In previous posts, we have examined how to optimize your spending on CPL campaigns. There are many different tricks that can be used; however, the long and the short of it always comes down to analysis. As with many business decision, being able to properly measure and evaluate success is extremely important. In this case, the CPL conversion matrix is an ideal tool for this process.

This system compares variations from the ideal cost per conversion against the number of conversions that can be afforded within a given timeframe. Cost per conversion is the CPL multiplied by the number of leads necessary to achieve a sale. So if your conversion rate is 25% (4 leads per sale) and your CPL is $5, your CPC is $20. Before beginning to create this table, you need to determine your ideal CPC. This should be based on an analysis of your gross customer lifetime value. If your average customer generates $200 in business and your gross margin is 50%, then you are making a gross income per customer of $100. In this case you may determine that you should ideally not be spending more than 20% of that on acquiring the customer. So your ideal CPC is $20.

Your table should start with your ideal CPC and be broken into rows that represent different intervals of variation from that ideal. So your first row may be between your ideal and 1.5 times it. Criteria that have bids between $25 and $30 would fit into this category. Set your tolerance for the number of conversions you are willing to accomplish within this range. For the sake of example, let’s say that 4 or less is acceptable. Continue to add groups until the final one has only 1 tolerable conversion. These tolerances should be designed to ensure that you are achieving a suitable profit margin.

Once you have identified groupings of criteria bids and relevant tolerances, examine your historical data from the last time period. If you based this off of a month long campaign, look at data from the last month.

In here you should have the data necessary to highlight the cost per conversion of each set of parameters. As stated above, CPC is the CPL times the number of leads needed to convert on average. Once you have that, compare parameters within each range of CPC against the table you already made. You may find that one set of criteria is within the 3.5 times ideal range meaning that is can have 2 or less conversions. However, you may identify that this has led to 5 sales. This indicates that too significant a portion of your sales are coming from this relatively inefficient category which is therefore eating up too much of your budget. As such you may determine that you need to make a change.

This system is not an end-all-be-all set of rules; instead it is a framework for red flagging areas of concern for your campaigns. It can be used to efficiently check to make sure that your budget is being appropriately focused on high-leverage parameter sets. Through analyses such as this one, you can optimize your spending through data in order to streamline your CPL campaigns.