Home search ads Keyword Bidding Counterpoint: It’s Not Automation That’s The Problem

Keyword Bidding Counterpoint: It’s Not Automation That’s The Problem

In a recent Search Engine Land opinion piece entitled Automated Keyword Bidding? More Like Automated Money Sink, the author espouses the view that automated keyword bidding is flawed because it is impossible for agencies to scale their systems to deliver positive results to clients.

While I agree with most of the points the author has raised, I believe his conclusion is wrong. Blaming automation for poor bid management is the equivalent of blaming a Ferrari for a car crash if a monkey was driving it.

The real debate is really optimization vs. automation. Many people confuse the two and perhaps it needs clarification. Rules-based bidding is sub-optimal and not a scalable solution for clients.

Rules in computer science are known as “heuristics” and are defined as rules of thumb that do not guarantee the best solution. However, a bid optimization algorithm does guarantee the best solution subject to the constraints applied – i.e. a spending target or a CPA/ROI goal.

There is also the issue that keyword performance based on 7 day or 30 day increments can lead to poor campaign management decisions. I agree with the author on this point. The flaw is that the marketplace is very complex and doesn’t account for factors such as news, seasonality or events making it impossible for a human to correctly figure out what bid would result in specific CPCs , ROI and position.

Simple curve fitting (i.e. what a smart high school student would do) will simply not work. Bid performance profiles for keywords can be vastly different. Keyword models themselves need to be sophisticated and require knowledge of techniques such as time series forecasting. Crunching this large amount of data needs a huge database and computational firepower. An excel spreadsheet will not do. However, the flaw here is not of automation but that of building poor keyword models.

Instead of avoiding firms that espouse “proprietary technology”, it’s better to ask the right questions to make sure they truly understand optimization. Some important questions to ask include:

  1. Is your proprietary technology a rules-based or a portfolio approach? A lot of agencies say they do portfolio-based bid management, but what they really do is simply cluster keywords. That is not a portfolio approach. Quiz them about the portfolio approach and ask them to explain their method.
  2. Is the technology you’re being sold a campaign automation tool or a bid optimization platform? The difference is huge. A campaign automation tool might have all the bells and whistles to speed up labor intensive tasks. However, it will not have the technology to help you maximize your performance. A bid optimization platform will maximize your performance and provide you with tools to speed up your day-to-day tasks. To take the car analogy further: an automation part is like the body of the car while the optimization is the engine. A sleek car body is nice to look at, but when you are performance driven, what you really need is a powerful engine.
  3. What is the accuracy of your keyword models? If they are doing model-based portfolio optimization, they should be able to give you a simulation of revenue/CPA at every spend level. At Efficient Frontier, we do this for all our clients and have the capability to automatically generate these in real-time. Once you managed with the portfolio approach, you should find the simulations to be within +-10% accuracy.
  4. What do you do for sparse data keywords? If data is sparse, you cannot use a simple rules based approach. Make sure you ask them their approach to solve this issue.

It is not automation that should be blamed for poor campaign management. It’s the improper usage of modeling and tools that leads to sub-optimal results. So remember, don’t blame the Ferrari for the monkey crashing the car. Ask the right questions of the owner of the monkey.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

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