First-principles thinking for paid search and paid social advertisers.
Following the introduction of machine learning into paid media platforms, most prominently in the form of Smart Bidding in Google Ads, campaign creation and management has been simplified, this means in many instances day-to-day manual changes are often unnecessary and can be more detrimental to performance than conducive.
One of the biggest challenges that we face daily while working in paid media is being able to cut down the noise to identify what’s actually working and what isn’t.
We’re constantly swimming amongst a sea of data and metrics. It’s not just easy to get swept away from seeing opportunities, ending up down rabbit holes over optimising campaigns and reading into performance changes – it’s almost an inevitability!
Because there are so many variables involved in performance the best starting point is to cut down analysis and simplify the problem to: is this a volume or cost-efficiency problem? The way we continue to investigate each of these types of problems is very different from one another. There is always an answer to the question, things don’t just stop working for no reason, we just need to put on our detective caps and get to work on our investigation.
Building on this type of mindset gives you a robust methodology to follow and it means that whatever the specifics may be, and however frequently the ad platforms change, you get to the root of the problem and create an effective, adaptive strategy to achieve what you need to.