Several search marketing firms (like Efficient Frontier) claim to have based their account management technology on Modern Portfolio Theory, the method for allocating capital among classes of assets that won Harry Markowitz the Nobel Prize in Economics. But, there are problems with portfolio theory that could easily get online marketers into trouble if they take companies like EF at their word.
Don’t misunderstand: The Search Agency uses a portfolio-based technique which is not derived from Modern Portfolio Theory (MPT) for the analysis of our own clients’ accounts. It’s partially from developing this technique that we were able to discover some of MPT’s dirty little secrets:
1. It’s actually just a production function.
Efficient Frontier shows diagrams on their website of ‘Conversions vs. Ad Cost’ and claims that the relationship between these quantities is called an ‘efficient frontier’. These diagrams are similar to the one shown below:
For different possible levels of spending, this chart shows how many conversions one can expect. There is a maximum amount of spending and conversions (marked by a terminal point) even if all the words in the account were pushed into first position. A green ‘X’ marks the actual performance of the account over the past week, for example.
EF calls this relationship an ‘efficient frontier’. Heck, they even named their company after it. But, unfortunately, it’s not an efficient frontier. It’s just a production function. (Check out the graphs in Wikipedia’s entry for ‘production function ‘, to see what I mean. Plotted on the vertical axis is ‘units of output per time’, like Conversions. The horizontal axis is ‘units of input per time’, like Ad Spending.)
To graph an actual efficient frontier we must plot the average return from a basket of assets versus the covariance of the value of that basket. The purpose of an actual efficient frontier is to determine the optimal allocation of assets – for instance, what percentage of stock (or bond) A and stock (or bond) B we should own in order to maximize our expected return for a given level of risk.
I realize ‘production function’ doesn’t sound as sexy as “efficient frontier”, but it’s the correct term. So either Efficient Frontier doesn’t know the difference between a production function and an efficient frontier, or they are simply hoping that you don’t.
2. There’s also a “Deficient Frontier”
Efficient Frontier’s version of portfolio theory is concerned with identifying the maximum number of conversions an account can expect for various levels of ad spending. But to judge how effective your account management is, you also need to consider the minimum number of conversions you can expect.
In the 1985 comedy Brewster’s Millions, Richard Pryor inherits a fortune, but to get the money he must spend one-tenth as much in 30 days and have absolutely nothing to show for it. Of course, the minimum number of conversions a given amount of ad spending could theoretically generate is always zero. But as Richard Pryor found out, it is extremely difficult to spend lots of money and get no results at all.
So, if we wish to gauge how well an account performed, we must look at how well it did relative to the range of reasonable expected levels, not just compared to the maximum. Looking at the production function above, the actual performance might appear to be quite good. But when we consider the production function representing the ‘deficient frontier’ to the graph, we see that the actual performance wasn’t as remarkable as it first appeared:
By neglecting to disclose the Deficient Frontier, the performance of an account can be made to look better than it actually is.
3. The ‘efficient frontier’ is not your target.
After you have identified the ‘maximum conversions’ production function, the next thing to realize is that this line is not your target. EF claims that any bid set that moves you closer to the production function improves the performance of the account, but in my blog post ‘Transgressing the Boundaries ‘ I showed that there is actually only one point on this line (which I call the “target point”) for which you should aim, based on budget limits or a CPA goal. To aim for just any point on the production function besides the target point will miss your goal.
4. The production function can move / be moved over time.
Though it is possible to improve the performance of an account by moving closer to the ‘maximum conversions’ production function, it is often easier to simply move the production function to higher values across the board. (Again, please read the section of the Wikipedia article on shifting a production function , if necessary.) Unfortunately, doing so generally requires labor-intensive, good old-fashioned account management (A/B testing, adding negative terms, pruning underperforming keywords, and such) and typically can’t be done by any currently automated means.
5. Using portfolio theory lets ‘deadwood’ float.
Proper account management should move the production function to higher values over time, but using portfolio theory to do this can undermine your efforts. Let’s say that we have an account containing thousands of keywords that overall are hitting their combined performance targets. The spending rate is within budget, the CPA is acceptable, and so forth. (Of course, some individual words might be above the target and some below the target, but overall their performance is acceptable.)
But let’s also say that just one of those words is terrible. Everyone agrees its tangential to the company’s business. It gets clicks and incurs cost, but never gets a conversion. Its presence might be penalizing the adgroup or account’s Quality Score. The rational thing to do is to delete this keyword from the account. But as long as the account’s combined performance is acceptable, then portfolio theory says that it is OK to leave it in. That is, even though the account’s performance could be improved slightly by removing the word, using portfolio theory will result in the word being left in, racking up ad spending for no good reason.
6. “Wall Street technology” almost destroyed the economy.
Speaking of spending for no good reason, despite the ongoing financial crisis and the unprecedented 1000-point intraday drop in the Dow Jones a few weeks ago, Efficient Frontier remains bafflingly proud of the fact that their technology is just like the high-risk methods that run Wall Street.
In their recent whitepaper ‘The Tale Behind the Tail ‘ (registration required to obtain copy), EF says, “Tail terms can be thought of as microcap stocks”. I won’t rehash my blog post, ‘Keywords Are Not Stocks ‘, debunking this idea, but regardless of how you think of keywords, EF’s thinking is profoundly tone-deaf given the current economic situation.
7. Even Warren Buffet dislikes portfolio theory.
In case you still might be enamored by ‘Wall Street technology’, realize that Warren Buffet, the greatest investor of all time, is not: “Modern Portfolio Theory tells you how to be average.” he was quoted in The Warren Buffet Way as saying, “But I think almost anybody can figure out how to do average in the fifth grade.”
8. It’s a bad way to bid.
According to Efficient Frontier’s descriptions of their own technology, they guess “billions of possible bids”, then select the set of bids with the best estimated performance. If a magician has you draw a card from a deck and then tells you that he can guess which card you chose using only a billion guesses, that would not be a very impressive trick. Marin Software’s bid management technology is able to directly calculate a bid from performance data without making ‘billions of guesses’. Google’s chief economist, Hal Varian, showed how to determine bids in his YouTube video ‘Google AdWords Bidding Tutorial ‘ without making billions of guesses too. Any system that requires making billions of guesses clearly doesn’t know how to bid optimally.
- AdWords Position Preference is Dying. Good Riddance.  - April 7, 2011
- Is Google Exploiting Neuromarketing in Reporting Quality Scores?  - March 21, 2011
- Does Google Reward High Quality Scores with More Impressions?  - February 14, 2011
- Like a Rock: The ‘Bid-CPC’ Relationship  - January 19, 2011
- From Business Intelligence to Bathtub Insights  - December 30, 2010
- Google’s New “Automated Rules”  - December 9, 2010
- Braking the Rules  - December 6, 2010
- Google Rich Snippets for Shopping Sites: A New Dilemma  - November 4, 2010
- Quality Score Never Shined My Shoes  - October 19, 2010
- Ad Auctions are Not Auctions  - August 24, 2010