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Manual PPC bidding versus automated PPC bidding. It’s not really an age-old question, but there are certainly plenty of people on both sides of the discussion who have passionate views. But… let’s call it an important dialogue, one that can have a meaningful impact on business results. (It certainly shouldn’t damage any relationships!)
While tactically there are breakdowns of each automated bid strategy available for advertisers - from Google and plenty of others - with pros and cons, we aim here to join the conversation from a different angle. Let’s take a look at the needs and the philosophical goals of search engine marketing and PPC bidding.
With Manual bidding, what are the core byproducts we should extract for discussion?
The first is control. One of the most powerful ideas behind manual bidding is that control falls into the hands of the advertiser, and not into the hands of a search engine ad-publisher or a third party tool. The advertiser has control and visibility into the decision making, the data, the performance, and the outcomes.
Why is control important? There are two primary reasons:
The second byproduct of manual bidding: effort. The other primary idea inextricably coupled with manual bidding is that effort is required, and often a lot of it. Time investment is needed. Continuous analysis, review, and mental energy must be applied on the same set of tasks. By definition, manual bidding takes time and effort!
Why is the effort discussion-worthy? We’ll dig in:
What are we really after here? We want to merge the best that “control” can offer with the best that “effort” can offer.
Obviously our underlying goal is to set and accomplish business outcomes: to have program results be acceptable, or better yet, excellent. We believe control is powerful. We should have the right amount of control. However, we are also limited in the amount of effort we can meaningfully exert.
How do you accomplish this balance?
Well, it starts with reflection (or analysis - whichever word you align with more). Spending a bit of time evaluating your desired level of control (for you personally, and for the programs you manage) and your current versus desired level of effort and time investment.
If you’re reading this article, you’re probably the type of person who is interested in learning and improving the way you operate, and thus likely to take a meaningful shot at reflecting on your present methods (which is a great thing!).
This reflection and analysis should help you to identify options for automating sections of your program: First, where you can take advantage of the elements of control (tactically or strategically). And second, where you can invest effort into places it best serves you, your goals, and your business goals.
No article or blog post can tell you that exact mix of manual versus automated for your specific program, but it can act as a catalyst to begin that reflection process!
Where does automated bidding fit into this type of conversation?
Control has psychological elements, but ultimately the aim is to understand and control performance. You feel and know that you are getting the best performance possible because you are seeing the inputs, “turning the screws” yourself, and seeing the outcomes. Performance and results are ultimately the goal of having all this control.
The reality in many, many cases is that performance will be better when automated processes and calculations take care of the bidding. There are times when automated use cases may not apply as much (when thinking about impression share, or page position, or match type benefits, etc), but where there is data on conversions or revenue, the right strategic goal, and enough volume to merit it, automated bidding will optimize PPC campaigns better than manual human efforts ever could.
The second point, effort, is completely flipped on its head when using automated bidding. The day-in and day-out effort and time investment to manually analyzing performance and making bid adjustments is removed. Yes, you’ll still be reviewing your performance often, but in the world of at-scale paid search, that’s a given.
You create time savings by removing the pain of manually managing countless ad groups and keywords and products, and can use that time on more strategic activities to grow your business. Time and effort will be required, and required in abundance. However, those hours will be worth more. Assuming one doesn’t thoughtlessly apply a single automated bidding strategy to an entire paid search account, the campaigns and portfolios that have specific bid strategies will be operating at a much higher clip, creating time for people to focus on the other parts of the program that need the human touch.
Automation in SEM goes far beyond just doing a process automatically, it gets deep and complex quickly with optimization techniques. This is where artificial intelligence, machine learning, and other engineering and statistics innovations are attacking the process of improving performance in paid search. Automating some campaign management and workflow tasks are helpful to save time - but from a dollars-in, dollars-out perspective, big data applied to bid management has the most potential.
There are obvious places where a human’s manual thoughtfulness is better suited than any sort of machine or automation. Some of those are:
In the past, other items would have been on this list (like where device and audience bid adjustments should be made), but those specifically are now being automated fully by automated providers (from data ingestion, modeling, calculation, and execution). “Machines are taking our jobs” is real; but in the best of ways. You (the human, I presume) get the job of thinking, planning, and deciding, then the robot gathers the data, performs the calculations, and executes hundreds of thousands of actions for you.
Machines (a fun way to name any automated software or system) are obviously better at the niche, nitty-gritty analysis, calculation, operating at scale, and executing at ridiculous speeds. Bidding is one of the best places for automation to take over; it’s a problem that’s based in statistics and numbers that correlate directly from higher funnel (position, impressions, and clicks) to lower funnel (conversions, LTV). The machine’s platform will have a U.I. to make big or small tweaks and test the performance, providing control to the PPC bidding optimization effort.
Then, there’s the data...
Data is the other element that takes the benefits of automation and exponentially amplifies it. With an increase (almost every week, it feels) in the amount of data we can capture about the customer journey, there is so much more to feed the machine! That statistics problem can be worked with a much more robust data set, over a longer and more nuanced customer journey. The requirements from a human to piece that data together to make meaningful decisions for optimizing performance at scale just isn’t feasible.
Automation applied to huge data sets is a beautiful thing.
But how do we maintain control; the type of control described early on in this article? There are three points to make clear at this stage:
Clearly the stance offered here is that automation can add significant value. Nothing works without humans captaining the vessel, but we do believe that the cooperation of humans and machines is the best way to achieve (and exceed) goals in paid search. Machine learning PPC algorithms and automated bid management have tremendous potential, but shouldn’t be unleashed without preparation and thoughtfulness.
Now is as good a time as any to reflect on where it makes sense to invest your time, effort, and hours. In smaller programs where the overhead isn’t enormous and there simply aren’t many huge strategic decisions to make, the decision to proceed manually is likely a great option.
Alternatively, working with a program with over five hundred thousand keywords and a monthly budget around that $500,000 range as well may have much more to gain from automating bidding, and putting that manual, human effort in other areas that allow the machine to perform better at automating, and ultimately allow the business to prosper.
Try to maintain the optimal control and get the best return on effort, but don’t fall into a false sense that full control by a person is better than joint control with an automated solution.