Different businesses have different needs and may therefore have different target metrics and goals. A 40% COS might be acceptable for one retailer (a home theater cable store that benefits from high margins) whereas another retailer may need to hit a 10% COS (a low margin plasma TV etailer). Moreover, even the statistics chosen to measure and track depend on the business.
There is a term in the industry for pretty much any statistic that can be measured. To make things confusing, in many cases marketers use terms interchangeably or incorrectly. There can also be a lot of overlap in metrics. What matters most is that, internally, you stay consistent. You can even invent your own metrics, depending on what’s important to your business. For example, RPC typically represents revenue per click and is an indication of the value of each lead generated via a campaign. However, you might use RPC to represent revenue per conversion - also known as AOV (average order value). There is no right or wrong way to measure and analyze your campaign statistics… just make sure that you are familiar with the common terms and that, however you define things internally, you stay consistent.
Statistics can be used to measure an individual marketing campaign or your site as a whole. As an example, RPV represents revenue per visit. You can calculate the RPV for a specific campaign (more frequently referred to as the RPC, or revenue per click, of that campaign) or you could calculate the RPV for your entire site.
Reporting can be meaningful on both a macro and micro level but, in many cases, you can arrive at the same statistics via different calculations… there is a lot of overlap in analytics. For example, on a campaign level, you may have spent $1,000 and made $10,000. Using those figures you will arrive at a 10% COS. You can also arrive at this statistic using a different approach. If you know that campaign generated 500 clicks, then you know the average cost per acquisition (or cost per order) was $40. If you know the campaign generated 25 orders, then you know the average order value (or revenue per order) was $400. Knowing the average cost per order and the average revenue per order will allow you to arrive at the same 10% cost % of sales statistic that the aggregate campaign cost and revenue figures do.
In most cases, percentages provide more insight than do raw numbers. 5,000 orders may sound like a lot but if it equates to only a .05% conversion rate, then it might not be so great. It’s OK to have raw number goals (for traffic, for example) just keep percentages in mind.
When sorting or filtering products by percentages (for example, when looking at products with the highest conversion rates) make sure you consider raw values and don’t make decisions until you have collected a large enough set of data to draw conclusions from. For example: a 50% CR looks good, but it should be ignored if it represented 1 item sold out of 2 clicks.
Use multiple different tracking solutions as backup.