Dimension Focus: FW: Selling Partner
In this post we’re spending a little time with one of our most commonly used Dimensions, FW: Selling Partner.
Most of our Freewheel customers use selling partners to improve their fill rates, and so it’s a dimension that’s used constantly to understand how inventory is performing. Let’s find out a bit more about this dimension.
FW: Selling Partner
A selling partner is a body that sells your inventory on publisher’s behalf. Most likely, this is an SSP.
The names you see listed are drawn from Freewheel . You manage your resellers directly in MRM. If an ad slot was sold Direct or Programmatically, this field is left blank.
Our customers often use this dimension to create specific filtered reports per selling partner, to monitor performance.
A report showing FW Selling Partners ranked by unfilled inventory
This allows you to ensure all the opportunities you are given to that partner are fulfilled, and quickly expose differences between the performance of Selling Partners. It gives an insight into which (if any) partners are problematic at any given time.
It could be that one particular partner is blocking others from performing. By using this dimension you can see who is throwing errors, and helps make a decision on what to do about that.
Watching That Case Study:
One Watching That client recently discovered that 7.4m ad slots were going unfilled from a network I/O error. By drilling into their data by FW: Selling Partner, they could see that 7m of these were from a single partner.
The client was then able to simply refine the data by OS and then Device to discover most of this was happening on one device, and one operating system.
This information – gathered within minutes – allowed them to allocate resource immediately to tackle the problem.
Watching That Customer Success Manager, Morgan Callue’s Tip:
“Applying the FW: Selling Partner dimension as a filter in our Troubleshooting Module will allow you to drill down and see what the main error is for each individual partner. This is useful because you can quickly spot where an anomaly is taking place.”
