How to Modify Product Data to Meet Retailers Requirements

For brands who want to increase online sales in marketplaces and drop ship programs, one of the biggest pain points is modifying product data to meet each retailer’s unique and specific requirements. Each retailer requires different product specifications to align with their systems, including image size and shape, background color, and descriptions such as the number of characters, specific attributes and formatting – making sure all relevant categories are filled correctly. The issue here is providing a scalable solution for managing multiple integrations that does not require hiring an in-house team. 

Data Points

Knowing the right data fit for each retailer and aligning your product descriptions to meet specifications requires immense manual work which is simply not scalable.

Let’s take Walmart as an example. Here you’ll see what is needed for EACH and EVERY product. This includes the:

• Product Name
• Description
• Key Features

Here are some examples of what should NOT be included specific to Walmart. 

Product Name

Do not include:

• Information about yourself or your company, except for the product’s brand name
• Any special characters
• Retailer-specific information about the product
• Any sales information
• Product attributes
• Marketing phrases
• Any verbiage referencing other marketplaces such as:

Key Features

Do not include:

• Any special characters
• Any sales information
• Unproven, vague marketing phrases
• Any verbiage referencing other marketplaces such as:

Description

Do not include:

• Any special characters
• Any sales information
• Unproven, vague marketing phrases
• Any verbiage referencing other marketplaces such as:
• Any offensive verbiage

Along with updating each product description, any change in product information will need to be updated and pulled regularly to combat gaps in product information, including sale prices and inventory amounts. 

Our automation platform is able to adjust the descriptions and titles to meet retailer specifications, including required colors, bullets, material care and instructions.

According to each product’s specifics, multiple images and angles may also be necessary, such as numerous images of a shoe – with a frontal view, side view, etc. Each retailer has its own requirements, and with Neiman Marcus, their format is through choice boxes.

With each retailer requiring different product data arrangements, it provides little room to grow digital channels quickly. Also, with current manual processes, there is a lot of space for human error. The great thing about working with Cymbio is that all product data is fulfilled automatically, so you can worry less and grow more.

Wrap up

With the need to scale digital sales fast, many brands can no longer afford to rely on creating gigantic excel sheets, which leave a lot of room for error. With in-house teams required to manage these excels, they are not scalable. When optimizing time to market, finding the right automation tool is an absolute must. As growth on new retail channels is essential and managing tens, even hundreds of retail partners and thousands of products, all of which are required in different formats – there is absolutely no way this can be fulfilled efficiently at scale.