Creating product descriptions manually takes time - about 30 minutes per item. But with EAN codes and tools like TextBrew, you can cut that time to just 5 minutes per product. Here’s how it works:
An EAN (European Article Number) code is a 13-digit product identifier that acts like a digital passport for items. It provides details about the product’s origin, manufacturer, and key specifications. These codes are standardized, ensuring products are uniquely identifiable across various platforms and marketplaces.
Here’s how the digits break down:
EAN codes are essential for streamlining product content automation. They pull product information from reliable sources, which, when combined with AI, can quickly generate accurate product descriptions.
"Using EAN codes, TextBrew gathers data from Amazon, bol.com and Google Shopping and your PIM, then uses AI to create unique, optimized content following your brand guidelines."
This approach has revolutionized the way content is created. Consider the following comparison:
| Content Creation Method | Time Per Product | Products Per Hour |
|---|---|---|
| Manual Writing | 30 minutes | 2 |
| EAN-Based Automation | 5 minutes | 12 |
| Time Savings | 25 minutes | +10 |
Businesses leveraging EAN-based automation tools report impressive results:
The real strength of EAN codes lies in their ability to gather accurate product data from multiple sources. When paired with specialized tools, they eliminate manual data entry, reduce errors, and ensure consistent product descriptions across all sales channels - all while maintaining your brand’s unique tone and style.
To maximize these benefits, make sure your EAN codes are correctly formatted and verified before using them in automation systems. Proper preparation ensures high-quality results and accurate data throughout the process.
Next, learn how to prepare your EAN database for automation.
To streamline product description automation, start by organizing your EAN database. Pay attention to these key aspects when collecting EAN codes:
Your database should include the following fields for accuracy and usability:
| Field Name | Description | Example |
|---|---|---|
| EAN Code | 13-digit identifier | 4002516315155 |
| Product Name | Basic item name | Miele Complete C3 |
| Category | Primary classification | Home Appliances |
| Source | Data origin | Supplier Database |
| Status | Verification state | Verified |
Pick database tools that support features like CSV export, API integration, and data validation to ensure smooth operations. Look for solutions that offer:
Follow these management best practices to keep your database reliable:
1. Regularly back up data and maintain a consistent format to avoid discrepancies or loss.
2. Set up clear workflows for:
A carefully managed EAN database lays the groundwork for accurate and automated product descriptions using tools like TextBrew, ensuring a seamless transition to the next steps.
Once your EAN database is ready, linking it to TextBrew is simple. The platform uses EAN codes to pull product data from sources like Amazon, bol.com, and Google Shopping. Here’s how to get started:
| Input Method | Format | Best For |
|---|---|---|
| Direct Paste | Single or multiple EANs | Quick individual entries |
| CSV Upload | Bulk file with an EAN column | Managing large catalogs |
Once these settings are configured, you can fine-tune them further for your e-commerce platforms.
Different e-commerce platforms have their own requirements for product descriptions. TextBrew makes it easy to adapt your content to fit these needs:
Choose the right export format for your sales channels:
| Format Type | Features | Best Use Case |
|---|---|---|
| Clean CSV | Plain text descriptions | Basic imports |
| HTML Markdown | Formatted content | Platforms needing rich text |
| Excel Workbook | Full product data | Multi-channel distribution |
Before processing, validate your EAN codes. TextBrew’s attribute mapping system will automatically organize product details into a structured format, ensuring consistency across your catalog.
Once your EAN database is integrated with TextBrew, the next step is streamlining product processing. Bulk processing can cut down the time spent on descriptions from 30 minutes to just 5 minutes per product.
| Processing Stage | Best Practice | Impact |
|---|---|---|
| Data Preparation | Organize EANs in spreadsheets with clean formatting | Minimizes errors and saves time |
| Attribute Mapping | Set up intelligent mapping for specifications | Ensures consistent and clear structure |
| Quality Control | Validate a sample before full processing | Helps maintain high-quality outputs |
To process multiple products effectively, focus on organizing your data sources. Combining multiple sources ensures your descriptions are detailed and efficient.
While automation speeds up production, preserving your brand voice is crucial for maintaining quality. TextBrew’s voice analysis system helps align descriptions with your brand’s tone.
Here’s how to ensure consistency:
Using these settings, TextBrew can help boost SEO performance by up to 75%, all while staying true to your brand. Whether you’re crafting descriptions for tech products or lifestyle items, this approach ensures your messaging stays on point.
Don’t forget to revisit and adjust your brand voice settings as your market evolves. TextBrew’s AI can adapt to reflect your brand’s personality, creating descriptions that highlight key features while staying persuasive and consistent.
When using EAN codes to automate product descriptions, data issues can arise. Problems like missing or unrecognized EAN codes can disrupt your workflow. TextBrew helps by flagging these issues through its attribute mapping feature.
| Issue Type | Solution | Impact on Description Generation |
|---|---|---|
| Unrecognized EAN | Integrate PIM data | Ensures complete product information |
| Incorrect Format | Verify proper digit grouping | Prevents processing errors |
| Missing Data | Use multiple data sources | Creates more complete descriptions |
By combining your Product Information Management (PIM) data with EAN codes, you can produce accurate and detailed product descriptions.
Once these EAN-related issues are resolved, you can shift your focus to improving the quality of your descriptions.
After fixing EAN problems, the next step is to ensure your product descriptions meet quality standards and align with your brand's voice. TextBrew offers tools to adjust tone and structure, making it easier to maintain consistency.
"Ensure consistent brand experience with customizable tone settings across all product descriptions and marketing channels." - TextBrew
If your descriptions are falling short, review and adjust the tone settings and data inputs. This step works hand-in-hand with earlier data preparation efforts. Regular updates to your brand voice settings, especially as your product range changes, will help keep your descriptions both relevant and aligned with your brand identity.
TextBrew streamlines the process of creating product descriptions by using EAN codes, slashing production time from 30 minutes to just 5 minutes - all while maintaining quality and sticking to brand guidelines.
Here’s what the automation achieves:
| Outcome | Impact | Time Frame |
|---|---|---|
| Content Team Efficiency | Saves 80% of the time | Immediately after implementation |
| SEO Performance | Increases visibility by 75% | After deployment |
| Product Listing Speed | Speeds up deployment by 5x | During initial setup |
TextBrew pulls data from reliable sources like Amazon, bol.com, and Google Shopping, combining it with your product information management (PIM) system to generate detailed, optimized descriptions.
"Using EAN codes, TextBrew gathers data from Amazon, bol.com and Google Shopping and your PIM, then uses AI to create unique, optimized content following your brand guidelines." - TextBrew
To get the most out of TextBrew, accurate EAN code management and a clearly defined brand voice are essential. These factors are key to boosting SEO and improving engagement.
