Harley Norrgren studied Statistics at University College London and after a two year tenure is currently heading up Infectious Media’s Analytics Team. Being with Infectious throughout their entire working relationship with RTB he’s had the opportunity to watch the space develop since the start of RTB’s European adoption.
If you’re spending large portions of your media budget on brand activity, you’ll want to ensure that you’re getting the best performance for your money, yet the effect of brand activity is typically hard to measure as it poses a few difficult questions to advertisers:
- What metrics can we use for measuring brand engagement?
- How can we get access to user level data from predominantly offline channels?
- How can we integrate cross-channel data to get a full picture of the effect of our branding spend?
It is our proposition that buying via RTB on Ad Exchanges makes brand advertising measurable and increases the accuracy of any direct response path to conversion analysis and attribution modelling. We currently create bespoke branding metrics (in conjunction with our data partners) and marginal attribution models, which help to give advertisers better insight into the effect of their brand spend and facilitate optimisation towards branding goals. These bespoke metrics are called ‘Brand Units’, and are a standardised unit of any combination of different brand measurements, such as exposure time or brand related search uplift, which can either be a proxy for conversion or reflect other incomplete path brand objectives.
Exchange generated impression level data feeds provide unique opportunities for data providers to integrate their data with unprecedented granularity. We are currently working with data partners to provide us with impression level exposure time metrics, enabling us to optimise towards advertising face time and to buy display in terms of view duration rather than per impression. The combination of engagement, search uplift and on-site activity density means that we can measure brand effect on a per user basis, rather than resorting to surveys, and optimise campaigns against these metrics in real time.
The unique user level insights generated from brand activity can be coupled with post brand engagement and ultimately conversion/post-conversion activities, allowing us to fit brand activity directly into the conversion path, as well as attribution models, providing advertisers with more insight about the path to conversion than was ever available before from a single channel.
One of the main considerations about running brand activity through exchanges is the perceived ‘remnant’ status of most inventory available. It’s important to remember that just because an impression is remnant, it doesn’t mean it’s of poor quality. Through the use of ad exposure times we can identify and optimise towards the best value Cost per Face Time inventory sources, giving advertisers more clarity and better value than direct buying could. Furthermore, the presence of private exchanges and the market wide increasing adoption of ad exchanges means that more and more ‘premium’ inventory is made available every day. Via exchange buying, adverts can be purchased on premium inventory on a per-impression basis and made measurable enough to get a stronger indication of the real value of each advert shown.
These insights represent a large step forward for a communication goal which is generally hampered by industry standard attribution models. We hope that the unprecedented feasibility of marginal attribution models and access to user level data means that more opportunities can arise for branding activity to be bought on exchanges and start to drive a shift away from historically retargeting heavy DR budgets.
