December 3, 2017

How probable is the “opportunity to see” any advertising? How reflective are the media consumption metrics compared to the reality of media consumption? For instance, even if TV ratings shifted to second-by-second statics do we really know if people are paying attention or ignoring the advertising?

Since Acquire Online started tracking online advertising with MOAT from October 2015, we have analyzed 700M+ banner ad impressions across an extensive array of ad (appearance) serving and banner (touch) engagement metrics.

The MOAT system helps advertisers measure whether people see and engage with online ads at a publisher (URL) domain, browser and device level. This is especially pertinent given growing concerns over viewability, fraud and brand safety. It’s efficacy as an advertising measurement tool is reflected on the fact that it works with some big names including Nestle, Uniliever, Facebook, ESPN and Snapchat.


With data from MOAT, we have completely changed how we value and buy inventory. Through MOAT we are confronting some fundamental questions:

  • Is the viewer a person or a bot?
  • Was the ad placed on a page in time to see?
  • Did the user touch the advertisement with a cursor or finger?
  • How long was that ad viewable?
  • How fast or slow are people scrolling through websites?
  • Are people hovering on the ad but not clicking?

There has been a history of dismissing viewability & engagement tracking in favour of performance (CPL or CPA) campaigns. However, while performance campaigns are optimised to end goal, we know from attribution tracking that better online viewable inventory has a direct influence on future conversion actions being taken.

MOAT delivers quarterly benchmarks for various countries. New Zealand benchmarks should be used by media and creative agencies to set expectations for ad campaign objectives for key metrics such as viewability and engagement…as well as CPM, CTR, CPC & CPA. Having all objectives in mind when organizing a campaign (building whitelists & blacklists, selecting devices & ISPs, choosing creative type etc.) will significantly improve online trading tactics.

There is no better research on publishers than the insights achievable from online viewability and engagement tracking tools like MOAT, as almost every ad impression can be monitored versus a small sample of ads.

All online advertisers should track online advertising to:

  • Ensure that good publishers are rewarded with higher CPMs.
  • Remove the worst publishers with blacklists.
  • Ensure Brands have full visibility on the sites their ads appear.
  • Reduce budget wastage by optimising on good creatives and engaged audiences.
  • Decrease invalid traffic by significantly minimising bot influence (i.e. increase targeting on real people engaging with your ads)
  • Understand how users are engaging with your banner creative through heat mapping.
  • Help publishers to understand the relationship between their audiences and advertising appearing on their pages (vs their competition).

WHAT DO WE KNOW? (Desktop Benchmarks Q2 New Zealand from MOAT)

The MOAT benchmark from Q2 can give us a NZ perspective on performance for banner advertising on desktop devices. These metrics and an explanation on each follows:

  • 97.8% In-View Measurable Rate. The percentage of impressions where viewability-related metrics were measured. It is calculated as the number of In-View Measurable Impressions divided by the number of Impressions Analyzed.
  • 61.9% On-Screen Rate. The percentage of impressions where at least one pixel of the ad was in-view with focus.
  • 53.3% In-View Rate. Percentage of impressions where at least 50% of an ad was In-View for at least one continuous second. If the ad is as large or larger in area than 970×250 (eg. 300×1050 or 970×418), then it only needs to have 30% of its area In-View.

But, what happened to the impressions not in-view?

  • 2.8% Universal Interaction Rate. Percentage of impressions where a user entered the frame of the ad and remained active for at least 0.5 seconds.
  • 28.7s In-View Time. The length of time an ad has been active and In-View.
  • 6.9% Screen Real Estate. The average percentage of pixels that the ad fills on the user’s screen. This is calculated by taking the ratio of ad pixels to device screen pixels for all measurable impressions.
  • 15.1s 50% On-Screen Time. The average length of time that at least 50% of an ad has been on-screen.
  • 58.2% 50% On-Screen Rate. The percentage of impressions where the ad surface was at least 50% on-screen for any period of time. For ads that are 242,500 square pixels or more, the ad only needs to have 30% of its area on-screen.
  • 48.9% 80% On-Screen for 1 Sec Rate. The percentage of impressions where the ad surface was at least 80% on-screen for one continuous second.
  • 44.0% 1 Sec Fully On-Screen Rate. Percentage of impressions where the ad surface was 100% on-screen for at least one second continuously.
  • 50.3% Fully On-Screen Rate (No Time Minimum). Percentage of impressions where the ad surface was 100% on-screen for any period of time.
  • 37.0% Human and 2 Sec Fully On-Screen Rate. The percentage of measurable impressions where the ad surface was 100% on-screen for at least two seconds continuously.
  • 6.95% Out of Focus Rate. Impressions served into a backgrounded or minimized tab.
  • 36.68% Out of Sight Rate. Impressions had no pixels visible on screen.
  • 5.31% missed opportunity (area) rate. Impressions partially visible on screen but did not meet the 50% pixels requirement.
  • 5.40% Missed Opportunity (Time) Rate. Impressions had 50% of their pixels visible on screen, but not for a full second.
  • 53.3% Human and Viewable Rate. The percentage of measurable impressions that were viewable under the MRC standard and were delivered to humans.
  • 52.6% Human and Fully On-Screen or Large Ad Rate. The percent of impressions where the ad surface was 100% on-screen for any period of time or was as large or larger than 970×250 (eg. 300×1050 or 970×418) and was delivered to a human.
  • 9.4s Universal Interaction Time. Average length of time the user interacted with the ad.
  • 9.4% Hover Rate. The percentage of impressions resulting in a user hovering on an ad.
  • 67.1% Scroll Rate. Percentage of impressions where the user scrolled.
  • 29.0% Attention Quality. Ratio of users that converted from hovering to interacting.
  • 54.8s Active Page Dwell Time. Average length of time the user was on the page with the window in-focus.
  • 0.8% IVT Rate. The percentage of total unfiltered impressions that were determined to be delivered to a non-human end point. This includes General IVT (Spiders, Excessive Activity, and/or Data Center Traffic categories) and Sophisticated IVT (Invalid Proxy, Automated Browser, and/or Incongruous Browser Traffic categories).


There is no escaping that digital advertising is growing. According to Dentsu Aegis Network’s (DAN) Ad Spend Forecast (June 2017), digital’s share of ad spend is set to surpass television’s for the first time (37.6% against 35.9%), totaling NZD$313.8 billion. Not only that, but within digital, programmatic (automated ad buying) is set to grow by 25.4%. As DAN CEO Jeery Buhlmann says brands must be ready to embrace advertising innovation as new technologies become available and “ensure that they remain relevant by creating new value for their consumers.”

So, what does this mean for a research agency?

At the analysis and reporting side, it means the agency can have a greater understanding into consumer behavior and interaction with a brand. Are rural customers not able to load ads because the creative is too complex for their internet speed? And is that why their awareness of a new product line so low? Are urban commuters scrolling past an ad because it’s too text heavy as they are scanning through the news during their morning commute? Could that be why they find the ads annoying and feel more negatively towards a brand? Understanding these factors along with the insights gained from market research will give a deeper level of knowledge into a brand’s ecosystem and in turn allow them to deliver stronger and more refined recommendations to clients in an advertising world that growing ever more complex, fast-pace and evolving.

Data from: