Earlier this month Google announced the move to First Price Auction across its Publisher exchange, joining the majority of other SSPs in First Price auction. Google’s ad exchange; Google Ad Manager is by far the largest supply side platform representing the largest share of inventory traded programmatically, so this is a significant move for the industry.
Previously when trading programmatically a buyer accessing Google’s exchange would only pay the price of the second highest bid in an auction, however in a first price auction, the buyer will pay the price of their bid even if it is much higher than the next highest bid.
Why is this important?
Current programmatic bidding strategies often include fixed bid strategies which will now have a larger influence on the resulting CPM cost. A fixed bid strategy involves bidding the same price for every impression that fits the defined targeting criteria and can result in the buyer overpaying for an impression compared to its market value. This effect is amplified by the tech fee that is charged by DSPs (typically around 8-10%) and any other commissionable fees (e.g. agency commission) which are applied on top of that bid.
In a simplified example:
Before: Bid £20 & competitors bid £10 – Pay £10.01
After: Bid £20 & competitors bid £10 – Pay £20
Consequently, there is now more emphasis on correctly valuing impressions in an auction and bidding competitively.
What are the solutions?
Many DSPs now offer dynamic bidding to offer an alternative to fixed price bidding; utilising platform algorithms to evaluate the value of an impression to a campaign. DSPs will also analyse market prices in order to bid competitively and win the impression at the lowest price possible.
Known as bid shading; this aims to optimise a programmatic campaign to deliver as many outcomes as possible for the lowest cost – most commonly this takes the form of an optimised CPM. Further solutions allow optimised bidding towards specified outcomes; e.g. Conversions, Complete Video Views, Viewable Impressions that can increase the impact of algorithmic optimisation.
This highlights the need to clearly identify relevant KPIs at the start of a campaign and capitalise on algorithmic optimisation to maximise campaign outcomes. Within our analysis a core component explores KPI frameworks to ensure agencies are;
- Planning campaigns to relevant objectives
- Configuring the DSP to help deliver KPIs
- Optimising towards selected KPIs both algorithmically and manually
Outcomes & Considerations
Implementing a dynamic bid strategy will help mitigate some of the risks of overpaying in a First Price auction:
- Cost efficiency – bidding in accordance to market & competitor levels can minimise CPMs and platform tech fees.
- Maximising outcomes – better valuation of impressions based on granular data to optimise KPI metrics.
However algorithmic bidding is not without risk, as automated bidding can increase CPM bids over time based on increasing automated bids on ‘higher value impressions’. Different definitions of a ‘high value impression’ highlight the potential risk of allowing an algorithm full control of bidding. Therefore, the focus should be ensuring there is a level of control over bid strategies to maintain CPMs and pacing at acceptable levels. Some strategies include:
- ‘Max CPM’ restrictions
- Controlled daily pacing caps
- Closely monitoring CPMs by strategy
7 Key take outs
From a client perspective, it is important to maintain relationships with programmatic teams to ensure campaigns have the best opportunity to deliver against objectives. We recommend the following;
- Clearly identify KPIs to measure success
- Assign a primary optimisation KPI and secondary KPIs where relevant
- Select DSPs, inventory & targeting strategies based on these KPIs
- Align bidding strategy to KPIs
- Utilise algorithmic optimisation (bidding) where relevant
- Define approach to CPM cost control
- Implement an optimisation framework to monitor outcomes