PPC Keyword Analysis – Wall Street Style

by Anthony Mills on June 11, 2009

There is so much wasteful spending when it comes to advertising. Companies should think of keywords as an investment and optimization efforts as money management. Agencies are the trusted financial advisors that who manage those investments and ensure that they yield the highest return.

The Efficient Frontier Model of Keyword Management

When I was an investment analyst (before all of the toxic assets and Ponzi schemes came to light), we had used a number of different models to evaluate an investment’s value. One of those models was known as the efficient frontier. Its purpose is to gauge the expected return of a portfolio weighed against the risks of the assets within it. I had used it to help determine which portfolio composition would yield the highest return while mitigating its risk. The same principal can be applied when evaluating spend in a pay per click campaign. The following chart was created by a company, actually named Efficient Frontier, in London who has utilized a similar methodology.

revenue_v_spend

spend_and_variable_spend

When looking at pay per click ROI you’ll notice that the strategy of spending an even amount daily would have returned $3,975 each day, or 398% return on investment. However when you look at the second scenario, you would have lost $258 in revenue or dropped 9% in profit if spend had fluctuated. This is a simple example of how the law of diminishing returns will eventually harm a campaign. Finding that optimal point will ensure that client’s spend is being utilized to its fullest degree. Events that will affect the model are weekends and promotional campaigns as they tend to behave differently and therefore should be separated from the broad analysis.

Some people see analytics as a dull subject but I think by using it in creative ways we can optimize our efforts and maximize returns for clients. What other models from different industries, such as the financial district, can we use in web analytics?

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