Become a better keyword vintner

A key objective in PPC is to grow revenue within efficiency targets. This can be achieved through good bid management on the existing keyword set, as well as through the addition of new keywords. It is easy to add thousands of keywords using product feeds or a machine generation method. These keyword sets often add very little term value in a PPC campaign. Quantity is no substitute for quality. It is important to track the quality of keywords you add to a PPC campaign over time and possibly by the source of the keyword e.g. product feed, keyword research, search query mining etc.

Some questions you may want answer include:

• What is the average additional revenue we generate per keyword added (and is it within efficiency targets)?
• Is our initial evaluation period for new keywords sufficient, or are we potentially missing opportunities?
• What is the best source for new keywords?
• Is the quality of new keywords improving over time?

The answers to the above questions are not always apparent from traditional keyword performance reports. Keyword portfolios have already been compared to investment portfolios when it comes to keyword bidding. We use a similar analogy which compares keyword portfolios to loan portfolios. This allows us to apply the idea of a vintage curve for a loan portfolio to keyword portfolios. A loan vintage is a group of accounts that originated in a given time period.  For example, all new customers from 2009 make up the 2009 vintage. Vintage groupings can be monthly, quarterly, or annual, depending on the application or data available. Different groups of customers from the same vintage can also be compared to assess their relative quality (e.g. walk-in customers versus directly solicited pre-selected customers). A performance metric such as the proportion of accounts more than 90 days in arrears is often chosen to compare different loan vintages by time on book. If we make the analogy that new keywords represent new customers we can extend the idea of loan vintages to that of keyword vintages. Similar to loans, keywords are added at different time and can originate from different sources (e.g. product feeds or a break-down of search query reports). We can track performance metrics with “keyword age”, which may include percentages of new keywords with a click per impression or revenue per new keyword after a certain time period.

Below we will illustrate one application of a vintage analysis on real campaign data to gain some insight into new keywords. Many more applications are also possible. In figure 1 we consider 8,467 new keywords added to a PPC campaign from April to August 2009. Suppose we start a large set of new keywords on a fairly aggressive initial bid in order to gather performance data with which to optimize keyword bids. We would expect that a large proportion of them would be bid down over time in order to achieve an acceptable or agreed efficiency target, until we reach a stable overall bid level for these keywords as a group. When we study a larger set of campaign data across various advertisers, this seems to happen on average after about 3 months. A similar trend is apparent in figure 1 for our example campaign. It suggests that we achieved an average monthly long-term revenue of about $4 per original keyword added. It is clear how new keywords were bid down over time as performance was optimized.

There is an important variable we did not consider in the above view, and that is the efficiency metric for the new keywords over time. In the case of the above campaign the efficiency metric is cost of sales (i.e. PPC cost/sales). A target of around 8% (allowing for statistical noise) on non-brand terms is an acceptable benchmark for this campaign. In figure 2 below we show the average revenue per keyword (as shown in figure 1) against the cost of sales by keyword age.  Despite consistently decreasing bids on new keywords over time, the overall efficiency varied around the 8% cost of sales benchmark throughout. This suggests that we potentially did not give new keywords enough time to prove themselves before decreasing bids on them. If we kept the average bid higher for a longer period we can potentially achieve a higher average long-term revenue than $4 per keyword added, within the efficiency target. The keyword bidding in month 8 seems to try and address this efficiency by raising the average bid. Hopefully we have not priced too many of the original keywords out of contention by this stage.

Similar to the above curves you can track the average revenue that you gain from each new keyword added for different cohorts of keywords. This often decreases over time if your inventory remains fairly stable over time, as the most relevant keywords are often selected upfront if your initial campaign setup and research processes are well developed. Treating your keywords as ‘vintages’ can provide useful insight about the quality and performance of your new keywords over time. It also gives you an approximation of the average revenue you can expect per keyword added and at what efficiency. I hope 2010 will be a good vintage for your PPC keywords!