What 2,100 3PL quotes reveal

Three years of disruption. Modest changes in quoted fees.

Tariffs, strikes, rate wars and an M&A wave. Against that backdrop, the median fees in my RFP sample moved surprisingly little.

Comparing USD quotes from 2023–24 with those from 2025–26, the largest increase among 12 fee types was the B2C order fee, up 3.6%. Additional picks rose 2.9%, pallet storage 1.4%, and account management fell 4.4%.

These are different pools of brands and providers, not the same rate cards tracked over time. Read the changes as differences between sample medians. A particular 3PL or brand may have had a very different experience.

The useful question is what those individual fees add up to for the work a brand actually needs.

Wages ran. The quoted fees walked.

The archived wage benchmark rose 7.4%, from $23.43 to $25.17 an hour. Its exact series population and averaging window have not yet been independently revalidated, so treat that comparison as provisional. The fee results reproduce: median additional-pick fees rose 2.9%, B2C order fees 3.6%, and quoted warehouse labour fees 2.6% between the two sample windows.

That is a possible source of operating pressure. It does not tell us what happened to any provider’s profit margin: productivity, order mix, occupancy, staffing and other charges also matter.

For an operator, the practical check is whether revenue from the full customer account keeps pace with the cost of serving it. A national wage series and a few fee medians cannot answer that on their own.

Same RFP. Different bids. A 22% modeled gap.

I compared quotes within each RFP using the same simplified cost model. Across 298 RFPs with at least four eligible quotes, the highest modeled cost was a median 22% above the lowest. The middle half of those highest-to-lowest gaps ran from 16% to 27%.

In 48 of the 298 RFPs, or 16.1%, the highest modeled cost was at least 30% above the lowest. Ten had a highest quote more than twice the lowest, and the largest ratio was 2.92 to one.

Those numbers come from a standardized model of B2C order fees, additional picks, quoted shipping estimates, one insert per order and pallet storage where profile inputs were available. Profiles were assigned by order-volume and SKU similarity; some assignments are approximate, and 46 RFPs use a fallback 1.9 units per order.

Receiving, monthly account fees, minimums, setup, returns and B2B work are outside this model. The result shows why bids deserve a line-by-line comparison. It does not mean every brand can save 22%, or that the cheapest modeled bid is the right operational choice.

Rents vary more than the quoted storage rates.

I compared quoted pallet-storage fees by state with asking-rent benchmarks for a main logistics metro in each state. The metro rent benchmarks range from $5.25 to $16.50 per square foot a year, a little over three to one.

Among states with at least 10 eligible pallet-storage observations, the state-level median quoted storage fee ranges from $17.82 to $21.95 per pallet a month, about 1.2 to one.

That is a narrower spread in quoted fees than in the selected rent benchmarks. But a metro asking rent is not a provider’s lease cost, and a state-level quote sample is not a matched sample of facilities in that metro.

For an operator, this is a reason to examine storage economics using their own rent, racking, occupied pallet positions and utilization. It is not a measure of how much margin a particular market leaves on the table.

The Canada file: local quotes do not simply mirror rent.

The retained dataset includes 546 CAD quotes across 682 proposed facilities. Among the Canadian cities shown here, Calgary has a median quoted pallet-storage fee of C$38.18, compared with C$23.45 in Toronto, despite a lower asking-rent benchmark.

The GTA also varies: Vaughan and Brampton have medians of C$34.66 and C$32.62, while Toronto is C$23.45. These are observations in this archive, not estimates of every warehouse’s rates in those cities.

Representation matters. The Calgary comparison contains 10 eligible storage observations, and the archived provider-count inputs identify one represented provider there. Repeat observations are not the same as a broad sample of competing operators.

Competitive intensity may help explain these differences, alongside the service mix and the providers represented. This dataset does not isolate the cause. I would use the figures to frame questions for a shortlist, not to declare one city overpriced.

An exploratory pattern: provider coverage and the price/rent index.

I also compared a storage-price/rent index with the number of distinct providers represented in each state’s RFPs. The index divides a year of quoted pallet storage by a metro asking-rent benchmark per square foot.

Across the ten included states, the relationship is negative: r = −0.69. States with more providers represented in my archive tend to have a lower index.

This is an exploratory comparison. The provider count reflects my sourcing network, not every competitor in a market. The index is not a markup or profit margin: it does not account for space per pallet, rack levels, aisle space, occupancy or operating costs.

My working hypothesis is that competitive intensity plays a role. Testing that explanation would require broader provider coverage and facility-level cost data.

The 2025–26 rate card, in one place.

Here are the median and middle-50% ranges for eligible positive USD rates quoted in 2025–26. Each fee has its own sample size; not every proposal quotes every charge.

For pallet storage, the middle half is $17.69–$21.49 per pallet a month, with a $19.32 median. For additional picks, it is $0.28–$0.44 per unit, with a $0.35 median.

Use these figures to ask better questions about a proposal. A rate outside the band may reflect different handling, volume, service requirements or another charge included in that fee. Compare definitions and the full account economics before deciding a price is high or low.