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As we wait for class to start, please sign in for today’s attendance tracking: Text to 37607: PAPER netID Go online to AEM 4550 class website Click on “attendance tracking” – in green font Submit your netID or
AEM 4550: Economics of Advertising Prof. Jura Liaukonyte Presentation Prep
Timeline of the project Sometime between now and the end of this week – you should email me to “reserve” the industry or company so that we do not have any overlapping topics. Note: the earlier you do this, the better the chances are for you to “get” that industry or company. I will post the chosen topics as soon as I get them. Confirm with me that the industry that you have chosen is not reserved by any group. By 10AM on April 7 th – one page project outline is due. In this outline you should note: What industry/company you picked and why Why would it be interesting for the advertising audience? What are the examples of advertising strategies that this industry/company employs? How does the competition in the industry affect the advertising strategies? April 7, 9 – 15 minute individual meetings with me to go over your proposed project so that I could address any questions or concerns you may have and give you data and recommendations on how to approach the analysis. April 9 – HW5 is due May 5 – Mini Exam, final paper due
Individual Meetings April 7* – Individual meetings in class April 9* – HW5 is due, Individual meetings in class * Attendance will be taken for everyone. I expect that the rest of the students will spend that time discussing and preparing for the presentation with their group members.
General Rules Every team should plan to present for 35 minutes and distribute that time approximately equally among all team members (~9 minutes each). Groups of 3 should plan slightly shorter presentations (under 30 mins). Even though there will be a common denominator that will determine the score for your group overall, I will also evaluate presentations on an individual basis. Therefore, the scores for presentation and paper across the same team members might not be the same. I will take attendance during every presentation and take particular note of students who ask good questions. There will be a mini exam that will be based on your classmates’ presentations.
Raw Data Requirement Cannot emphasize that enough!
Suggested outline for presentation 1. Introduction: Which industry/company did you choose? Why? 2. Industry Structure 3. Advertising Strategies: Raw data requirement Graphs, quantitative analysis 4. Recommendations:
Prime Time Advertising Data See excel file posted on the course website. Pick appropriate data for your team SLICE-DICE-ANALYZE Explanation of POD = X.Y.Z X = the position of the break within the program Y = the position of the ad within the break Z = the length of the break (number of total positions within the break)
Primer on Graphs
What is the goal of a graph? The goal of a graph is to present data in a manner that allows the reader to quickly grasp what the data mean. To let the data tell their story.
How can we do this? A graph should be… Simple Simple usually means better – don’t let the formatting get in the way of the letting the data tell their story, e.g. white background and simple color schemes. Clear Lines, axes, labels, legends and the title should be clear and easy for the reader to understand with a quick glance. Appropriately Sized Try to maximize real estate for the important stuff (the chart itself), while giving everything else just enough space so that the reader knows what is going on. Consistent The weight (thickness) of lines, the font, and color scheme should be consistent throughout the chart. Even better if the font matches (or complements) the font used in the paper.
Before and After
Summary of Tips: The simpler the better. Fanciness leads to busy-ness, and busy-ness can make it difficult for the viewer to understand what is going on. For example, white backgrounds virtually always the best way to go when making professional looking graphs. Additionally, try to use thin lines. Thinker lines take up more space without giving the viewer any additional information. Axis Labels! Moreover, use appropriately sized labels. Labels that are too big can crowd out valuable graph space. The graph that is telling the story, so it should get the most real estate. Make sure you choose distinctive colors (or dash styles) so that the reader can distinguish the different lines. Don’t use polynomial fit. A lot of interesting variation in the data is lost when you force a smooth fit between data points. If you have dates, make them short. The reader knows that January 1, 2015 is the same as 1/15, but the later is much easier to process and takes up much less room. Consistency of font between title, axis labels, key, etc. Even better if the font matches (or complements) the font in the text of the paper. This one gets overlooked but can greatly add to the readability of your graphs. Lastly, give the source. It is always good to let the viewer know from where you get your information.