Describe how you would assess how a row (keyword-engine pair) is performing and how to manage it To figure out how a row (keyword-engine pair) is performing, we need to do cost-benefit analysis first. In other words, since company’s goal is to sell tickets and create value, it would be useful to assess by measuring dollar amount earned from a dollar of cost (= Amount/Total cost). However, the row is already in ascending order of dollar amount relative to total cost. Also, there are only 368 data out of more than 4,000 data overall. Therefore, looking at the sales figure only is not the best way to assess keyword-engine pair performance.
I took out all the numbers that have no conversion rate. That means, it did not generate any sales and these will not be helpful in assessing the performance. Then, among those numbers with conversion rates, I only looked at the numbers of which the amount is bigger than the cost. Otherwise, company is losing money whenever it pays advertising. Then, I multiplied average position with click through rate and conversion rate so that to calculate how people relatively choose to pick up Air France and buy tickets via website. This will tell how its keyword performs with search engine to generate sales over cost.
However, to manage well, we also have to consider Ad rank. QS is determined by click thru rate and bid strategy is actually average CPC. If we multiply together, we can get Ad rank. To perform well, we need have higher click thru rate rather than higher CPC. Therefore, we also need to look at relative CPC assuming same position. That’s why I looked at other numbers without conversions rate too. Apply your performance metrics to each of the keyword-engine pairs (i. e to each of the rows) and identify the “top 10” keyword-engine pairs to pursue Below are the top 10 results based on performance metrics that I mentioned above.
However, we can see that most keywords already contain france . I believe people who typed france will look at Air France site automatically, so the company should not focus highly on the word. I confirmed this logic by looking at numbers without conversion rate. See below. And also, the first one should be an outlier, since only one click generated 900% of sales. So, I calculated again filtering these two words out. Below is the result. As we can see from above, both “cheap”and “paris” are a good match with “Google”.
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