Modelling digital advertising costs across platforms
Digital marketing is often suggested to be a science rather than an art because of the data that it provides. We set out to discover exactly how true that is. Can we really commoditise human behaviour? Can we place people into interest categories and know exactly what they’ll buy next? And if not, how close can we get?
We investigated this by analysing benchmarks for the main advertising platforms. The platforms don’t publicly report this information. This means that consultants, digital marketers and investors are left to search elsewhere to understand how well their campaigns are performing.
The companies able to provide the best data are ad-tech platforms that manage and oversee millions of pounds of advertising for their clients. When they release their figures publicly, the information is readily shared. But these leave a number of begging questions: Are they consistent? How much do they change over time? Do they add more confusion than clarity?
We aggregated and analysed the most influential benchmarking studies. Our aim was not to find one all-encompassing figure for each metric. Instead, we were looking to understand the consistencies between them, and equally, the inconsistencies.
The resulting data provides clear strategic takeaways for entrepreneurs, marketers, and investors. These can be categorised into two groups. The first covers the fundamentals that all advertisers can use to guide budgets allocations and improve campaign performance. The second presents the additional strategies used by the most successful advertisers.
This research includes
11 pages of analysis (4,500 words).
Data tabulated and comparable from multiple benchmarking studies.
Multiple metrics e.g. CPC, CPM and CVR
The main platforms and inventory types.
Strategic takeaways for campaign optimisation.