
The 10 most common mistakes that suppliers and manufacturers make in online retail
Online retailing is almost impossible for most retailers. The reason lies with the suppliers and manufacturers. They do not think from the retailer's perspective, which makes efficient online retail almost impossible. The reason is simple: in e-commerce, the quality and structure of the product data provided plays a decisive role in sales success. Unfortunately, mistakes are made time and again that make the integration of data more difficult, resulting in lost sales not only for retailers, but also for suppliers and manufacturers. In this article, we look at the 10 most common mistakes that are made when providing product data - and how to avoid them.
1. mistake: Unstructured provision of images and videos
A common mistake is the provision of product images and videos via cloud storage such as Dropbox, Google Drive or even FTP servers. These solutions make automated data processing considerably more difficult.
Better: Structured provision of image and video URLs
Suppliers should provide images and videos directly as URLs that can be easily downloaded from a CSV, Excel or XML file. This allows retailers to import the data automatically without having to manually search for files. Automation is crucial here, as retailers rarely have the time or resources to maintain the data manually. If retailers have to do this work, it takes longer for the products to be online - which can cost the supplier sales.
2. Mistake: Images with too low a resolution
Many suppliers provide images with insufficient resolution. However, customers expect high-resolution images in order to see the product in full detail.
Better: Provide several high-resolution images
Suppliers should provide images with a minimum resolution of 1500 pixels on the longer side, ideally even 3000 pixels. In addition, several perspectives (front, back, side view) should be covered so that customers get a comprehensive impression of the product.
3. Error: Incomplete product data in CSV files
CSV files are often not structured correctly or important fields remain empty. As a result, retailers have to add a lot of information manually afterwards.
Better: Provide all relevant data in full
Use a structured formatted CSV file with UTF-8 encoding to ensure that all special characters are displayed correctly. Every data field should be filled in and, above all, image and video URLs as well as detailed product descriptions should be stored in separate fields.
4. Mistake: No product highlights or USPs
Many suppliers fail to emphasise the most important product features or unique selling points (USPs) in a clear and structured manner. Customers want to know what makes the product special and why they should buy it.
Better: state product highlights clearly and concisely
In addition to the general description, also provide product highlights that emphasise the added value or special features of the product. These features should be clearly named and integrated into the product data. A retailer must present this prominently. This is only possible if this data is structured.
5. Mistake: Only one image instead of several views
Another problem is the provision of only a single image of a product. However, customers want several views so that they can see the product from different perspectives. In contrast to stationary retail, products cannot be touched. For a customer to want to buy, more images are needed to get an impression of the product.
Better: Provide at least three to five images
Provide several images of the product, ideally from different angles. This increases transparency for the customer and strengthens confidence in the purchase decision.
6. Mistake: Missing or incomplete product details
Many suppliers do not provide complete product details. Information such as size, material, weight or colour is often missing, which limits the filter options on the retailer's website.
Better: Provide detailed product details
All relevant product details should be provided to enable filter functions in online shops. The more information available, the easier it is for the customer to find the right product. Filtering by features such as size, colour or material is now standard in many online shops and contributes significantly to the purchase decision.
7. Mistake: Not regularly updating stock levels
Suppliers often forget to inform retailers about their stock levels or to update them regularly. This leads to misunderstandings when products are displayed as available even though they are not.
Better: Provide regular stock data
Always keep your stock data up to date to avoid shortages or excessive orders. Providing this data also enables dropshipping, where retailers sell directly to the end customer without keeping the products in stock.
8. Mistake: No possibility for automation
Some suppliers do not offer the option to retrieve their product data automatically. Retailers are then forced to process the data manually, which is error-prone and time-consuming.
Better: Enable automated data transfer
Use modern interfaces such as APIs or webhooks to transfer product data in real time. Alternatively, the data should be provided in standardised formats such as CSV, XML or JSON to enable simple and automated integration.
9. Mistake: No detailed product descriptions
Many suppliers only provide rudimentary product descriptions that lack important information. However, customers want detailed descriptions in order to understand the product.
Better: Detailed and formatted product descriptions
Make sure product descriptions are detailed and explain all the key features and benefits of the product. Use HTML to make the description visually appealing and emphasise important information.
10. Mistake: No focus on the retailer
Perhaps the biggest mistake is that many suppliers and manufacturers don't understand that it's in their own interest to make things easier for retailers. The more effort the retailer has to put into data integration, the longer it takes for the products to go online - and the fewer sales are made.
Better: retailer-friendly data provision as a sales booster
Suppliers should make the process of data provision as simple and automatable as possible. The easier it is for the retailer to integrate the product data, the faster the products can be sold. A structured approach to data provision leads to faster listings and higher sales.
Conclusion: Avoid mistakes and increase sales
By avoiding these common mistakes, suppliers and manufacturers can ensure that their products are efficiently integrated into online shops and sell better. Structured product data, automated processes and a complete, detailed description of each item are the keys to success.
For example, use our Excel template for quick and easy data submission and read our Knowledge Base entry to understand all the relevant steps. By being systematic and retailer-friendly, you will benefit from faster listings and increased sales.
Checklist for retailersHow to give your suppliers clear guidelines for the optimal provision of product data
To ensure that you as a retailer receive the best possible product data from your suppliers and can integrate it quickly and easily into your systems, we have created a checklist. You can pass this on to your suppliers to avoid misunderstandings and optimise data processing.
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Image quality and quantity
- Images must have a minimum resolution of 1500 pixels (optimally 3000 pixels).
- Provide several images from different perspectives (front, back, side view, detail shots)
- No watermarks or unnecessary backgrounds.
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Image and video URLs
- Provide images and videos as directly accessible URLs.
- Do not use proprietary cloud storage such as Dropbox or Google Drive.
- The URLs should be stored in a structured CSV, Excel or XML file so that they can be downloaded automatically.
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Product descriptions
- Provide detailed descriptions that emphasise all relevant product features and benefits
- Use HTML to format the descriptions in a visually appealing and structured way. Only use standard HTML here.
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Product highlights and USPs
- Add clear product highlights and unique selling propositions (USPs).
- Include important details that set the product apart from the competition
- Provide this data in a structured form for automatic processing
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Product details for filter options
- Include all relevant product details such as size, weight, material, colour, etc.
- This data enables the customer to filter and quickly find the product in an online shop.
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Update stock levels regularly
- If possible, provide your retailer with current stock levels or at least a traffic light display so that retailers know whether the product is available.
- Update this data regularly, especially for fast-selling items.
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Use a structured CSV file or PIM system
- Use a structured formatted CSV file with UTF-8 encoding for the provision of product data. Always adhere to the standard (RFC 4180) to avoid problems with line breaks, commas, quotation marks and similar during processing
- Alternatively, you can use a PIM system such as TYRIOS to transmit the data in real time via API or webhooks
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No use of FTP or other manually operated systems
- Do not use FTP servers with proprietary access or similar solutions that do not allow automation.
- Data provision must be automatable in order to be processed efficiently. Manual processing is not financially viable for retailers.
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Several images instead of just one
- Provide at least three to five images that show the product from different angles.
- Customers expect detailed views before they make a purchase decision