... a theoretical cognitive limit to the number of people with whom one can maintain stable social relationships. These are relationships in which an individual knows who each person is, and how each person relates to every other person.
Proponents assert that numbers larger than this generally require more restricted rules, laws, and enforced norms to maintain a stable, cohesive group. No precise value has been proposed for Dunbar's number, but a commonly cited approximation is 150.
And it arrived at the conclusion: we're not necessarily "more social" - if being social means having more friends, a wider circle of friends... but we are more adept at "advertising" aspects - and minutiae - of our life.
So why do we go to facebook again?
Causation in ROI, measurability, and accountability measurement discussions is almost always never mentioned. And if it were ever mentioned, it is in a manner that is simplistic and in a ‘by-the-way’ fashion. A number of media and ad companies claim that ROI is as simple as running models after the gathering of data and transformation of these data and ﬁtting them in models - most likely linear regressions using OLS or MLE, econometric modeling, or worse, how the numbers "fit" against norms. Fits are measured by R-squared and areas-under-curves.
But causation is far more than that.
And that is probably why causation is rarely mentioned: it is far more than that - and is far more complex.
Because causation is very closely related to correlation: a strong correlation between two variables, for example, would potentially imply a causative relationship. Two variables - X and Y - that are strongly
correlated could suggest a potential causative relationship: that X causes Y. But the reverse may also be true: that Y causes X.
Alternatively, there may be an even deeper explanation - a third (or even a fourth) variable that explains the movements across the two variables. Simply put, there might be a variable, say M and Z, that essentially a ‘catalyst’ between X and Y, such that X ‘increases’ the value of Y because there is also an upward change in the difference between M and Z.
However, because correlation is far easier to explain and calculate than causation/cause-and-effect, we stop at correlation. And worse - assume that whatever we are looking at is "causative" rather than "correlative".
Nothing is technically better than the other - it’s really dependent on what you want to achieve.
If the end goal is simply to ﬁnd out the nature of the relationship between two variables - say, advertising spends and sales - then, correlative modeling may be sufﬁcient. One can go as far as saying “A dollar spent in advertising appears to correspond with a 0.2 increase in sales revenues, assuming a linear model”.
But that is only as far as one can go in correlative research.
There are no further explanations that can be gathered from the these research - no matter how many data points and no matter how robust the sampling methodology and framework is.
If the end-goal of the project is to explain the impact of advertising on sales and revenues, then causative modeling is what we ought to conduct.
Note the subtle difference between the two objectives - so subtle that even analytics people seem to forget it:
Neither is better than the other - it all depends on what one wants to achieve in the ﬁrst place.
One is simply different from the other because simply, correlated variables do not necessarily indicate causal relationships.
Simply put, the perils of correlative research is when one starts to look at the data as if they were causative.
Let’s take the case of advertising spends and sales. Assume that a correlation of 0.70 has been found between 104-weekly data points. Can we conclude that advertising spending caused the improvement in sales? Not necessarily.
Whilst the correlation - and the R-squared - is close to 0.50, it is still is not sufficient to conclude that increasing advertising spends means increased sales.
Similarly, if another set of data points actually see a correlation of 0.30 - low by standards of correlative research - between sales and advertising spends, we cannot simply say “advertising efforts are wasted because they did not contribute to sales”.
Just to reiterate: There is nothing wrong with correlative research; what is worrying is when we look at correlative research results as if they were indicative of causal relationships. It is when we start misusing these results that we get misleading results.
Causative research is far more extensive and time-intensive than correlative research. Causative research indicates a deep-dive into theories, hypothesis, and testing.
It goes beyond pure equations and r-squared (or other indicators of goodness-of-ﬁt) into areas that such as model-testing (through structural equation modeling and latent modeling across time).
Causative research requires a deeper understanding of the variables - thereby making the equations far more complex.
But the beauty of causative research is that it can explain - or at least attempt to explain - why and how things work.
In the case of ad-spends versus sales, an inquisitive, curious mind might not just measure these two variables - but also intervening variables: recall, executional cut-through, correct-brand attribution, message-relevance and afﬁnity, likeability, and believability of the message.
This curious mind might also incorporate the characteristics of the respondents themselves into the model to determine if being female or male, or if being under-20 or above-20, could potentially ex-
plain the movements between ad-spends and sales. She would also be interested in short-term, long-term, and base-effects of previous campaigns - and explain why these remain to be so.
Moreover, an inquisitive, curious mind bent on ﬁnding out “why” and “how” will dive deep into academic literature, best practices, and other models that have been uncovered by others in the past to test if these models and hypotheses ﬁt her own set of data.
Causative research is no panacea. In fact, there will be lots of discussions from causative research - but the main discussions will be centered, disciplined, and rigorous. Because causative research demands rigor:
Causative research takes time, effort, patience, and curiosity - a deep-seated belief that there are stories behind numbers.
And that numbers are typically shy - and secretive of their stories. It takes some teasing to see the stories they tell.
Scott Ballum writes in a manifesto his belief about our contributions to the world by making the right choices - however small they may be:
How many of us are actually actively involved with our lives? In the choices that we make?
I can't say that I have been 100% involved with everything that I do.
I honestly hope that I am getting there.
My eyes are dry, I cannot cry, I’ve got no heart for breakin’, But where it was in days gone by, A dull and empty achin’. My last boy ran away from me, I know my temper’s wearin’, But now I only wish to be Beyond all signs of carin’. Past wearyin’ or carin’, Past feelin’ and despairin’; And now I only wish to be Beyond all signs of carin’.
-- Henry Lawson, Past Carin’
All of us have got to come to a point of blithe insouciance, bordering on apathy – and go beyond that. It’s like when one is so tired that one cannot even fall asleep for falling asleep in and of itself requires energy – and there simply is no more to expend. So one lies in bed – staring at the ceiling, enveloped by the darkness, hoping that sleep will come on its own and soothe one’s soul, perchance recharged the next morning.
It is all bollocks, I believe.
One cannot go past caring – because in spite of everything and of one’s wanting to not care and just be blithely unaware and uncommitted, one remains. It’s as if by swearing not to care, one is ensnared – yet again – to care.
We cannot go beyond past-caring.
We cannot go blithely insouciant.
We cannot go blithely, quietly insouciant.
The problem with being efficient is that you tend to finish stuff quick and fast. Your inbox gets cleaned up fairly fast – and your in-tray gets emptied by the end of the day. However, it doesn’t mean that you’re going to ever see an empty tray or a complete-read/no-unread-mails inbox. You’d have more.
Sometimes, I honestly wonder if being efficient and fast is worth the energy that I am expending. If I finish something fast, new things get thrown my way – which I will get to finish quite fast – and…
It’s a virtuous – or shall I say, vicious? – cycle that never stops.
(These are days when “TGIF” does not offer any consolation – but dread.)
Games Will 'Eclipse' Other Media
Video games are poised to "eclipse" all other forms of entertainment, according to games studio boss Mike Griffith. Social gaming, more interactivity and better technology would help gaming dominate the entertainment landscape in future.
Last Word: Advergaming’s integration with social media technologies will become inevitable. With the push of Microsoft XBOX LIVE and its competitors in invading the living room and being a part – if not the center – of the consumers’ entertainment lives, we will see more this medium.
For audiences, this will mean having a new dimension in their current gaming lifestyles. For brands, it means a new way to connect with consumers. For media planners, it offers a new dimension – and a new set of questions – to measurements and metrics.
Microsoft Begins Windows 7 Push
The first public trial, or beta, version of Windows 7 has been released. Windows 7 would be the pivot of a broader Microsoft push to improve the way its separate software and service families work together. “Connecting all these devices together is the last mile in creating a real breakthrough experience,” says Steve Ballmer.
Last Word: With a new wave of OS coming from Microsoft we can expect consumers with more tools for becoming authors of content – as well as centralizing and organizing the information they have on their PCs. Consumer control of the media and the entertainment that they have access to will become even stronger.
For brands, this offers opportunities – and challenges. The challenge is “Is your content good enough to be kept at arm’s length (or at a click) away from the audiences?”
No Spam Please: Mobile Content with a Difference
Spam – a word that went from describing a tasty can of processed meat into something that now brings horror to anyone using e-mail – is, Charles Ash believes, the curse of tech fundis across the globe. You know the emails: "Enlarge your appendage"; "Cheap Meds"; "C1@l!$"; "Buy your PhD" and billions of other annoying unsolicited marketing mails sent hourly, from which there seems no escape. The Spam curse has shown its hardiness, stumping tech funds the world over and now evolving to proliferate and infect the mobile universe, with millions of unsolicited SMS messages sent daily.
Last Word: Mobile advertising will require more regulation, and a transformation from an “easy” form of delivering a message. A new creative pull-form of advertising using mobile devices will rise trying to avoid this turbulent sea.
Do You Know Where Your Kid Is? Check Google Maps
With an upgrade to its mobile maps, Google Inc. hopes to prove it can track people on the go as effectively as it searches for information on the Internet. Google also is promising not to retain any information about its users' movements. Only the last location picked up by the tracking service will be stored on Google's computers.
Last Word: This new application will open a gate for a new generation of services, from commercial to security. What would be interesting though is how audiences and the general public feel about this development: will this new development shift (once again?) our views about privacy? With the continued emergence of twitter and other microblog-everywhere services that encourage consumers and audiences to share their lives anytime anywhere, our “views” on privacy may have changed. Will this new Google service accelerate that even further?
The preceding excerpts and commentary were compiled by the leadership team at UM’s Global Digital Communications Practice. Please write to trending-up [at] umww.com for more information.