It wasn’t so very long ago that it was not uncommon to hear colleagues say, “If I hear that ‘E’ word one more time, I’m going to…” There were several articles a week referring to viewer engagement in one context or other. The Advertising Research Foundation (ARF) was undertaking a major initiative to define and measure engagement, and major media players (programmers and agencies) were publishing position papers on the subject. Then along came ACM (Average Commercial Minute) ratings and C3, commercial retention, set-top box data, touch points, contextual advertising, brand engagement and TV on the Web. 

 
So, what happened to the idea that engagement with programs and content translates into advertising impact? What happened to all the discussion and press coverage about the value of an engaged audience? Does it still matter how viewers, users or readers experience program content?
 
True, it has been difficult to find consensus on Viewer Engagement, how it relates to Advertising Effectiveness and how best to measure it. Alone, behavioral measures, such as reach, time-spent or frequency, tend to be poor predictors of advertising impact. Frequency, for example, correlates strongly with ad recall, but not necessarily likability, persuasion or purchase intent.
 
C3 is established as the new TV currency, but the jury is still out on how to best measure the relative value of different advertising opportunities across platforms. Perhaps it’s time to revisit Media Engagement and its relationship to Ad Effectiveness.
 
Recently, Simmons released the first wave of their enhanced Multi-Media Engagement (MME) study, further illuminating the dimensions of Engagement. It included differences between audiences based on category, brand purchasing, and usage. The first thing we note in these data is that the ratio between the highest and lowest ranked TV networks for overall Ad Effectiveness is 7 to 1. This is a much greater ratio than the highest vs lowest break retention figures for cable networks, which are normally just a few percentage points apart.
 
This is also consistent with past MME data, and published results from other sources, that suggest that the range in ad effectiveness between a good placement and a poor placement can be several fold. The same is true at the individual program level, where the ratio between highest and lowest Ad Effectiveness is 6 to 1. Similar results occur for Web sites and print publications (6:1 for Web, 4:1 for magazines).
 
We also note that the correlation between average audience, reach or frequency, and Ad Effectiveness is not very strong. This also appears to be true for print and Web sites.
 
A regression analysis shows that 71% of the variability in Ad Effectiveness scores of Nielsen rated networks is explained by the following attribute types: Motivation (60%), Emotional Relatability (7%) and Credible Information (4%). Further, some individual attributes, such as “This network gets me to try new things” and “I relate to the people, situations & characters on this network,” have a much higher correlation with overall Ad Effectiveness than others, such as “This network gives me something to talk about” and “This network is definitely entertaining.” Again, this appears to be true for both print and Web sites.
 
Next we investigated whether Ad Effectiveness levels are different among users or buyers of different product categories. What we found is that the levels and ratios of highest to lowest Ad Effectiveness are consistent across all major product categories, including auto buyers, home-improvement shoppers or insurance prospects. So – no matter the category – a network, Web site or print publication that has high overall Ad Receptivity scores will have high ad receptivity in the various categories.
 
At Scripps, our most recent investigation is in the area of cross-platform convergence. Looking at several TV networks with strong, well-integrated web content, we found that Ad Receptivity among people who both use the Web site and watch the TV channel can be substantially higher than for those who only watch the TV network, or those who only use the Web site. For example, FoodNetwork.com has 32% Ad Receptivity among people who both visit the site and watch the channel. To the contrary, FoodNetwork.com Ad Receptivity among those who do not watch Food Network television is 25%. The same is true for the Food Network on TV, with 33% for those who use both, but only 23% among those who only view the TV network.
 
With all this evidence, maybe it is time that the Engagement debates be revived. (You can start by commenting below.) Perhaps news of demise of the “E-word” is premature!

(A 30-year research veteran, Mike Pardee has managed audience and consumer research for Scripps Networks, since leaving Your Choice TV in 1998. Mike champions an approach to research that focuses on consumer motivation, benefits and experience. He is an active participant in industry organizations, including co-chairing the CTAM Research Committee for several years).

 
 

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