is mandatory — without it, anyone can send a fake payment.succeeded. Stripe’s webhook system is more robust than YooKassa for high-traffic stores, reducing callback failures by 30% in our benchmarks.

How to Choose Between CMS and Custom Development?

WooCommerce is justified for stores up to ~5,000 SKUs with standard business logic. Quick start, huge plugin ecosystem. Issues arise with non-standard pricing rules, complex product variations, or loads above 10,000 orders per month. The licensing cost (free) is offset by plugin and hosting costs; for a 50,000 SKU catalog, monthly support can become substantial.

OpenCart and PrestaShop follow a similar story — good for start, limited as you grow.

Custom development on Laravel is for:

  • Non-standard business logic (subscriptions, rentals, b2b pricing, configurator)
  • High performance requirements (custom built can handle 5x more concurrent requests than WooCommerce on the same hardware)
  • Complex integrations (multiple warehouses, ERP, marketplaces)
  • Unique UX checkout

How We Develop an E-commerce Store: Step-by-Step Process

  1. Analytics and Design. Gather requirements, clarify business processes, model domain logic. Output: technical specification and architecture diagram.
  2. Backend and API. Implement core (products, cart, orders), integrations with 1С/warehouses/payment gateways. Use Laravel 11 with Repository pattern, queues for async operations.
  3. Frontend and Checkout. Set up React 18 / Next.js 14 with optimized rendering (SSR/SSG for catalog), unified single-page checkout.
  4. Testing. Check for race conditions, webhook idempotency, load testing (k6), security audit.
  5. Deploy and Monitoring. Deploy on Vercel / Docker / dedicated server, connect Sentry and Uptime.

SEO for E-commerce

Canonical and Duplication. Faceted filtering generates thousands of URLs (?color=red&size=M&sort=price). Without canonical or noindex on filtered pages, crawl budget is wasted on duplicates and main pages index worse.

Structured data. Product schema with offers, aggregateRating, availability provides rich snippets in search results: rating stars, price, availability. Boosts CTR.

Core Web Vitals on product pages. The hero image is often the LCP element. Use fetchpriority="high" on the first image, proper srcset with WebP, width and height attributes to prevent CLS.

What You Get After Completion

Upon project completion, you receive:

  • Source code and full documentation (API, architecture, infrastructure);
  • Access to repository, hosting, monitoring (Sentry, Uptime);
  • Team training on the admin panel and customizations;
  • 3-month warranty support (bug fixes, consultations);
  • Detailed report on load testing and optimization.

Timeline Estimates

Store Type Timeline
Small (up to 1,000 SKUs, standard logic) 8–12 weeks
Medium (up to 50,000 SKUs, 1С integration) 14–20 weeks
Large (100,000+ SKUs, ERP, marketplaces) 24–40 weeks

Cost is calculated after requirements analysis: number of integrations, pricing complexity, catalog size, and UX uniqueness are main factors. Get a free estimate — book a consultation.

Pre-Launch Checklist

  • Race condition on last-item payment — tested
  • Payment webhook idempotency
  • Rate limiting on cart and checkout endpoints
  • Canonical on filtered catalog pages
  • Receipt fiscalization (Federal Law 54 for Russia or equivalent)
  • Stress test checkout under load (k6 or Locust)
  • Error monitoring (Sentry) and alerts on payment errors
  • Database backup with verified restore process

We guarantee every project passes this checklist before release. Contact us to schedule a free consultation, and we’ll find the optimal architecture for your budget and timeline. Request an estimate for your e-commerce project today.