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How Do I Measure Incrementality on Display Advertising

Measuring display advertising can be a challenge. It’s often difficult to account for views and ad impressions which can contribute to conversion goals driving your business. The most common & easiest method of measuring display advertising is through view-through and click-through measurements provided by the publishers. There are pros and cons to using publisher provided view-through and click-through data:

Advantages of Publisher Provided Display Advertising Measurement

  1. The first obvious “pro” is that the measurement is provided by the publisher so there is no extra work required to measure the ad campaign.
  2. You can use this data to optimize campaigns/audiences with that publisher, but it has its limitations.

Disadvantages of Publisher Provided Display Advertising Measurement

  1. The main “con” of using publisher provided view-through and click-through conversions is that you will be double counting across other media channels. For example, if someone sees your display ad on site X and sees an ad on Facebook, how do you attribute the conversion?
  2. If your media portfolio consists of more than 1 channel (which is most certainly the case) you can’t compare the results in an apples to apples way with other publisher measurement results.

In order to measure true contribution of the display advertising, marketers need to measure the incrementality of the display ads. The incremental contribution of display advertising can be measured by using audience holdouts, serving the held out audience a placebo ad, and comparing the measured conversion rate of the held-out audience versus the campaign (or exposed) audience.

This process is called Design of Experiments (DoE). When expertly designed, it has the ability to deliver on the promise of incrementality measurement at the vendor, campaign and audience level in a way that MMM cannot due to practical limits on data granularity and degrees of freedom.

Incrementality Testing for Retargeting Tactics

For heavily biased tactics like retargeting, DoE incrementality results can be actively incorporated into MMM as Bayesian Priors to improve MMM models across the board. For retargeting tactics, DoE offers the most unbiased measurement approach, as it randomly selects a subset of website visitors for exclusion from retargeting impressions, both in total and at the vendor level, in order to measure true incrementality of these tactics on a customer group that has already established interest and intent.

Design of experiment incrementality measurement for retargeting marketing example showing audiences segmented by platforms: Facebook, Criteo, Pinterest, All three vendors and control population.

Incrementality Testing for Prospecting Tactics

For prospecting tactics such as Facebook, DoE randomly selects a subset of prospects to serve as the control group. One approach to capturing a control audience is to show them a placebo such as a PSA advertisement (charity ad) which has nothing to do with the brand, but serves as a way to initiate tracking and thus segmenting the user away from the exposed cohort. Because this is designed at the group level, DoEs are not subject to all of the user level data challenges encountered by MTA requiring only that campaigns exhibit enough reach to establish statistical significance at the group level. For most advertisers this statistical significance is achieved in a matter of weeks and can be meaningfully updated afterwards on a weekly basis to inform tactical campaign optimization.

Author

Trevor Testwuide - CEO

Expert in business strategy and marketing measurement.

 

Multi-touch attribution is more challenging today due to limited tracking options, identity and cross-device resolution hurdles, data leakage and the massive amount of time it takes to implement.

 

What is cross-platform attribution (or cross-channel attribution) and why is it difficult?

The goal of cross-platform attribution in marketing is to gain clarity on the interplay and contribution of influence that each channel/tactic/campaign has on driving conversions over and above baseline sales.

It’s a task that has proved to be very difficult for many reasons including but not limited to:

  • Walled gardens are typically inaccessible to third-party tracking of impressions
  • Identity resolution across media platforms is quite low
  • Cross-device tracking is difficult and match rates are extremely low
  • Instrumenting a tracking infrastructure by a third party measurement provider has proved to be fraught with breakage and data leakage
  • It is extremely time consuming to implement without the help of a partner

Video: Landing a source of truth cross-channel media reporting dashboard

 

 

What are some cross-channel attribution tools?

MTA – collects individual, or user-level data, for trackable addressable media and conversion events in order to determine the impact of each media event to the desired conversion at the customer level. By summing the impact of each addressable media touchpoint on each customers’ likelihood to convert, MTA quantifies the total media channel lift provided by addressable media. MTA does not account for the impact of non-addressable media, and furthermore much addressable media is either non-trackable or lost due to the innumerable challenges of tracking data at the user level.

Incrementality Measurement – Incrementality in marketing refers to the incremental benefit produced per unit of input stimulation. Incrementality is the lift in desired outcome (awareness, web visits, conversion, subscriptions, revenue, profitability) provided by marketing activity.

Incrementality in marketing is especially needed for channels where ad impressions such as display, Facebook, social, or even TV are hard to measure. To measure incrementality, the audience is broken out into test groups (exposed to the ads) and a control group (suppressed from seeing the ads).

MMM – MMM is a top down (aggregate marketing data) and very artistic statistical exercise where one or more models (e.g. econometric, multi-linear regression) are leveraged to extract key information and insights by deriving information from multiple sources of marketing, economic, weather and financial data. MMM is also a high-touch consultative approach that is very manual with little to no automated data inputs, whereas MTA and Incrementality, when deployed properly, is a very automated approach leveraging preconfigured connectors that extract the required marketing data, across many channels, on regular cadence. (It’s important to note that MTA can take 6 months or more to deploy, whereas Incrementality can be up and running with reporting in 4-6 weeks.) See this article for more on why always-on automated experimentation is the future of marketing measurement.

Author

Trevor Testwuide - CEO

Expert in business strategy and marketing measurement.

 

Multi-touch attribution is more challenging today due to limited tracking options, identity and cross-device resolution hurdles, data leakage and the massive amount of time it takes to implement.