How to Collect Product Data for Your Fulfillment RFP

You know you need to document product characteristics for your fulfillment RFP. Dimensions, weight, fragility, storage requirements, handling needs. The framework is clear.

But when you sit down to actually compile this information, the questions start:

Who internally has this data? Do I measure products myself or pull from existing systems? What if we have been fulfilling in-house and never documented any of this? What if our product data is scattered across multiple spreadsheets, inconsistent, or just plain wrong?

Collecting product data is not glamorous work. But it is foundational. The accuracy of your RFP responses depends on the accuracy of your product data. If you understate fragility, you will get inaccurate pricing. If you overstate dimensions, you will pay for storage space you do not need. If you miss special handling requirements, you will discover them during onboarding — when they are expensive to fix.

This is the tactical playbook for actually gathering product characteristics before you run your RFP.

Start With What You Already Have (Even If It Is Incomplete)

Most brands have some product data somewhere. It might be incomplete, inconsistent, or out of date — but it exists.

Before you start measuring products or interviewing teams, audit what you already have.

Where Product Data Usually Lives

Ecommerce platform (Shopify, WooCommerce, BigCommerce)

• Product dimensions (length, width, height)
• Product weight
• SKU identifiersProduct names and descriptions

Why this matters: Your ecommerce platform has dimensions and weight because shipping carriers require it. This is your starting point. Export a product catalog and use it as your base template.

Why this might be wrong: Many brands enter dimensions and weight that are estimates, rounded, or copied from the manufacturer without verification. Dimensions might be product-only, not packaged. Weight might exclude packaging materials. Use this data as a starting point, not as gospel.

Inventory management system (NetSuite, Cin7, Fishbowl)

• SKU data

• Product attributes (color, size, material)

• Units per case

• Storage location codes

Why this matters: If you have an inventory management system, it likely has more detailed product attributes than your ecommerce platform. It may also have historical data on how products are stored (shelf vs. pallet, individual vs. case pack).

Why this might be wrong: Inventory systems track what is in stock, not necessarily how it should be handled. Storage location codes are based on your current warehouse layout, which may not reflect what a 3PL needs to know.

Shipping software (ShipStation, ShipBob, Easyship)

• Package dimensions (as shipped)

• Package weight (as shipped)

• Shipping method distribution (parcel vs. freight)

Why this matters: Shipping software has real-world data on how products actually ship. This is often more accurate than ecommerce platform data because it reflects what your current operation does, not what someone guessed during product setup.

Why this might be wrong: Package dimensions in shipping software reflect your current packaging choices, which may not be what a 3PL will use. If you over-package for protection or under-package to save costs, a 3PL may do it differently.

Product development or merchandising files

• Technical drawings

• Manufacturer specifications

• Sample product images

• Packaging design files

Why this matters: If your product or merchandising team has spec sheets from manufacturers or designers, these often include precise dimensions, materials, and packaging requirements. This is especially true for custom products or private label goods.

Why this might be wrong: Manufacturer specs are for the product itself, not necessarily how it should be stored or shipped. A ceramic mug might have exact dimensions, but the spec sheet will not tell you it requires bubble wrap.

Audit Your Existing Data Quality

Once you have pulled data from these sources, do a quick quality check:

• Completeness: Do you have dimensions and weight for every SKU, or are there gaps?
• Consistency: Are units consistent (all inches, or a mix of inches and centimeters)?
• Accuracy: Spot-check 5-10 products. Do the listed dimensions match the actual packaged product?
• Recency: When was this data last updated? If it is two years old and you have changed packaging, it is stale.

If your data passes this quality check, you have a solid foundation. If not, you need to fill gaps.

Who Internally Should Own Product Data Collection

Product data collection is cross-functional. No single person has all the answers.

Operations or Warehouse Manager (Primary Owner)

Why they matter: If you currently fulfill in-house, your operations or warehouse manager knows how products are actually handled every day. They know which products break easily, which require extra care, which ship in their retail packaging versus secondary boxes, and which create handling bottlenecks.

What to ask them:

• Which products require special handling or extra care during picking and packing?
• Which products are frequently damaged in fulfillment?
• Which products take longer to pack than others, and why?
• Are there any products that require two people to lift or special equipment to move?
• Which products ship in retail packaging versus plain boxes?
• Do any products require inspection before shipping (QC for defects, checking for leaks, etc.)?

What they will provide: Real-world operational context that no spec sheet captures. They will tell you that Product X is technically "standard fragility" but customers complain about damage, so it needs extra bubble wrap. Or that Product Y has dimensions that make it awkward to pack, so it takes twice as long as similar-sized items.

Product or Merchandising Team (Secondary Input)

Why they matter: Product teams have manufacturer specifications, technical drawings, and design intent. They know material composition, how products are meant to be used, and any specific presentation or branding requirements.

What to ask them:

• Do we have manufacturer spec sheets with exact dimensions and materials?

• Are there any specific packaging or presentation requirements (must ship in branded boxes, must include tissue paper, etc.)?

• Are any products temperature-sensitive or have humidity requirements?

• Do any products have regulatory or compliance requirements (FDA, USDA, hazmat)?

• Are there any upcoming product changes that will affect fulfillment (new packaging, new sizes, discontinuations)?

What they will provide: Accurate dimensions, material details, and forward-looking information about product changes. They can also flag products with special requirements (food-grade storage, temperature control, fragile materials) that operations may not track formally.

Customer Service Team (Valuable Context)

Why they matter: Customer service sees damage complaints, packaging complaints, and quality issues. They know which products generate the most post-shipment problems.

What to ask them:

• Which products have the highest damage or complaint rates?
• Do customers ever complain about packaging (over-packaged, under-packaged, wrong presentation)?
• Are there products that frequently arrive late or have shipping issues?
• Do any products generate questions about storage or handling (damaged seals, expired products, broken components)?

What they will provide: Customer-facing reality checks. If customers frequently complain that a product arrives damaged despite your operations team calling it "standard handling," that is critical information for a 3PL.

Finance or Inventory Planner (Data Validation)

Why they matter: Finance and inventory planning teams often have clean, consolidated data on SKU counts, velocities, and costs. They can validate that your product list is complete and that you have not missed SKUs.

What to ask them:

• Can you provide a complete list of active SKUs (products we actually sell, not discontinued items)?

• Which SKUs represent 80% of order volume?

• Are there seasonal SKUs that only ship part of the year?

• Which SKUs are highest value and need extra care?

What they will provide: A definitive SKU list and velocity distribution. This prevents you from spending hours documenting a product that ships twice a year while missing a hero product that ships 1,000 times per month.

How to Measure Products Yourself (When Existing Data Is Not Enough)

If your existing data is incomplete or inaccurate, you need to measure products yourself.

This is tedious. But it is also the only way to ensure your RFP data is accurate.

What You Need to Measure

For each product (or representative products if you have many similar SKUs), document:

Product dimensions (as stored)

• Length x width x height
• Measured in inches or centimeters (be consistent)
• Measure the product in its storage-ready state (in retail packaging if that is how it is stored, or loose if it is stored unboxed)

Product weight (as stored)

• Weight in pounds or ounces

• Include all packaging that will be stored with the product

Packaged dimensions (as shipped)

• Length x width x height of the shipping box or poly mailer

• Include all protective materials (bubble wrap, air pillows, paper fill)

Packaged weight (as shipped)

• Total weight including box, product, and all packing materials

Fragility and handling notes

• Does it break easily? (glass, ceramics, electronics)
• Does it require orientation (This Side Up)?
• Does it need protective materials beyond a standard box?
• Can it be stacked, or must it be stored flat?

Special requirements

• Temperature or humidity needs
• Expiration date tracking
• Lot number or serialization
• Any regulatory or compliance requirements

Tools You Need

• Tape measure or ruler (for dimensions)
• Digital scale (for weight; a kitchen scale works for small items, a shipping scale for larger items)
• Spreadsheet template (to record measurements consistently)
• Photos (take a photo of each product in storage state and shipping state)

How to Measure Efficiently

If you have fewer than 20 SKUs: Measure every product individually. Be precise.

If you have 20-100 SKUs: Measure every hero product individually (products that represent 80% of volume). For low-velocity SKUs, group similar products and measure representative samples.

If you have 100+ SKUs: Measure hero products individually. Create product categories (small apparel, large apparel, fragile glassware, standard household goods) and measure 2-3 representative samples per category. Note which SKUs belong to each category.

For products with variants (colors, sizes): If a t-shirt comes in 10 colors but dimensions are identical, measure one and note "applies to all colors." If sizes vary, measure each size.

Document Handling Reality, Not Just Specs

As you measure, pay attention to handling reality:

• Does the product feel fragile, even if it is not technically glass? (Thin plastic that dents easily, lightweight items that shift in boxes)

• Is it awkward to pick or pack? (Odd shapes, heavy for their size, requires two hands)

• Does it need to be packed a certain way? (Orientation matters, must be separated from other items)

Write these observations down. They are as important as dimensions.

What If You Are Still In-House and Do Not Have Formal Data?

Many brands fulfill in-house without ever formalizing product data. Products live in Shopify with rough dimensions. The warehouse team "just knows" how to handle things. There is no formal documentation.

This is common. It is also fixable.

Start With a Working Session

Block two hours with your warehouse or operations lead. Bring a laptop, a scale, a tape measure, and your product catalog.

Walk the warehouse floor together. For each product (or product category), measure and document:

• Dimensions and weight (as stored and as shipped)
• Where it is currently stored (shelf, pallet, floor)
• How it is currently packed (box type, protective materials)
• Any special handling the team does (but may not have formally documented)

Take photos. Capture the tribal knowledge before it is lost.

Build a Simple Product Profile Template

You do not need a complex system. A simple spreadsheet works:

SKU, Product Name, Dimensions (L x W x H), Weight, Fragility, Storage Notes, Packaging

This is enough. You can refine later.

Prioritize Hero Products First

If you have limited time, focus on the products that represent 80% of your order volume. Measure and document those precisely.

For low-velocity products, create categories and document representative samples. A 3PL can work with "similar to SKU-005" for a product that ships twice per month.

Accept That Some Data Will Be Estimated

If you are still in-house and have never tracked kitting frequency, you will not have a precise percentage. Estimate conservatively.

"Approximately 20% of orders include gift messaging" is better than nothing. "Roughly 30% of orders are multi-SKU" gives a provider useful context, even if it is not exact.

Providers can work with estimates. They cannot work with silence.

How to Organize and Present Product Data in Your RFP

Once you have collected product data, organize it clearly for your RFP.

Option 1: Product Profile Spreadsheet (Recommended)

Attach a spreadsheet with one row per SKU (or SKU category) and columns for:

• SKU identifier
• Product name
• Dimensions (as stored)
• Weight (as stored)
• Dimensions (as shipped)
• Weight (as shipped)
• Fragility level (low, medium, high)
• Storage requirements (ambient, climate-controlled, refrigerated, frozen)
• Special handling notes
• Monthly velocity (units shipped per month)

This format is scannable and easy for providers to import into their estimating tools.

Option 2: Product Categories with Representative Samples

If you have 100+ SKUs, group them into categories and provide detailed profiles for representative samples:

Category: Standard Apparel

• Representative SKU: T-Shirt (Medium)
• Dimensions: 12" x 8" x 2" (folded)
• Weight: 0.6 lbs
• Fragility: Low
• Packaging: Poly mailer
• SKUs in this category: 45

This approach works when products within a category are operationally similar.

Option 3: Attach Photos

Include photos of products in storage state and shipping state. Label each photo with the SKU identifier.

Photos eliminate ambiguity. A provider can see that your "standard apparel" is heavyweight denim jackets, not lightweight t-shirts. They can see that your "fragile glassware" is thick restaurant-grade glasses, not delicate stemware.

Photos also help providers spot handling challenges you may not have articulated (awkward shapes, items that nest together, products that require orientation).

Common Mistakes When Collecting Product Data

Relying Only on Ecommerce Platform Data

Shopify dimensions are often wrong. They are estimates, copied from suppliers, or entered quickly during product setup. Do not assume they are accurate.

Spot-check. Measure a sample of products and compare them to Shopify data. If there are discrepancies, measure more.

Measuring Products Without Packaging

A ceramic mug is 4" x 4" x 5" and weighs 1 lb. But when you add bubble wrap and a shipping box, it becomes 6" x 6" x 7" and weighs 1.5 lbs.

3PLs need to know packaged dimensions and weight, not product-only. They are storing and shipping boxes, not loose products.

Skipping Low-Velocity SKUs

It is tempting to document only hero products and ignore the long tail.

But low-velocity SKUs often have the most complexity. They are the odd sizes, the special-order items, the products that require custom handling. If you skip them, you will miss operational complexity that affects pricing and provider fit.

Document at least representative samples of every product category, even if individual SKUs are low-velocity.

Forgetting to Update Data After Product Changes

You measure products, run your RFP, and select a provider. Six months later, you change packaging or launch new products.

Product data is not static. If you make changes that affect dimensions, weight, fragility, or handling, update your documentation and notify your 3PL. Surprises create friction.

Product Data Collection Is Foundational Work

Collecting product data is not exciting. It is measuring boxes, filling spreadsheets, and walking warehouse floors with a tape measure.

But it is also the foundation of an accurate RFP. Providers cannot quote accurately on bad data. They cannot assess capability fit without knowing what they are handling. They cannot plan space allocation, labor, or packaging without understanding your products.

The time you invest in collecting accurate product data upfront eliminates surprises, inaccurate pricing, and misaligned expectations later.

Start with what you have. Fill the gaps. Measure what matters. Document the reality, not the ideal.

Your RFP will be better for it.