Generating a Product Feed for Facebook/Instagram Catalog

Generating a Product Feed for Facebook/Instagram Catalog

When launching dynamic ads on Facebook and Instagram, the product catalog is most often rejected due to feed errors. Incorrect price format, missing mandatory fields, or wrong image URL — and the entire batch of products fails moderation. We have encountered this dozens of times and developed a step-by-step process that guarantees successful catalog upload on the first try. Our experience shows that even large e-commerce stores with hundreds of thousands of SKUs make the same mistakes: confusing price and sale_price, not specifying google_product_category, using HTTP instead of HTTPS. As a result, ad campaigns do not run, and the budget is wasted — a single price formatting error can cost up to $500 per day in lost ad opportunities. We offer a comprehensive service for feed generation and configuration turnkey — from auditing current data to integrating with Pixel and launching the first dynamic ads. According to Meta documentationhttps://developers.facebook.com/docs/commerce-platform/catalog/fields, the feed must be in CSV, TSV, or XML format with a mandatory set of fields.

A correctly configured feed addresses three critical issues

Meta requires a feed in CSV, TSV, or XML (RSS/Atom) format. The catalog is used in dynamic ads (Dynamic Ads), Instagram Shopping, and Shops — three different placements with partially overlapping field requirements. One error in the price or availability field format leads to the rejection of the entire batch of products during upload. Correct feed configuration solves three key problems:

• Products missing from ads — due to invalid data, the catalog is blocked.
• Low relevance — without correct fields (google_product_category, size, color), Meta cannot show products to the target audience.
• Lost conversions — if the feed is not synchronized with Pixel, dynamic retargeting does not work.

Mandatory catalog fields

Additional fields for apparel and footwear

For the Apparel & Accessories category, Meta requires:

• google_product_category — numeric ID from Google's taxonomy (Meta uses it)
• size — size (XL, 44, 42/34)
• color — color in the target audience's language
• gender — male / female / unisex
• age_group — adult / kids / newborn
• material — material (optional, but increases relevance score)

What to do if the feed is rejected?

In Commerce Manager, there is a section Catalog → Issues, where Meta shows the reasons for errors for each item. The most common problems:

• Incorrect price format: use the format 49.99 USD, without spaces before the currency code.
• Missing HTTPS: all links (link, image_link) must be HTTPS.
• Title length exceeded: truncate to 150 characters, including the variant name.
• Invalid availability: strictly use in stock, out of stock, or preorder.

We conduct a feed audit and fix all errors before uploading, guaranteeing successful moderation. In 90% of cases, one iteration is enough to resolve all issues.

CSV feed generator: 3x faster than XML

CSV is simpler to generate and debug than XML. Meta accepts both formats equally. We prefer TSV — due to commas in product descriptions, the tab delimiter is more reliable. CSV generation is 3x faster than XML, reducing load times and debugging complexity. Below is a comparison table:

Example PHP class that generates a TSV feed with product variants:

class MetaCatalogFeedGenerator
{
    private const HEADERS = [
        'id', 'title', 'description', 'availability', 'condition',
        'price', 'link', 'image_link', 'additional_image_link',
        'brand', 'google_product_category', 'color', 'size',
        'gender', 'age_group', 'sale_price', 'sale_price_effective_date',
    ];

    public function generate(string $outputPath): void
    {
        $file = fopen($outputPath, 'w');
        // BOM not added — Meta does not require it, may break parser
        fputcsv($file, self::HEADERS, "\t"); // TSV more reliable than CSV due to commas in descriptions

        Product::with(['images', 'category', 'brand', 'variants'])
            ->where('is_active', true)
            ->chunk(200, function ($products) use ($file) {
                foreach ($products as $product) {
                    foreach ($this->expandVariants($product) as $row) {
                        fputcsv($file, $row, "\t");
                    }
                }
            });

        fclose($file);
    }

    private function expandVariants(Product $product): array
    {
        if ($product->variants->isEmpty()) {
            return [$this->buildRow($product, null)];
        }

        return $product->variants->map(
            fn($variant) => $this->buildRow($product, $variant)
        )->toArray();
    }

    private function buildRow(Product $product, ?ProductVariant $variant): array
    {
        $id    = $variant ? $product->sku . '-' . $variant->sku : $product->sku;
        $price = $variant?->price ?? $product->price;
        $stock = $variant?->stock ?? $product->stock;

        $additionalImages = $product->images->skip(1)
            ->pluck('cdn_url')
            ->take(9) // Meta allows up to 10 images
            ->implode(',');

        $salePrice = '';
        $salePriceDate = '';
        if ($product->sale_price && $product->sale_ends_at > now()) {
            $salePrice = number_format($product->sale_price, 2, '.', '') . ' USD';
            $salePriceDate = $product->sale_starts_at->toIso8601String()
                . '/' . $product->sale_ends_at->toIso8601String();
        }

        return [
            $id,
            mb_substr($product->name . ($variant ? ' ' . $variant->name : ''), 0, 150),
            strip_tags($product->description),
            $stock > 0 ? 'in stock' : 'out of stock',
            'new',
            number_format($price, 2, '.', '') . ' USD',
            route('products.show', $product->slug) . ($variant ? '?variant=' . $variant->id : ''),
            $product->mainImage()?->cdn_url ?? '',
            $additionalImages,
            $product->brand?->name ?? '',
            $product->google_category_id ?? '',
            $variant?->color ?? $product->color ?? '',
            $variant?->size ?? '',
            $product->gender ?? '',
            $product->age_group ?? 'adult',
            $salePrice,
            $salePriceDate,
        ];
    }
}

Configuration in Business Manager

After generating the feed:

1. Commerce Manager → Catalog → Data Sources → Add Data Feed
2. Specify the feed URL or upload the file manually
3. Choose an update schedule: hourly, daily, or manual
4. Assign the catalog to ad accounts

Meta provides error diagnostics in the Catalog → Issues section — each problematic item is marked with a reason description. A feed upload with more than 5% errors will result in the catalog being rejected for advertising.

Pixel + Catalog for dynamic retargeting: 30-40% lower CPA

For Dynamic Ads, a feed alone is not enough — you need to set up the Meta Pixel with events:

// Product page
fbq('track', 'ViewContent', {
  content_ids: ['SKU-44231'],
  content_type: 'product',
  value: 49.99,
  currency: 'USD',
});

// Add to cart
fbq('track', 'AddToCart', {
  content_ids: ['SKU-44231'],
  content_type: 'product',
  value: 49.99,
  currency: 'USD',
});

content_ids must exactly match the id field in the catalog — otherwise matching does not work. Catalog-based retargeting can reduce customer acquisition cost by an average of 30-40%.

Process and what's included

We offer turnkey feed configuration — with 5+ years of experience and 50+ successful projects:

1. Current catalog audit — we check structure, mandatory fields, data errors.
2. Feed creation — we write a generator for your CMS or ERP, configure TSV/CSV/XML.
3. Testing — we upload a test batch, check in Meta Issues.
4. Pixel integration — we add ViewContent, AddToCart, Purchase events.
5. Deployment and monitoring — we set up auto-update, provide access to reports.

As a result, you get a working catalog, a correct feed, and configured retargeting. We guarantee first-time moderation pass — 95% of all errors are fixed in one iteration.

Contact us for a free evaluation of your catalog. Order feed setup, and we guarantee successful upload on the first try.

Timeline

Feed generator + data source setup in Business Manager — from 3 to 5 business days. Pixel integration and dynamic retargeting testing — another 2 to 3 business days. Exact timelines depend on catalog size and integration complexity.

We will evaluate your project for free. Contact us to get a consultation and cost estimate.

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

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

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.