Getting Rid of Bad Apples and Polishing the Good Ones

The challenge

An e-commerce client came to us hoping to increase online sales. The client wasn't in a position to just raise its budget because the cost per conversion was already slightly too high for comfort. With five product categories spread among three sloppily set up campaigns, it was extremely tedious to find opportunities in the existing data.

Because there were too many kinds of products in each campaign, the client couldn't distinguish profitable from unprofitable keywords and product lines.

The solution

To identify the problem areas, we ran the data through AdWords filters looking for keyword and ad group names that shared similarly poor conversion numbers. We discovered that one product category was eating 35 percent of the entire AdWords budget, yet generating only 3 percent of online sales. We immediately eliminated that product line, freeing up around $15,000 per month to spend on better performing keywords and ad groups. We applied that $15,000 toward campaign elements that had already been profitable, and could now aggressively pursue and optimize for that traffic.

The result

We began working with this client on May 1, 2010, corresponding to the cross-hatch below the graph lines in Figure 19-3. As you can see, and to our surprise, conversions grew rapidly, and the cost per conversion immediately stabilized and then continued to steadily improve.

Figure 19-3: Simply finding and eliminating unprofitable product ...

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