Paid Search: Man vs Machine
My monthly paid search column at Search Engine Land, in case you missed it:
The question is often debated in the industry: “Which is more important the bid management tools used or the person who does the managing?” Sometimes the argument becomes self-serving, with artisans who manage their programs manually saying it’s all about the person, and tool providers arguing that it’s all about the algorithms, analytic power and automation.
For large, complex, tail-heavy accounts, this is like asking: “Would you rather be operated on by a skilled surgeon using stone tools, or a Neanderthal using the latest equipment?” The first may be preferable, but neither option is attractive.
However, the fact of the matter is: not all programs are large, complex and tail-heavy. Indeed, the roots of many disputes in our industry are a product of the vastly different types of challenges and accounts on which we’ve worked. What is most important to some programs is least important to another, hence digging into the man vs machine debate with a bit more precision may be a worthwhile exercise.
The Human Element
Human’s are much better than machines at many elements of the paid search game, including:
- Keyword selection;
- Match-type and syndication layering;
- Negative association anticipation and selection;
- Landing page selection/testing;
- Copy writing;
- Anticipating seasonal, geographic, and promotional effects;
- Classification schemes, recognizing and predicting meaningful keyword commonalities;
- Establishing and evaluating success metrics;
- Nuanced understanding of attribution, the characteristics of channels, and the ways that both last-click attribution and cheesy “assist” counting mechanisms can torque the truth.
The Power of Machines
Machines outstrip humans in some areas of the game as well:
- Speed, speed, speed. Automation allows a person to move mountains in a hurry.
- Precision. Programmers may make mistakes, but machines execute solid programs pretty much flawlessly.
- Data crunching. We have a number of folks on staff who can do pretty high-level math — present company excluded — but those aren’t uniformly available skills. Machines and software packages can execute enormously complex calculations across massive arrays of ads and engines and do so hourly without making a mistake.
- Pattern recognition. Human’s are key for providing flagging mechanisms for algorithms to watch, but the machines are often better than human’s at identifying signals in the data and separating them from statistical noise.
It’s worth noting that not all paid search automation software is created equal. I once heard a computer described as “the fastest, most diligent, but stupidest clerk you’ll ever meet.” Indeed, James Zolman was spot on when he pointed out that many so-called bid management platforms simply execute rudimentary rules set by humans (eg “if over efficiency target by X then decrease bids by Y”, or “bid this collection of keywords to position 6″). More valuable software with real algorithmic power is a rarer breed.
Of course, not all paid search managers are equally good at all facets of the game either. Smarter, better trained analysts will do the human work better than the average Joe.
Quality software allows smart human users to do tremendous volumes of work, quickly and flawlessly, and takes away much of the routine scut work from the plate of the the paid search manager. This has the important side-effect of making their job much more interesting, allowing them to do more of the brain work that humans do better than machines, and improving retention rates of paid search managers. The better the machinery, the better caliber of paid search manager you’re likely to attract and retain.
However, both the human manager and the software used cost money. These costs can exceed their value depending on a number of factors:
- How much money can be spent wisely on search? If everything is handled perfectly, what’s the benefit? If the answer is “not much” because the market niche is too small, having both brilliant software and top notch analysts on the case may be too expensive.
- Is the tail material? If 95% of the program is in the top 100 keywords, then the value of automation is greatly reduced. As the value of the tail increases the value of automation and smart algorithms increases.
- Is there much traffic volume? Sophisticated algorithms require a certain volume of traffic before they become more valuable than intuitive judgment. If the data is too sparse (regardless of CPC) smart algorithms simply don’t help much.
- Is there much ongoing maintenance to be done? The ongoing value of human oversight may be reduced if the product/service offerings are static, if there isn’t much seasonality, if there aren’t many promotional changes to implement, if geography is irrelevant, etc.
- Are there many anomalies to address? The fewer exceptions to the rule there are due to seasonality, events, the news, competitive pricing, inventory shortages, etc. the more accurate will be the assumptions of a good bid management system and the less value there is in smart human data analysis and anticipatory bidding.
For large, complex, dynamic programs both sophisticated technology and a sophisticated manager(s) are essential to generate the best results. However, as the above implies, in other cases what matters most depends entirely on the context.
The essential element in almost any case is having the core program build out properly from the ground up, and this is only done well by humans. For tiny accounts, the cost of that build out may even be prohibitive, and Google Boost may be the right solution for those folks, but for anyone spending real money investing in the smart skilled human to do the work well is the one piece that no amount of hardware or software sophistication can replace.
Beyond that build out, whether the algorithm or the person is more important will depend entirely on context.