The Paid Search Uncertainty Principle

Werner von Heisenberg courtesy of Wikipedia

In 1927, Werner von Heisenberg documented what he referred to as an “Uncertainty Principle” governing quantum mechanics.

The Uncertainty Principle holds that an observation cannot precisely reveal both the position of a particle at a point in time and its momentum. The more the observation reveals about one, the less the observer can know about the other. A similar principle governs paid search.

Physics sidebar: feel free to skip! If memory serves, the notion is that the act of observation impacts the object. To observe anything — by sound echo-location, sight, touch — we have to bounce something off of the object we observe.

For big things, this is irrelevant. Shining a flashlight on a tree doesn’t impact the tree. However, in the world of subatomic particles, bouncing photons or anything else off a tiny particle has a big impact.

If you want to know where a particle is at an instant in time, you have to “hit” it hard to get the answer quickly, but in doing so you impart a huge and unpredictable change in momentum to what you’re trying to observe.

The Paid Search Uncertainty Principle

This reads: “The amount of variance tolerated in Advertising Efficiency (“E”) times the amount of variance tolerated in the volume of advertising spend (“V”) is greater than some constant, K.” As the variance in one approaches zero, the variance in the other approaches infinity.

Okay, okay, enough of the physics metaphor, the idea is this: you can’t control both spend levels and efficiency metrics. The more you predetermine one, the less control you have over the other.

This fundamental law of paid search may be its least understood, as many companies determine an efficiency target and then simultaneously fix a rigid budget for how much they will spend in media. Those companies are often frustrated with their results.

Fixing a budget for ad spend translates to the following:

“I’m going to spend this amount of money regardless of market opportunities. I will flush money down the toilet if I must in order to spend my entire budget. If, on the flip side, the market conditions are such that I can make $20 in profit for every $10 I invest, I will nevertheless stop spending money when I reach my budget.”

Fixing an efficiency target translates to the following:

“I am going to spend my advertising dollars at an efficiency that makes sense for my business. I will spend an unlimited amount of money if I can do so efficiently. I will spend no money if market conditions dictate that I can’t spend efficiently.”

Stated as such, the Uncertainty Principle clearly follows.

Yet enterprise-level advertisers try to violate this principle all the time:

“We’re going to spend $1 Million this month, and we need to see an ROI of 5 to 1 (or a CPL of $30).”

It’s nice to have goals, and it’s smart to try to forecast what you’re likely to see, but at the end of the day market conditions may dictate that you pick one or the other target to hit, or you’ll likely end up missing both.

Important caveat: this assumes that your program is well managed. We’ve taken over many horribly mismanaged programs and both grown the spend and greatly improved the ROI.

But all things being equal, for any well managed program there is a trade off between efficiency and volume that has to be understood.

Paid search managers have control over many pieces of the game:

• The user searches that will and will not fire an ad
• The text of the ad fired by a particular search
• Where ads are served (both domains to a greater or lesser degree, and geographies)
• On what devices they are served
• The maximum amount the advertiser pays for a click on a given ad under almost any circumstance

As I’ve argued relentlessly in the past, we’d like more and better controls over many of the above, but we certainly do have a large degree of control.

But it is also important to recognize those factors paid search managers do not control:

• The volume of user search in a category. If the users don’t search, we can’t serve ads.
• How much other advertisers are willing to pay for clicks. If other advertisers behave irrationally, or change their bidding practices significantly, it will have a material impact on the marketplace opportunities.
• The advertiser’s selection, pricing, content quality, and promotions are often outside of the control of the paid search manager. These impact the value that can be extracted from traffic and thus the amount the paid search manager can spend for that traffic.
• Competitors’ promotions, selection, content quality, pricing, etc. Significant changes in the business practices of competitors impacts CTR, QS, and conversion rates for their ads and thereby shifts the Volume v Efficiency landscape in ways we can’t control.

The point of this isn’t to make excuses. Indeed, if the goal of enterprise search advertising  is to spend a large budget, there is no excuse for spending significantly more or less than the budget. If the goal is to hit an efficiency metric (CPL, ROI, Margin to cost ratio, whatever) for non-brand search, there is no excuse for missing that target.

However, introducing two targets often creates an unsolvable problem for paid search managers of any size.

Hitting both an efficiency metric and a volume goal requires good execution, yes, but it also requires favorable market conditions over which the paid search manager has no control.

Paid search managers must be held accountable for those elements that are within their domain, but holding folks accountable for conditions outside of their control is both unfair and unwise.