Google’s Smartbidding strategies: Why there is no free lunch

Published by Patrick Mebus on

There is a theorem in Machine Learning which says, that a free lunch does not exist. This literally means: there is no model and algorithm which performs best for every problem. Same counts for Google’s Smartbidding solutions. They can be incredibly successful. But it depends heavily on your market, your product, your customer and your overall marketing strategy and and and…

There is no free lunch: a one fits all solution doesn’t exist

What Smartbidding solutions does Google offer? 

Let’s get a quick overview about the different Smartbidding tools Google Ads has:

    • Maximize Clicks: Get as many website-clicks as possible for your budget
    • Target CPA: Google tries to collect as much conversions as possible within a given Cost Per Acquisition goal.
    • Target ROAS: Google manages your bidding based on Return On Ad Spend Goal. The focus here lies on conversion-value
    • Max conversions: Let Google set up your bids to increase the amount of conversions you can get for your campaign-budget 
    • Enhanced CPC: Google manages your bidding and tries to catch valuable traffic while not exceeding your max. CPC

Smartbidding uses Machine Learning signals to optimize auction-performance

So Which Smartbidding-strategy of these is the best?

Simple answer: non of those.
There is no Smartbidding-algorithm that skyrockets your performance in every situation.

As mentioned above, there are a lot of factors that need to be considered when relying on Google’s Smartbidding and Machine Learning in SEM. Here are just a few examples: 

  1. Which is your most valuable audience and group of users? It never ever makes sense to target everyone between 18 and 65 to sell your product
  2. In which phase of the product life cycle does the product find itself? Is it’s about launch phase with thousands of freaking out ready-to-buy-fans and customers? Or is it about a maturity phase where only deal-hunters are willing to buy your product for the cheapest price?
  3. What about the seasonality? Are we in November and you’ve an online-shop for ice cream (bad idea in general haha)?
  4. What is your overall marketing goal? Is it about growth and awareness whatever it count’s? Or do you have a CEO which second name is “efficiency”, heavily focused on margin and ROI?
  5. What about your competitors? Are you the market leader or chasing the bigger brands revenues?
  6. How does your keyword-setup look like? Focusing on brand-keywords or reaching out to more generic search-queries to catch users in the upper-funnel?

Even after you’ve answered all these questions for you and found a smartbidding-solution that could fit into your strategy, there will never be a 100% certainty that your results and KPIs will show improvement. 

Machine Learning Models and Algorithms are based on data. They use historical input to predict new values. Since a market is (again depending on the product and context) always dynamic and complex, an algorithm can just provide you a rough idea of future numbers. 

So all you can do, is to rely on the oldest but always best technique in marketing: testing. Figure out which smartbidding-tool works best for you and apply it to your campaigns. After a while question this strategy and tool and start testing from new. Stay critical and don’t get satisfied and lazy with your solution when it works for a couple of weeks. There will still be no free lunch, but the luch you’ll find will be much more delicious and most likely way cheaper.

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Patrick Mebus

I’m a Digital Marketer with deep passion for Search Engines, Automation and AI. I’m here to make Machine Learning more feasible for Search Engine Marketers.

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