Pay Per What? Choosing Pricing Models In Digital Advertising

How to determine which of the many different digital advertising pricing models makes the most sense for your business.

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Cost per Click. Cost per Mille. Cost per Action. Cost per Lead. Cost per Engagement…

Today’s digital advertising is filled with many different pricing options. Just a few decades ago, there only used to be two options: CPC (cost per click) and CPM (cost per 1000 impressions). Now there are dozens.

Pricing options have important implications on advertisers’ budgeting strategy. In this article, we will take a look at what caused the explosion of pricing options, and how advertisers should respond to the complexity.

A Brief History Of Digital Advertising Pricing Models

A carryover from other forms of advertising, the CPM model has existed since the dawn of online advertising, but it first became widespread starting around 1995, when it was adopted by Netscape and Infoseek. DoubleClick, launched in 1996, adopted CPM as its standard pricing model, which was key to popularizing its use in display media.

In 1998, the precursor to the CPC pricing model was pioneered by Goto.com, which later became Overture (and was eventually acquired by Yahoo). Google formally adopted the pricing model in 2002, and CPC has been the standard pricing model for paid search ever since, though it’s also commonly used in display.

The increasing variety of digital media channels in the past decade, along with the improvement of tracking technology, have further expanded pricing options, giving rise to CPE (cost-per-engagement) and CPF (cost-per-follower/fan) for social media, along with CPV (cost-per-view) for internet video, and CPI (cost per app install) for mobile.

Conversion-based pricing has existed since the past century. However, the increasing focus on performance-based advertising has created newfound interest in CPA (cost-per-action) and CPL (cost-per-lead) models.

Nowadays, many publishers offers multiple pricing options, which can be confusing to an advertiser. In order to understand their advantages and disadvantages along with implications on performance, we need to first take a look at the mechanism behind pricing models from a publisher’s perspective.

The Mechanism Behind Pricing Options

Ultimately, all pricing options are translated into a single metric on the publisher side: eCPM, or effective-cost-per-impression (= effective revenue per impression for the publisher. Wherever I mention “cost” below, it is “revenue” from a publisher standpoint).

Let’s say, for simplicity’s sake, that the publisher is interested only in maximizing short-term ad revenue, and the quality of all ads are similar from a user experience perspective. Then the calculation is simple: the publisher will just choose the ad that has the highest eCPM bid.

CPC, CPA, and other types of bids can be translated to an eCPM bid by predicting what the click-through rate (CTR) and conversion rate will be for the ad if it were shown for the particular ad spot:

eCPM = CPC * Predicted CTR * 1000
= CPA * Predicted Conversion Rate * Predicted CTR * 1000

However, this eCPM calculation depends on the accuracy of the CTR and Conversion Rate predictions. The less accurate the prediction, the more risk the publisher will take on that the CTR or Conversion Rate may differ from what was predicted.

Without going into too much detail, it is more difficult to predict events the further along they are in the customer journey, the less frequently they happen, and the more they are influenced by various external factors. Because of this, clicks are relatively easy to predict since they happen frequently, immediately, and on site.

On the other hand, conversions are difficult to predict because they happen less often, after more touchpoints, and are dependent on many different factors. Because of this, CPA pricing is more risky for the publisher compared to CPC pricing, which in turn is riskier than CPM.

For non-auction media, the result is an often-seen and rather straightforward order of preference, where a publisher may first sell as much inventory as possible on a CPM (preferably premium) basis, and then any remnant inventory on a CPC basis, and moves on to CPA (affiliate) sales as a last resort.

In an auction, things are slightly more complex, since different pricing models are eligible to bid against the same inventory. A sophisticated publisher such as Google or Facebook will adjust for this risk, where if two or more ads are competing for the same spot with a similar estimated CPM, the ad with the less risk is given preference.

For example, if one ad is bidding CPM while another is bidding CPC, then the publisher will choose the CPM-priced ad as the less risky option. Similarly, a CPC ad will be preferred over a CPA ad.

Another way to think about the mechanism, is that given a CPA ad, the auction algorithm will only be willing to show the ad for spots that are relatively certain to lead to a conversion, foregoing spots that may or may not convert. (Perhaps more accurately, each bid in the auction is penalized based on potential risk, taking into account the bid strategy). This limits the range of spots that the ad can be shown against.

The end result is that there is a risk and effort vs. scale tradeoff for the advertiser, where low-risk options such as CPA-priced campaigns have limited scalability; whereas, CPM or CPC campaigns can potentially attain the same CPA target at greater scale, but requires greater optimization effort to reach that same level of efficiency.

Implications On Advertising Strategy

So given the above, how should advertisers think about different pricing options? And if there are multiple options available, which one is best?

It comes down to which of these three factors the advertiser is concerned with the most: Effort, Efficiency, and Scale.

  • Effort is the time and knowledge required to optimize the performance of an ad campaign.
  • Efficiency refers to the ROI for the campaign objective (need not be actual revenue)
  • Scalability is how much volume you can obtain for the objective.

The overall trade-off between effort, efficiency, and scale for different pricing options is shown in the chart below.

CPM/CPV, CPC/CPE, CPL (higher-funnel conversions), and CPA (lower-funnel conversions) are straightforward, with decreasing optimization effort, decreasing risk, but also decreasing scalability. The less risk there is to the advertiser, the greater the risk to the publisher, leading to limited scale.

Facebook’s oCPM (optimized CPM) pricing is interesting in that it offers scaling capabilities close to CPM since it does not promise any given level of performance, but only requires effort on the order of CPC/CPE campaigns.

CPF requires additional marketing effort in order to obtain brand or economic value, which the final efficiency will depend on.

The Future Of Pricing Models

Traditional CPM pricing will never go away. Many campaigns are focused more on branding than direct response, in which impressions and reach are important measures of campaign success. However, progress is being made on alternatives and refinements to existing models, such as CPVM (cost-per-viewable-impression).

Conversion-based pricing is sure to gain wider adoption in the future. Scaling will become less of an problem as predictive algorithms improve.

Also exciting is the potential development of integrated ad formats that allow conversions directly on the ad or site, such as Twitter’s lead generation cards. These new ad formats should allow campaigns to run at the efficiency of CPL campaigns, but close to the scale of CPC/CPE campaigns.



The number of different pricing models will only continue to increase in the future, with platforms and media competing for share of advertising budget. As the number of options grow, it is important for advertisers to understand the trade-offs between pricing models in order to pick the combination most suitable for their campaign goals and resource availability.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About the author

Kohki Yamaguchi
Contributor
Kohki Yamaguchi leads product marketing at Origami Logic, a cross-channel marketing intelligence solution for modern marketers. With a career of 8 years in marketing and analytics spanning various functions, Kohki's focus has always been on translating data into strategy, simplifying the complex, and bridging the gap between data and organizational silos.

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