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# Use Shipium's Dynamic Limits to Optimize Your Carrier Volume Commitments

[Image: A portrait of Anurag Allena, a Anurag Allena from Shipium.] [By Anurag Allena](https://hub.shipium.com/content/author/anurag-allena-1)

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Updated June 5, 2025

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5 min read

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While carrier volume commitments can offer favorable pricing incentives, predictable rates, and guaranteed capacity during high volume periods, traditional approaches to meeting those limits often leave savings on the table.  
  
In this post, we’ll detail how Shipium supports the configuration of Dynamic Limits, which enable shippers to meet and reap the benefits of volume commitments while capitalizing on additional savings driven by smarter service selection.  
  
Let’s explore how.

## The problem with static limits

In most cases (and largely due to shipping technology limitations), shippers assign the "first X%" of their shipments to a specific carrier to meet a volume commitment. For instance, if their contract dictates they must send 60% of shipments to a carrier, they send the first 60%, regardless of whether that carrier offers the best rate for each package within that set of shipments.   
  
While this approach can help to meet contractual incentives, it also leads to missed opportunities for optimizing your spend.

## Enter Dynamic Limits

Put simply, Shipium enables you to configure Dynamic Limits, which are configured to send the “right X%” of your shipments to meet those crucial volume commitments, rather than the “first X%”. The benefit of this is that you can consistently hit your agreed-upon volume commitments with carriers, without overspending.   
  
Shipium’s ML modeling, in conjunction with your defined business rules, identifies the optimal set of shipments to allocate to specific carriers. Rather than relying on a static configuration, our models analyze each shipment and apply your pre-defined rules to route it optimally.  
  
Additionally, once a limit is met, the remaining shipments can be routed to whichever carrier will meet their desired delivery dates at the lowest cost. This includes the [use of non-guaranteed methods](/en/blog/using-intelligent-downgrades-to-reduce-shipping-costs-with-kibo-and-shipium), which are eligible for selection even for shipments with date constraints (our transit modeling creates an ML-powered SLA based on data from millions of historical shipments, current network conditions and more).

### Recent launch: Dynamic Limit Groups

To further support this use case, we’ve added the ability to define multiple dynamic limit groups targeted to specific shipments based on their origin. This allows for greater control and precision over shipping rules — for example, you can set separate limits for specific warehouses or postal codes, which can drive targeted cost savings if your contract dictates that specific origins must meet volume thresholds.  
  
This can also help to avoid overallocation. Rather than using a single, broad rule for volume limits, you can ensure that limits are only applied when a shipment’s origin matches your desired criteria. 

## Wrapping Up

Carrier volume commitments are a proven way to secure favorable rates and reliable capacity, but the way they’re typically met leaves further savings on the table. Shipium's Dynamic Limits directly address this challenge by moving beyond static approaches. By identifying the optimal set of shipments to meet commitments — and routing remaining shipments for the lowest cost with reliable delivery dates — Shipium helps you take advantage of every possible savings opportunity. The introduction of Dynamic Limit Groups further refines this control, allowing you to tailor strategies to specific origins.   
  
If you're looking for a way to more strategically meet carrier volume commitments, reach out to our team [here](https://info.shipium.com/demo) to discuss your use case and see Dynamic Limits in action.

[Image: A portrait of Anurag Allena, a Anurag Allena from Shipium.]

Anurag Allena Anurag Allena

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