Thousands of hours are wasted every month across departments searching for content in scattered servers and folders, leading to outdated product information and costly errors. Managing product data at scale requires accuracy, consistency, and efficiency. Without these pillars, teams face endless manual processes that slow operations and impact sales.
This guide covers essential Excel formulas to consolidate, validate, analyze, and automate product data, helping you structure information effectively while avoiding common pitfalls.
Managing product data often involves pulling information from multiple sources—supplier catalogs, internal databases, and sales channels. Keeping everything aligned is critical.
Importing product data from multiple suppliers into a unified format.
Matching images and descriptions across sheets.
Ensuring accurate pricing across sales channels.
XLOOKUP: A more flexible alternative to VLOOKUP.
Example
=XLOOKUP("P123", A2:A100, B2:B100)
Finds the product name for SKU “P123.”
INDEX + MATCH: A powerful lookup combination.
Example:
=INDEX(D2:D100, MATCH(1, (A2:A100="P123") * (B2:B100="Electronics"), 0))
Retrieves the price for SKU "P123" in the Electronics category.
FILTER: Extracts multiple matching records dynamically.
Example:
=FILTER(A2:D100, B2:B100="Electronics")
Filters all products in the Electronics category.
CONSOLIDATE: Merges data from multiple sheets. Go to Navigate to Data > Consolidate. > Choose the function (SUM, AVERAGE, etc.) and then Select reference ranges from multiple sheets.
Ensuring data accuracy reduces errors in product listings, sales channels, and internal reports.
Verifying that all mandatory fields are filled (e.g., missing descriptions or images).
Ensuring SKUs follow a standard format.
Identifying duplicate records before updates.
COUNTIF: Detects missing product descriptions.
=COUNTIF(B2:B100, "")
Counts empty product descriptions.
ISNUMBER + SEARCH: Ensures correct SKU prefixes.
=ISNUMBER(SEARCH("EL-", A2))
Returns TRUE if SKU contains “EL-.”
To remove duplicates, select the dataset, navigate to Data, and choose Remove Duplicates. For data validation, which restricts entry formats, select the column, go to Data, click Data Validation, and set the desired rules.
Summarizing stock levels, tracking trends, and identifying gaps in product data help improve decision-making.
Generating category-wise sales reports.
Identifying low-stock items.
Summarizing product availability.
SUMIF: Calculates total stock per category.
=SUMIF(B2:B100, "Electronics", D2:D100)
AVERAGEIF: Finds the average price per category.
=AVERAGEIF(B2:B100, "Electronics", C2:C100)
Pivot Tables dynamically summarize stock levels and sales trends. To create one, go to Insert, select PivotTable, and drag fields into rows, columns, and values as needed.
Standardizing product names, SKUs, and descriptions ensures uniformity across sales channels.
Extracting key details from SKUs.
Formatting product names consistently.
Fixing incorrect measurement units.
PROPER: Capitalizes product names.
=PROPER(A2)
LEFT, MID, RIGHT: Extracts SKU components.
=LEFT(A2, 3)
SUBSTITUTE: Replaces incorrect text entries.
=SUBSTITUTE(A2, "cm", "mm")
Automating flagging and validation processes helps streamline workflows.
Identifying low-stock items.
Flagging missing images before publishing.
Highlighting incomplete records.
Essential Formulas:
IF: Flags low-stock items.
=IF(D2<50, "Reorder", "Sufficient")
AND + OR: Identifies incomplete records.
=IF(OR(B2="", C2=""), "Incomplete", "Complete")
Conditional Formatting: Highlights missing descriptions.
Excel is a familiar tool for managing product data, but as your catalog grows, it can slow you down. Structured formulas and validation rules help, but they don't eliminate inefficiencies.
When it's time to scale, a centralized solution like Sales Layer keeps your product data accurate, enriched, and ready for every sales channel. With built-in workflows, collaboration tools, and automated syndication, your team can work smarter and avoid Excel headaches.