Spreadsheets are often the most practical place to start managing product data. Excel and Google Sheets are familiar, flexible and quick to set up. For a small catalog, one file may be enough to manage titles, descriptions, prices, images and attributes.
The problems begin as more products, suppliers, sales channels, languages and team members are added. The real threshold is rarely a fixed number of products. It is the complexity around them.
Here are seven signs that your product catalog may have outgrown spreadsheets.
Marketing edits one copy, purchasing maintains another, and the development team uses a separate export for the webshop. Each file contains slightly different information, and nobody is completely sure which version is current.
Revision histories help, but they do not keep local files, channel templates and exports aligned. When people spend more time comparing files and checking who changed what, the business no longer has one reliable product catalog. It has several competing versions of the same information.
A revised title, price or technical attribute may need to be updated in the master spreadsheet, a marketplace template, a distributor file and the webshop back end. Or maybe in the quote your colleague was just about send to that important customer.
The problem becomes clearer during bulk updates. A supplier changes part of its assortment, and the same correction has to be repeated across several files. If you want to stay up to date with your offerings, there will be no way around it.
This manual product data management slows down launches and makes inconsistencies more likely. One channel receives the new information while another continues to display the previous version.
Supplier product data rarely arrives in one consistent structure. One supplier sends a CSV file, another uses XML, and a third provides an API. Column names, product identifiers, categories and units of measurement may all differ.
Before the data can be used, someone has to clean it, map the fields and match products against the existing catalog. Spreadsheets can support this work, but the process often depends on manual steps and the knowledge of one person to read and process them.
Every new supplier then creates another custom cleanup process.
A product can have a title and price while still missing an image, category, translation or important technical attribute. The difficulty is that product completeness depends on context.
A laptop, a chair and a washing machine do not require the same information. A product may be complete for one webshop but incomplete for a marketplace with different mandatory fields.
A spreadsheet can show empty cells, but it does not understand what “ready to publish” means for every product type, language or channel.
The same product may be sold everywhere, but every sales channel does not need the same content. Shopify, Amazon, Google Shopping, regional webshops and distributors can require different fields, category mappings, images and title structures. Remember your colleague from earlier? He also needs a client specific output.
Managing multichannel product data in spreadsheets often means creating another template or export for every destination.
The goal is not to rewrite the entire catalog for every platform. It is to keep the core data consistent while adapting the output. This is also backed by all the knowledge we have about how one product description doesn’t fit for all.
A product can contain every required field and still be wrong. The price may be outdated, a dimension may use the wrong unit, an image link may be broken or a category may be incorrect.
This is different from completeness. Completeness asks whether the required information is present. Product data validation asks whether it is accurate, consistent and valid.
IBM treats these as separate dimensions of data quality. A record can therefore look complete and still cause a rejected feed, broken webshop filter or incorrect product page.
Each new supplier can introduce another feed structure, mapping process and set of identifiers. Each new sales channel adds more fields, formats and content rules.
The workload does not grow only with the number of products. It grows through the relationships between products, suppliers, categories, channels, languages and teams.
When one new source or destination creates more files, manual checks and exceptions across the entire catalog, the product data process is no longer scaling with the business.
A spreadsheet is not inherently a bad tool. It is flexible and often the right place to begin. It becomes a problem when it has to act as a product database, workflow system, quality-control tool and distribution platform at the same time.
The next step does not have to be one particular software product. The important change is moving product information into a governed central system where teams can maintain reliable records, validate data and prepare content for different destinations.
For many businesses, that system is a Product Information Management platform, like Icecat PIM. A PIM centralizes product information and supports enrichment, localization, quality control and channel-specific distribution. Spreadsheets can still be used for imports and reviews, but they are no longer the central source of truth.
The deciding factor, however, is not a fixed SKU count or a particular platform. It is whether the current process still gives the team control over its product information.
When more time goes into locating, cleaning and transferring data than improving it, the catalog has probably outgrown spreadsheets.
There is no universal product limit. A catalog containing thousands of simple, stable products may be easier to manage than a smaller catalog with multiple suppliers, frequent updates, product variants, several languages and different sales channels.
The number of relationships and manual processes around the products is usually a better indicator than the number of rows in the spreadsheet.
Yes. Excel and CSV files are still commonly used to exchange, review and import product information.
The difference is that the spreadsheet is no longer the central source of truth. A PIM or another governed product data system stores the main product records and controls how information is validated, enriched and distributed.
No. The important step is moving product information into a governed central system. Depending on the business, that may be a PIM or another platform for structured product data.
Is your current product data process becoming difficult to manage? Contact our team to discuss your setup and possible next steps.
Read further: Icecat, ecommerce, Icecat, PIM, product content
