What dynamic freight matching operators know (and will soon find out) about the impacts of false positive matches on DFM operations and the customer experience.


Over the last several months, the team members at DFM Data Corp have had deep conversations with the leadership from many of the 200+ companies providing dynamic freight matching services (DFMs). After learning more about their businesses, we typically first walk them through the ideas surrounding our solution to eliminate replicated load and capacity data from the truckload spot market. As the dialogue progresses, the conversation naturally shifts to the question of the impacts replicated loads and capacity is having on their operations and customer experience.


Most have a clear sense that there is a problem—the presence of replicated loads and capacity in their open DFM marketplaces, platforms or load boards is causing false-positive matches; and it isn’t good for business.

The problem takes on many names: Phantom data, ghost data, duplicated, replicated, non-comm, fake, annoying, etc., but DFM operators sense a real and growing concern within their businesses.  Their datasets are polluted with a constant presence of postings that show as available, but in fact have already been booked on another DFM platform or marketplace.  Equally evident is that DFM business leaders don’t have a practical way of identifying which postings can be booked and which can’t.  It is instinctively known that this kind of data problem cannot be optimized out—and that this is surely impacting profits.

Confirmed shipping orders that are later determined to actually NOT be confirmed (in many cases, several hours later) means lost productivity and unhappy customers.  Back end customer support resources are then required to remedy the situation and smooth things over with the customer. The fix can require numerous phone calls and emails to fully resolve.

The challenge for that shipper-customer is that they made a decision to utilize one of the new breed of dynamic freight service providers because of their promise of faster, more reliable freight services at a lower cost than a traditional provider. Yet, if it is common to experience delays, phone calls and emails, then what they had expected to be an efficient, automated service, must now feel a lot like the customer experience they receive from traditional freight service providers.

The challenge for DFMs and their investors is that their core business models are all about utilizing big data technologies specifically designed to provide operational efficiencies that are otherwise not achievable. DFMs, of course, cannot be 100% automated services. There will always be a need for human beings to provide customer service and to handle exceptions, which will always be a critical part of healthy customer relationships. But… the efficiency goal of more revenue per seat than traditional operators achieve, is limited by the impacts of phantom data.


Surprisingly, our conversations with DFM operators also have revealed that while they know phantom data is costing them, they don’t know HOW MUCH it is costing them. Along with the perception that there is no way to identify replicated data before the false-positive match, very few DFMs have looked into the impacts to their operations. The over-arching decision is to focus their resources on what is considered to be “SOLVABLE” problems. 


Fortunately, DFM Data Corp. really is prepared to identify replicated data before the false-positive match occurs and eliminate phantom data from the entire market. Our approach will also finally provide the ability to provide an accurate index on true capacity in the truckload spot market – in real time.


To help individual DFMs to get a quick read on the impacts of phantom data on their operations, we have sponsored the creation of survey designed for a DFM to give to their brokers and agents as well as to their shipper and carrier customers.

We provide the survey and findings reports at no charge. 

The 5 minute survey is designed to clarify and quantify:

  • Incident rates of false positive matches
  • Booking delays and cancellations
  • Lost deals
  • Lost customers
  • Labor costs / operational efficiency
  • Customer relationships / loyalty / repeat business
  • Job performance / satisfaction
  • Primary causes of phantom data pollution
  • Perceptions of the reasonable cost to remedy the phantom data problem


Here is a link to the survey. http://sgiz.mobi/s3/National-Phantom-Data-Survey-s. You’ll see how the methodology is sampling perceptions of those directly experiencing the impacts themselves.

The survey is being deployed nationally as well as by individual companies. When we meet our participation goals for the national survey, we will publish the results. We will also provide reports to participating companies that will compare the impacts of phantom data on their operations with the national average. We anticipate being able to report national findings in Q1 2021.

Just ask and we’ll prepare a custom branded version of the survey ready for your use in as little as one business day. For more information about utilizing the survey contact:

David Wolff

CMO / VP of Marketing and Communications




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