Using automated bidding strategies can be a nice way to reduce the amount of time spent on your PPC campaigns. But the AI behind the bidding is not perfect.
A primer on artificial intelligence and its methods
Before explaining how AI pertains to online marketing, it may be helpful to clarify what some of the buzzwords related to AI mean.
AI at its simplest is when a machine can solve a problem that we perceive as something that requires a human and their special “human skills,” or cognition. Because that’s a fairly loose definition, it also means that what we think of as AI has evolved, and we no longer find it all that impressive when a computer wins at chess. Now the bar has been raised to the likes of driving a car that has no steering wheel across town in rush hour traffic. How it achieves this feat doesn’t matter for it to be considered AI.
Manually programmed AI
If you had enough time, it would be possible to create AI by manually writing a lot of code consisting of if-then statements to teach a computer what to do in every possible situation to solve a problem. In PPC-land, that would be like using a lot of Automated Rules to fully codify how your account manager goes about optimizing an account.
Machine learning is a statistical approach for finding correlations from lots of data to try to predict future events. Rather than explicitly telling the computer what to do in every possible situation, the machine teaches itself what to do based on likely possible outcomes given historical data.
Neural networks are another method for achieving AI by mimicking how we understand the human brain to work. In our brains, information is passed from neuron to neuron until we ultimately come to some interpretation of the signal. Neural networks also pass an input through many layers of processing and assign a confidence score for each level of processing.
When black box bid management sank an e-commerce campaign
An e-commerce company was using a black box bid automation system, similar to Google’s Flexible Bid Strategies, to achieve a better ROAS for their AdWords campaigns. One day they launched a new landing page design which performed much worse than expected. While they quickly noticed the decline in conversion rates, so did the black box bid system. The team restored the old version of the landing page, and conversion rates returned to their usual levels, but for some reason, the overall number of conversions didn’t come back to the same levels as before.
After many weeks of lost sales, they figured out that some of their main keywords had been bid down to page 2. Because they didn’t get enough new data to reverse the decision to lower the bid after the landing page was fixed, it never made its way back onto page one of the results.
When automated keyword mining caused a breach of contract
In another example of automation gone wrong, a company that was automating its search query mining lost comarketing dollars from a manufacturer when the system added queries with great performance as new keywords but failed to realize that these new keywords included trademarks they were contractually forbidden from using under the comarketing contract. If the system managing the automation is too simple and merely evaluates the metrics, it’s prone to make mistakes like this that a human would easily avoid.
Levels of PPC automation
Everything in the PPC account is done manually, with spreadsheets, and with tools that require all the inputs to be provided by humans.
In level 1, automations monitor and alert but take no automated action. A good example is an AdWords Script like Google’s Anomaly Detector, which scans performance of an account hourly and triggers an alert when the metrics deviate more than a set percentage from expectations.
Here, individual management tasks are automated, but there is no interconnection between the tasks. A good example of this would be an Automated Rule that runs daily and pauses any keywords that have a Quality Score lower than a set number.
This level of automation handles multiple tasks together and understands the interplay of the managed components. An example here would be a system that automates both setting bids and budgets and is smart enough to understand that when bids are raised, this may necessitate adjusting budgets to drive the most traffic to the best-performing campaigns first.
Now we’re getting into full automation, where human oversight is no longer required as long as the ads are kept within some pretty tight bounds. Imagine a vertical-specific platform where you set the goals of the campaign, like a CPA target, and a maximum budget, and because the vertical is so tightly defined, the system knows what it is allowed to do with bids, budgets, ads, keywords, targeting options and so on.
I think this is what Eric Schmidt, Google’s CEO when I worked there, would talk about during our weekly TGIF meetings. He envisioned a world where the ad system was so smart that it would know how to grow any business. A company could write a blank check to Google, knowing that they would see profitable growth as a direct result.
Any marketer who has used Google's automated PPC bidding has probably run into problems at least once. If you have a campaign that is performing well, do not mess with the good mojo by trying another landing page. Just create another campaign.