Do event outcomes affect how we rate their coverage? CNN IBN and US Elections 2012

Media feeds on elections. Counting and results declaration is when news becomes a “mass audience” genre, and the US Election results night more globally so is such a mass audience event. As I write, Obama has just been declared victorious. Apart from watching the coverage on BBC, I have been following the conversation in India on the topic on Twitter.

Rajdeep Sardesai, (Editor of CNN IBN , an important national cable news network in India) just tweeted that he was thankful to people for liking their coverage , on the basis of unsolicited instant feedback he received on twitter. Sounds very good!

BUT I couldn’t help ‘speculating’ if this enthusiastic support of the coverage had something to do with the outcome ( Obama’s Victory). Let me explain. Although a small fraction of Indians are really interested in US Elections,  many of them talk about it on twitter and also watch English language news. On average, they support Obama (they are young, globally mobile, have US connections mostly in North East and West Coast). So perhaps a Romney victory would not make them jump with joy. Then they (Obama supporters) may have liked the coverage a little less. Or at least not expressed unsolicited admiration.

I am not taking any credit away from Rajdeep or IBN. I am merely fishing for people’s thoughts on a hypothesis:An outcome of an event favorable to us makes us think more favorably of news media’s coverage of that event. So by corollary – On average, Americans who watched the 2012 elections night unfold on CNN (more liberal)  may rate CNN’s coverage more favorably than FOX News’ viewers (more conservative) would rate its coverage . Thoughts, comments?

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Facebook ads impact is just more ‘measurable’ than TV ads, not necessarily ‘effective’

They have been talking for a while about the death of the 30 second commercial. And social media were not the first technologies that inspired such claims.Yet, the size of Facebook with its tightly connected ‘anatomy’ has made these claims more vociferous. (The average degree of separation between any two people on Facebook is just 3.8, means that just in four steps a message can actually travel from anyone to anyone else, on average).

A recent post exemplifying this refrain, claims that Facebook promotion ( paid ads + all other kinds of messages) deliver 70 times more impressions ( eyeballs that see the ad) for the same cost than an ad on prime time television in the UK ( on coronation street) and 180 times more impressions than the same campaigns in the US . They argue that a well run Facebook campaign can generate 4 to 5 billion impressions versus the TV campaign that reaches a 100 million for the same duration. The claim is problematic due to the way impressions are counted for the two media.

The Facebook number is reached by counting the people touched directly (who friend or like the brand pages), their friends (who see it in their feeds, comments or messages) and friends of friends of those directly touched. In other words upto 3 levels removed from the campaign. For TV they simply count the number of eyeballs that saw the commercial ( the way marketers have computed ad effectiveness for TV ads for decades). There seems an implied an assumption that prime time television advertising only reaches those who see it directly. However just as Facebook page activity, television advertising too inspires conversations and recommendations through word of mouth that can make it reach a significant multiple of that 100 million, especially over the course of the year. In fact, the worth of one such conversation or recommendation (including on Facebook) ‘may’ be worth a few hundred Facebook impressions, a miniscule number of which may actually count themselves. However, obtaining any similar accurate measurement for the extended impact of TV advertising is next to impossible. However, his does not mean that there is no extended impact.

On first degree impressions, TV campaigns clearly achieve much more than the biggest Facebook pages( even Coca-Cola has just 53 million likes). Next, it may be worth pondering why these extended 4 to 5 billion impressions may not really count for a lot. Consider that for each person who likes a brand page, that activity appears on some laundry list of notifications of 16% of their 190 friends (Currently 16% of FB users are able to see such posts, and the average number of friends on FB is 190). A miniscule number of these impressions are likely to be welcomed or even consumed. Those receiving them may be just users who haven’t optimized their news feeds enough to avoid such notifications. Finally the post claims that Facebook itself did not have any data on the third level of sharing (to friends of friends of directly touched). This will be presumably much lower than the 16% on level 1. Think of chance that a friend of your friend is interested in the activity by their friend ( who is not a mutual friend) with a campaign or brand page. Since these data were not available, they used some triangulation to estimate some multipliers, and do not mention either the multipliers (no of people reached further by each person) or the attenuation (what % of people’s friends will receive such a message).

Of course other points worth considering are 1) why people like brand pages on Facebook (to get discounts!) and 2) how did they learn about these brands (surely not exclusively through FB campaigns or noticing friends who liked FB campaigns, but perhaps through prime time advertising and conversations with friends and family). These concerns make the value of these impressions questionable, even if their sheer volume is estimated properly. Of course the same can be argued for TV advertising that people do not want to see, but end up watching.

In sum, the key point here is that just because Facebook due to the traces users leave, allows one to measure how a campaign circulates beyond the first degree impressions and TV does not, one cannot conclude that Facebook campaigns are that much more cost effective than prime time TV.

Lets Abuse TAM Data: Indian TV Industry

An example that illustrates how one should be careful when reading television audience ratings data.

I read an ad in Mint about UTV-Bloomberg claiming that they have grown to no. 2 in the English Business News Space.

Lets Abuse TAM Data

Surprised I decided to look closely:
Well in the Male CS 25-44 (all SECs) Segment All India market they had slightly greater channel share (relative) than NDTV Profit and ET NOW according to TAM. For the uninitiated channel share is the product of no of people who watched at least one minute ( reach) and the average time spent by them.

I have three issues with this kind of abuse of TAM numbers :
1. The target for English Business News Channels is much smaller than the one used in the ad. Perhaps CS 25-44 M SEC A and B in 10 lakh plus towns would be more plausible.

2. The use of relative shares is again a misleading measure. In reality the absolute of share of viewing of these channels is minuscule to total television viewing so how many combined minutes of television viewing does this really mean?

3. The third is with the use of TAM for such data.English business news is a very niche segment.
a.) This genre is consumed by respondents who are hard to recruit for high involvement research like TAM.
b). Besides consumption is outside the home ( at public places, offices etc).
c.) The sample sizes for these channels is so low that these fluctuations may be due to sampling errors.

But the saddest part is that our media planners will continue to spend advertising money based on these irrelevant numbers and think they are making scientifically correct decisions.

I hope students of media/ advertising /marketing can learn this before going to the industry.

One cent per character : Will celebrities help Twitter monetise?

So as expected twitter has finally started talking more concretely about its revenue strategies interestingly they have taken to advertising (promoted tweets) as the primary driver along with some exploration into paid accounts. This is an article that talks about these in some detail.

I somehow feel that it is the celebrity accounts of twitter that can give it its much needed revenue stream. Think of the number of followers that celebrities on twitter have generated. Shashi Tharoor ( India’s external affairs minister) has 715,000 followers, Priyanka Chopra ( a bollywood actress) has 250,000 and so on so forth. Even celebrities with a niche appeal say popular journalists (Like Thomas Friedman has over 50,000 followers). So What?

What if twitter begins to charge everyone who has greater than a certain follower base size, a small amount of money on a fixed basis? Would these guys pay? I am sure their respective PR companies will advise them to pay. After all some 750,000 Indians chose to invest their time in receiving updates about their foreign minister’s activities . Can priyanka chopra choose to ignore her fan base of 250,000 people now that she has started actively engaging with them?

I would be interested in answers.

Beyond counting audiences: A bold attempt in the Indian GEC space

The recent ‘character India Loves’ study released by Ormax media demonstrates that capturing viewers tastes and preferneces is as important as measuring viewer numbers. Unfortunately industry has been laying emphasis only on the latter till now

With all due respect to TAM, my often echoed grudge with the Indian media industry has been its inability to look beyond plain counting. As an industry, it has been extremely focussed on reaping rewards from or critiquing the TAM panel in India, comparing it with AMAP (the other metering service) and advocating the need for more and more people-meters. Especially if you are a mass entertainment television channel, TAM has remained your holy grail for selling air time, understanding audience behaviour, making programming strategies, determining promo plans and whatever else was needed to be done. Thursday evenings (when the new data got updated) has long since been the day of reckoning for television channels. Even channels with niche offerings have pandered to the ratings game.
TAM, in my opinion, is an excellent system for what it offers, but it CANNOT answer everything. The industry needs to look for additional solutions to try and understand audience behaviour more closely and put the ratings data in better perspective. Only then will they be able to truly create differentiated content from their competitors and set trends. And I am sure many broadcasters do exactly that in some measure but its all propriety.
In other words there is a dire need for some industry wide original research to look beyond counting number of heads and the time they spent. To that objective, I found the recently released ‘Characters India Loves’ study (click here) by Ormax media a particularly innovative attempt at trying to quantify viewer engagement with popular characters on TV. That it is a study done by an independent company and not by one particular broadcaster should lend it currency among broadcasters, agencies and advertisers alike. That it promises to be a quarterly track will allow interested parties to look at trends than merely one off statistics.I believe a lot of innovations and sponsorships etc can be planned by drawing clever inferences from studies like this one.

I only hope that this is not a one off attempt and we see many more studies on Indian audiences where we get insights into their tastes and preferences. Of course the counting will remain as important!