What is Supply Path Optimization? (SPO)

Supply Path Optimization Definition

Supply path optimization, also known as SPO at a high level is the practice for a buyer of programmatic ad inventory to optimize the channels they buy impressions through as they purchase inventory. Buyers are able to utilize SPO technology to submit bids that are more likely to win the impressions through multiple pipes to a publishers inventory.

The digital advertising landscape is like a huge network of roads and highways with many routes leading to the same destination. When buyers use demand side platforms (DSPs) or Agency Trading Desks (ATDs) they are always trying to find the most cost effective, safest and transparent route to ultimately have their ad served on the publishers site, targeting the intended end user.

The fundamental issue with the ecosystem today is that there are too many different programmatic pipes leading to the same piece of ad inventory at different prices. In many cases, publishers don’t even know if ad networks, arbitragers, ad tech companies or any unauthorized parties in general are reselling their ad inventory. The rise of header bidding in general has increased inventory duplication and in some cases a buyer can access the same piece of inventory from over 30 different partners. While short term, publishers may be making more revenue by having more partners compete for the same piece of inventory, the buy side is confused, frustrated and loosing too much time and money by buying the same piece of inventory through multiple channels. In the long term, SPO will greatly benefit publishers and the ecosystem.

Supply Path Optimization Simple Example

This is where  supply path optimization comes into play, Supply Path Optimization (SPO) is both a discipline that can be practiced today and a technology that is being integrated as part of the future real time bidding (RTB) process. As a practice, DSPs will optimize their supply paths by first understanding at a high level, how many pipes they are using to access a URL.

For example let’s say DSP A is trying to buy a 300×250 banner on businessinsider.com. DSP A may work with 3 exchanges that all have a direct integration through header bidding with Business Insider and they spread their budget out across these 3 exchanges. It’s the end of the month and DSP A pulls a 30 day report and notices on average they see the following results:

  • Ad Exchange 1: $1.15 CPM and 30% Viewability
  • Ad Exchange 2: $1.30 CPM and 40% Viewability
  • Ad Exchange 3: $1.40 CPM and 70% Viewability

From here, the DSP may decide to cut spend with ad exchange 1 and 2 and only buy on ad exchange 3. Even through it is the most expensive, the increased viewability extremely important. There are other factors such as fraud score, discrepancy and others fees that could come to play in these decisions. By cutting spend with ad exchanges 1 and 2, the DSP is:

  1. 1. Reducing their overhead costs because they are submitting less bids and decreasing queries per second. (QPS) Remember, every time a DSP submits a bid, there are tech fees associated which add up quickly and lower margins.
  2. 2. Eliminating the practice of potentially bidding against them self – self explanatory.
  3. 3. Simplifying the supply chain to the end publisher.

In the future of supply path optimization, DSPs will bake in functions to their algorithms that automatically choose the best value path to a publishers inventory. With the increase adoption of ads.txt (which you can find out more in our overview here) DSPs will scan a publishers ads.txt file before bidding which will help eliminate fraud and unauthorized reselling. We are already seeing this technology being adopted and it will become a hot topic of discussion in the coming years.

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