Advanced PPC with Transparent Automated Bidding

November 17, 2016

In PPC, there are two main approaches when it comes to bidding workflow—manual and automated. Over the years, there’s been debate among search marketers on the pros and cons of each approach. Search marketers have differing opinions on which yields the best outcomes.

The Great Manual Versus Automated Debate


One of the main arguments in favor of manual bidding focuses on the control that it affords the search marketer, in contrast to the hands-off nature of automated bidding inherent with publisher bidding—like AdWords “Smart” bidding and most (but not all) 3rd party proprietary bidding algorithms.

In nearly all automated bidding approaches, the search marketer sets a goal and the bidding algorithm reviews historical performance, and then calculates a bid with limited transparency from start to finish.

The apprehension some search marketers feel towards automated bidding derives from the opaque nature inherent in most approaches. This fear is realized when a campaign is underperforming, and the search marketer becomes at a loss for what’s amiss, or how to improve it.

Putting that fear aside, let’s reflect on the many benefits of automated bidding, which is the reason for its proliferation.

Here are just a few.

Efficiency

Automated bid management is a huge time saver. Think about it—how long would it take you to manually change a million keyword bids? How confident would you be that each bid is optimized to maximize your return?

If you’re being honest with yourself, the answers to those questions should naturally steer you towards automation as the optimal solution. Automation augments the search marketer by executing repetitive tasks, serving as an ‘enabler’ for the search marketer to focus on growth opportunities or account strategy while keeping tabs on daily performance.

Accuracy

Automated bid management platforms produce accurate bids through regression modeling that looks backwards to predict future outcomes. With millions of dollars at stake, these algorithms are typically built with risk aversion at their core to produce low error rates. By their very nature, they make changes at scale that’s quite literally impossible for any individual, or even team, to compete with.

The reality is, sophisticated marketers with material budget use an algorithm to bid on their media today. If you aren’t, you’re putting yourself at a disadvantage.

Flexibility

Automated bid management platforms allow advertisers to define the goals and milestones for the algorithm to work towards. The marketer remains the operator and the brains of the operation, with the bidding algorithm working as his proxy.

Machine Learning

Learning from massive datasets to create better future outcomes is at the heart of bidding algorithms. Today, this type of mathematical analysis is popularly called “machine learning” and “artificial intelligence.” Most ad tech companies have years of experience with these techniques, but largely fly under the radar in popular press, with newfangled applications like self-driving cars getting the headline coverage.

So, how do you get the best of both worlds? Simple—employ automated bidding with full transparency. That’s not an oxymoron. That’s a real thing offered by a few leading independent marketing partners (not to toot our own horn, but Marin Software is one such example).

What’s in a Fully Transparent Bidding Solution?


Fully transparent bidding solutions (i.e., the bidding system shows you the step-by-step logic of the bidding algorithm) allow users to see all the details behind their bid calculations for each keyword. This includes the bidding model(s) employed, the details of the dataset used, performance bumpers activated, and any other pertinent details behind the decision-making. If automated bidding is fully transparent, many of the arguments opposed to automated bidding lose their heft.

Information Available in a “Fully Transparent” Bidding Solution

The level of information available for each keyword in a “fully transparent” bidding solution varies. That said, at Marin Software, we show the logic of our algorithms “line by line,” which allows users to see a full breakdown of bidding decisions, including:

  • Date ranges and data sets used
  • Metrics used
  • Predicted metrics
  • Auction and volume models
  • Data blending
  • Bid headroom
  • Learning models
  • How the optimized bids are calculated
  • External rules applied
  • Excluded dates and thresholds
  • Existing bid
  • Final calculated bid
  • Constraints on the algorithm


Contrast this to the information displayed in a “black box” bidding solution:

  • Existing bid
  • Final calculated bid (sometimes this is obscured, too)
  • User-defined bid rules


Clarity and Confidence in Transparent Automated Bidding


Fully transparent bidding solutions allow PPC managers to review the logic used to reach a bidding conclusion. In addition, the search manager has the option to overlay bidding rules to ensure the algorithm behavior is consistent with their risk tolerance and strategy to hit certain goals and milestones.

The best fully transparent bidding solutions also allow you to preview bidding calculations before they’re pushed to publishers, and manually override bids on specific keywords if needed. This gives PPC managers the full control of manual bidding with all the time saving, efficiency, and data processing power of automated algorithms.

If automated bidding isn’t currently part of your strategy, we hope this post helps break down the nuances of different approaches. Although it also explains the pros and cons, it advances the argument that if you aren’t using a transparent bidding algorithm in today’s environment, you’re hamstringing yourself, because it’s near-certain that your competitors are employing an automated method of bidding to try and out-compete you. If you’d like to learn more about Marin Software’s approach to bidding, click here.

By submitting this form, I am agreeing to Marin’s privacy policy.

See why brands have relied on Marin to manage over $48 billion in spend