Audience Analysis: Important for All Messages from Social Media to Technical White Paper

Before you write, during the writing and revision process, the key to an effective document, presentation, or message is understanding your audience.

Who is your audience?  Who, specifically, are they?
As you prepare to write, you need to have a good idea of your audience.  This will probably involve more than one stage of contemplation.  Of course, you know who your primary audience is likely to be, particularly if it is an instructor or an editor.  But who are the secondary audiences likely to be?  Why?

Demographics of the audience
As you define your audience, you need to have an idea of their basic characteristics.  Where do they live?  What gender are they? How old are they?  What is their income level?  What is their education level?  What are the demographics that specifically apply to your topic?  That will influence the questions you ask yourself as you try to obtain an accurate idea of the dominant characteristics of your audience.  For example, if your paper is on gun control, it is useful to know if your audience is likely to be comprised of gun owners, or members of the NRA.

How will they receive your message?  What is the medium?  Printed or written discourse?  Internet?  Graphics?  Film?  Television?
The medium of the message has a definite impact on audience impact.  For example, if they read your article in a newspaper, they will respond to it in a different manner than if they read it on typed pages.  If your message is on the Internet, you need to keep in mind such factors as design, color, accessibility, loading speed, etc.  If your message includes graphics, how are they printed on the page?  In color? Black and white?  If the medium is film or television, what are the production values?  What are other factors, such as music, set design, mise-en-scene, direction, camera angles, etc.?  All these are non-narrative elements that have an impact on your audience because each element carries with it meaning.  The mind makes meaning from each of the elements, and, like it or not, it will impact the spoken or written part of the discursive package.

What are the core values of your audience?  How can you affirm those while making your point?
What are the core values of your audience?  Of course, you will probably never know all of them, but if you understand a bit about the religious, ethnic, group, and/or demographic background of your audience, you may have a fairly good idea about how the audience members respond to certain issues.  What do they believe is the appropriate role of government and the state?  Is the human being inherently good, bad, or neutral?  Is the human psyche malleable or rigidly programmed?  The key is to identify the core values that pertain to your primary thesis and the topics in your paper.  If you affirm your audience's core beliefs, you can help convince your audience of your credibility and they will be more likely to pay attention.


When do the attitudes and values of your audience shift?  This is a key opportunity, but why?  What are your audience's situational attitudes?
This is an often overlooked and underestimated element in audience analysis.  And yet, it is precisely this area that holds the most promise because these are the points where you may actually be able to wield influence.  When the attitudes and values of your audience begin to shift due to a changing situation, or a different speaker, then you know you have an opportunity to create a more effective argument, and one which actually has a chance of working.  This is not to be overlooked.

Why will your audience read your document?  What's in it for them?
In constructing your paper, you need to keep in mind that your audience is not likely to read past the first line unless they perceive that there is some benefit or utility in continuing to read.  With that in mind, you need to structure your paper so that you "positively program or condition" your audience by making the paper readable, relevant, reliable, and rewarding.

What are audience expectations?  Narrative expectations?  Generic expectations?
Because of the nature of narrative and form, your audience will begin to develop the expectation that your paper will follow along these lines.  You must analyze your paper very carefully and decide what basic narrative form it is following. If it is a story, is it a Cinderella story?  Romeo and Juliet?  A revenge story?  If it is a report, is it a sales pitch?  An expose?  A recommendation?  A informational review?  Does it take a position and argue a point?  Generic expectations have to do with the genre or type of paper that it is. If it is a paper that takes a position, you would hardly expect it to read like an instruction manual.  Thus, you need to keep in mind how your audience will typecast your paper and just accordingly.

What are your audience's preconceptions about your topic?  The "major players" in your topic?
Is your audience likely to have preconceptions about your audience?  If they do, you need to address them.  If you do not acknowledge the preconceptions, your audience will think that you are not very well informed.  In addition, it is important to determine who the "major players" are and that they manifest themselves as subtopics, statistics, case studies, images, or individual characters.

Who do you consider yourself to be?  Who are you, and, more importantly, where are you in relation to your audience?  What are the power hierarchies?  Who and where is the "Other" in relation to you and your audience, and how does it change the way they approach you, each other, the text?
As you read your paper, think about how you would respond to your audience if you were meeting them face-to-face, then explaining the topic to them.  How do you envision them assessing you?  Your response to this is a key indicator of how you perceive yourself, and whether or not you believe yourself to be speaking to a group of peers, or to a group of individuals or an individual with more or significantly less power than you.  It's absolutely indicative of the post-colonial (and post-feminist, if one discusses the phenomenology of oppression) mindset, and it indicates how you know your own reality, and how you prioritize your perceptions.  If you can manage to think in an "Other"-centric way, you will have achieved what Kenneth Burke referred to as "consubstantiality," or the ability to "get under the skin" of your audience.

Using Statistics to Support Your Research

Statistics can provide excellent evidence for your paper.  However, unless they are used appropriately, they can undermine your argument and can even be destructive. In addition, it’s easy to reinforce cognitive biases with cherry-picked statistics without realizing what you’re doing.  The coupling of cognitive bias with flawed statistics was explored by Daniel Kahneman and Amos Tversky, and was part of their Nobel prize-winning findings. 

Here are a few guidelines for using statistics in your paper.

The key is to be aware of how statistical reasoning occurs and where it might be faulty.  Faulty statistical reasoning can be harmful.  It can lead to causal relationships or conclusions that are unwarranted, inaccurate, or deceptive.  Even if the presentation of the statistics is compelling, and even if the source seems to be reliable, they can be inaccurate. As you analyze, keep in mind when / how you might be making errors when analyzing data.

The Manipulated and "Sanitized" Statistic.  Numbers can be manipulated to make the facts seem to conform to one’s agenda.  For example, the College Board manipulated the SAT scores in 996 and it made it appear that math and verbal scores improved, when in reality, the performance was about scene.

Needlessly precise and hard to read:  need to put it in a form that it is easier to decipher and compare.

The Meaningless Statistic.  Exact numbers can be used to quantify something so inexact, vaguely defined, or difficult to count that it could only be approximated.  The exact number looks impressive, but it can hide the fact that certain subjects (domestic abuse, eating habits, use of narcotics, shopping, sexual preference) cannot be quantified exactly because respondents don't always tell the truth, because of denial, embarrassment, or merely guessing. Or they respond in ways they think the researcher expects.

The Vagueness of the Average.  The mean, median, and mode are three measures of central tendency (the intermediate, or middle, value in a set of numbers) can be used in inconsistent and inappropriate way in order to make .

How to say it’s the average:  The core of the problem comes from the fact that there are ways of reporting "average" - mean, median, mode

Unethical uses of "averages”.  people can tend to use the average that serves their purposes

The Distorted Percentage Figure.  Percentages are often reported without explanation of the original numbers used in the calculation.  Another fallacy in reporting percentages occurs when the margin of error is ignored.  This is the margin within which the true figure lies, based on estimated sampling errors in a survey.

False Ranking.  This happens when items are compared on the basis of poorly-defined criteria.  Unless we know how the ranked items were chosen and how they were compared (the criteria), a ranking can produce a scientific-seeming number based on a completely unscientific methods.

Drawbacks of Data Mining.  Many highly publicized correlations are the product of data-mining.  In this process, a software program searches databases and randomly compares one set of variables (say, buying habits) with another set.  From these countless comparisons, certain relationships, or associations, are revealed (perhaps between green tea frappucino drinking and pancreatic cancer risk).  At one retail company, a correlation between diaper sales and beer sales, presumably because young fathers go out at night to buy diapers.  The retailer then displayed the diapers next to the beer and reportedly sold more of both.

The Biased Meta-Analysis.  In a meta-analysis, researchers look at a whole range of studies that have been done on one topic (say, the role of high-fat diets to cancer risk).  The purpose of this "study of studies" is to decide on the overall meaning suggested by these collected findings. 
These are just a few of the many areas of bias in the use of statistics. With new algorithms being developed and the quest for meaningful pattern recognition in machine learning and deep learning, it’s important to recognize that bias can creep in at any point, especially if you have a predetermined idea about the result, or have a vested interest.

Sunshine Cleaning (2008): Sisters and Entrepreneurship

The independent, low-budget film, Sunshine Cleaning, (Dir. Christine Jeffs, 2008), was well received at film festivals and by critics. It received six non-winning nominations and two winning nominations for film awards. The film won “Outstanding Achievement in Casting – Low Budget Feature – Drama/Comedy) and also Women Film Critics Circle Awards “Best Woman Storyteller.”  The film’s budget was capped at $5 million. The box office proceeds came in at $17.3 million, which does not include Internet / app distribution.

Writer: 
Megan Holley

Cast (partial listing):

Rose (Amy Adams)
Norah (Emily Blunt)
Joe (Alan Arkin)
Oscar (Jason Spevack)
Mac (Steve Zahn)

Synopsis:
After deciding her gifted by quirky young son should attend private school rather than continue to be bullied, Rose Lorkowski, a mom who has been employed with a maid service provider, discovers that crime scene and biohazard cleanup pays many times more than her current job. So, with the help of her free-spirited but unreliable younger sister and baby-sitting support from her hapless entrepreneur father, she launches Sunshine Cleaning. The first few jobs are a bit overwhelming, especially since the two sisters know absolutely nothing about hazardous materials, bloodborne pathogens, or personal protective equipment. They persevere, however, and start to build the business.  As they clean up the aftermath of accidental deaths, accidents, criminal acts, and suicides, the sisters start to confront some of the darker issues of their own lives, including the suicide of their own mother, the erratic parenting of their father, and the tendency to become involved in relationships that have no hope of a positive outcome.

Analysis:
Set in Albuquerque, New Mexico, the light has that clear, yellow-gold clarity of northern New Mexico mountains, that contrasts with a clear blue sky and a chaparral / desert pavement ground. It’s earthy and realistic, lending the film a sense of authenticity.

What I like about the movie is the entrepreneurial spirit in a time of desperate challenges; the financial collapse of 2008 is not explicitly mentioned, but its presence is palpable. The uneasy relationship between two sisters and their well-intentioned but hapless father is also very touching. The sisters, through sheer force of will (and love for family), overcome the sickening nature of the crime scenes and bio-hazard zones.

In doing so, they are able to see the murky shapes in the recesses of their conscious minds, and to let the undifferentiated masses of emotions long suppressed come to the surface and untangle themselves.

Through the contact with death, many times due to the suicide of someone, the suicide of their mother emerges.  They come to realize that many of the patterns and behaviors they’ve had over the years have been in response to that traumatic loss.

And, as time goes on, they courageously face the memories and the feelings, they start on the tough work of cleaning up the ultimate bio-hazard zone, grief and loss.