Search Engine Marketing: Maximize Your Program Profitability Now

August 1, 2016 Tristan Reed

What if your paid search could go beyond ROI and focus on profit? Get every bit of revenue out of your next campaign with this advanced search engine marketing tactic.

To be successful, SEM managers need to understand profitability – and how to optimize profitability for each keyword. Why? Because most industry experts agree that analyzing marginal profit and then bidding accordingly is the most accurate way to optimize campaign profitability.  

So let’s talk about calculating keyword profitability.

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Don’t worry; this isn’t turning into a math exercise – in fact, my point is just the opposite. Who has the time to wrestle with the above equations and more to arrive at the highest point of profit, and the correct bidding targets to achieve it for each keyword? What’s an SEM manager to do?   

Using blanket profit targets

Most SEM marketers end up using a lot of trial and error while testing bid amounts and budgets to try to hit a blanket profit target across the program. While better than not setting a target at all for profitability, this strategy can leave a good deal of money on the table by not maximizing profit for each keyword.

Here’s an example.  Assume you’re managing SEM for a major apparel retailer, preparing for the winter rush as customers search for keyword A: “warm winter coats,” keyword B: “cashmere scarves” and keyword C: “leather gloves.” For your campaign, you set a blanket ROI of 10% across all your keywords on the assumption that during the busy winter holiday season, they’ll all perform about the same. But in practice, here’s what actually happens for each keyword:

  • Keyword A might hit its highest profit at 10% ROI
  • Keyword B might reach its highest profit at 30% ROI
  • Keyword C might hit its highest profit at 3% ROI

In this example, while keyword A, “warm winter coats,” performed quite well at the 10% ROI level, the campaign missed some potential profit for keyword C, “leather gloves” - and it drastically missed its maximum profit on keyword B, “cashmere gloves,” by optimizing to a much lower ROI than it should have.

Now extrapolate this example to hundreds, thousands or even millions of keywords and the potential difference between profitability at a blanket target and individual targets could be staggering.      

Analyzing each and every keyword

To truly maximize profit for your ad program, you need to analyze each keyword and then set the appropriate target. (I know, there’s lots of math and analysis involved.) 

Oh, and that’s not all. To arrive at the optimal ROI target for each keyword, you need to take into consideration the multiple dimensions of data for each keyword. For instance, profitability for a keyword can vary by geography, time of day, day of week and so on. You’d have to build a complex, multi-dimensional dataset to figure out the actual maximum profit.  

You know where I’m going with this. Today’s dynamic ad environment requires sophisticated technology if you want to maximize profitability. Modern predictive advertising management platforms can take advantage of very large, multidimensional data sets, machine learning and sophisticated modeling algorithms to determine profit by keyword—in the blink of an eye, rather than after days and days of manual effort.  

The bottom line: everyone’s doing it

Just like with automated bidding on eBay, if you don’t have automation, you’re at a serious disadvantage against your competitors who do. Sticking to the traditional method of setting a blanket ROI target across all your keywords can turn an otherwise strategically optimized program into an underperformer that costs you far more than necessary. So while you don’t have to be a data scientist to maximize program profitability, if you want to avoid wasting thousands – if not millions – of dollars in inefficiently deployed ad spend, you need automation that takes advantage of data science.

About the Author

Tristan Reed

Tristan Reed is a customer success manager at QuanticMind, where he works with Fortune 500 enterprise brands to track and optimize their search engine marketing campaigns across multiple devices, geos and timeframes. A polyglot who speaks Spanish and Japanese, Tristan graduated from UC Berkeley with a BA in economics, and applies his academic training daily to help position his clients for success.

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