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For the next installment of our Mastering the Metrics series, we’ll be discussing Cost Per Click.

Cost per Click (CPC) can be calculated by dividing the total advertising cost by the number of clicks generated. The context for this typically involves search engine advertising and refers to the amount paid to the search engine for each click that brings a visitor to the advertiser’s website. The cost per click metric can vary depending on the search engine used as well as the competitiveness of the keyword(s) in question. It is directly related to Pay Per Click (PPC), an internet advertising model that uses either a bidding system or fixed price to determine the price advertisers will pay when someone clicks on their ad. Cost Per Click is most often used to measure the cost-effectiveness or ROI of campaigns.

Advertising Cost / # of Clicks Generated = Cost Per Click (CPC)

In this installment of our Mastering the Metrics series, we will define Share of Voice.

Share of voice is a metric that quantifies the presence of a campaign or company in the overall advertising context of a particular market. Ideally, share of voice is calculated using impressions or ratings, but when this data is not available, marketers often use spending figures as a proxy. This metric is used to gauge the relative strength of a campaign within its market.

For this installment of our Mastering the Metrics series, we’ll define Effective Reach.

Effective reach measures an ad’s reach when it is exposed to an audience enough times to be effective, where the ad’s frequency of exposure must be equal to or greater than the effective frequency. We covered effective frequency in our last installment, but in short, it’s the optimal number of exposures needed for an ad to be effective. Therefore, effective frequency is a critical element in this calculation; in standard cases, it is often estimated to be 3.

In this installment of our Mastering the Metrics series, we will cover Frequency Response.

Frequency response refers to the reaction of an audience when it is exposed to an ad. There are several ways of conceptualizing frequency response functions. The three most common models are described below:

1. Linear – The linear model assumes that all impressions have an equal impact. This is a pretty sweeping assumption, so it’s not surprising that this model can be too simplistic for complex products.
2. Threshold – The threshold model suggests that several impressions are required before an audience responds to an ad’s message. This is the most commonly  used model because it offers the best combination of accuracy and simplicity.
3. Learning Curve – The learning curve model argues that an ad starts out having little impact, but gains ground with repeated impressions, finally tapering off after saturation is reached. With so many moving parts, it is difficult to get this calculation exactly right, so this model is not always entirely accurate.

Continuing our Mastering the Metrics series, today we’ll cover Effective Frequency.

Effective frequency refers to the number of times a person must be exposed to an ad before the message sinks in. Underexposure risks being ineffective, while overexposure equals wastage.  The standard figure that marketers use for planning purposes is an effective frequency of 3; however, for optimal accuracy, testing this assumption is probably a good idea.

Effective frequency helps you determine the ideal exposure level for a campaign, such that you’re balancing spending against the risk of ineffectiveness. In other words, you want to maximize the campaign’s impact while spending the least amount possible.

Continuing in our Mastering the Metrics series, today we’ll define Average Frequency.

Average Frequency estimates the average number of times an individual views your ad, with the assumption that the individual has actually seen the ad. Average frequency is useful for gauging an ad’s intensity — that is, how strongly it is focused on a target audience. To calculate average frequency, divide the total number of exposures by the total number of unique individuals who have viewed the ad.

Total Exposures / Audience Members = Average Frequency

In the first installment of this series, we defined impressions and explained their usefulness. A related metric is Cost per Thousand Impressions (CPM), which helps you figure your cost per advertising expenditure. This measurement relates to web traffic and approximates the your cost per thousand ad views (total impressions).

Calculating this metric on a per-thousand basis (rather than expressing the figure as a cost-per-impression) makes more sense because you’re dealing with dollar figures, which are easier to conceptualize when they’re whole (not fractional) dollar amounts. For example, saying you have a CPM of $3 really means that each time the page loads and the ad is viewed, it costs you 0.3 cents ($0.003). It’s just easier to express this concept as CPM of $3.

Advertising Cost / # of Impressions (1000s) = CPM

It’s the perpetual marketer’s conundrum: How do you measure and quantify your activities and the results they produce? I’m reading a great book right now that has a whole chapter dedicated to advertising and web metrics. It breaks the metrics down one by one and describes their uses and significance. I thought it appropriate to share the relevant ones in a series called “Mastering the Metrics.”

METRIC 1: IMPRESSIONS

Impressions are the number of times any given ad is viewed, usually indicated by the number of times the webpage containing the ad has been viewed. These can also be referred to as exposures or opportunities-to-see (OTS). You can calculate total impressions by multiplying the ad’s reach (# of people viewing it) by its frequency (# of times it appears). Keep in mind that this number is not as valuable some other metrics like Cost-Per-Click (which we’ll discuss later); just because someone viewed the webpage doesn’t mean they saw your ad or paid attention to it. Still, calculating the total impressions is one way to measure ad exposure.

Reach * Frequency = Total Impressions

Stay tuned for the next post in our “Mastering the Metrics” series, Metric 2: Cost per Thousand Impressions (CPM). For more tips, check out the full book: Marketing Metrics: 50+ Metrics Every Executive Should Master by Paul W. Farris, Neil T. Bendle, Phillip E. Pfeifer, and David J. Reibstein.