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Principles of Marketing Notes Week 6

by: Kelsey Bixler

Principles of Marketing Notes Week 6 GEOG 1010 - 003

Marketplace > Auburn University > Geography > GEOG 1010 - 003 > Principles of Marketing Notes Week 6
Kelsey Bixler
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About this Document

Notes from February 15 to 18.
Global Geography
Daniel A McGowin
Class Notes
Principles, Marketing, Wolter, auburn
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This 3 page Class Notes was uploaded by Kelsey Bixler on Monday February 22, 2016. The Class Notes belongs to GEOG 1010 - 003 at Auburn University taught by Daniel A McGowin in Spring 2016. Since its upload, it has received 46 views. For similar materials see Global Geography in Geography at Auburn University.


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Date Created: 02/22/16
Principles of Marketing  The predictor for future behavior is past behavior- The quantity  consumed or patronage during a specific period. Sometimes companies do not like their heavy users­  example­ Internet companies.  Pareto principles­ 80% of your results come from 20% of your input  80% of your revenues 20% of your customers   Example­ Winn Dixie found that their best customers were moms with large  families­ the demographic is that they are moms.  Share of wallet­ for you as a customer you spend a certain percentage of your  income on certain companies. Percentage of a customer’s category/industry  spending that they spend with a company. This allows you to look at big  spenders for your type of product and lets you asses how you can get these  customers to get them to come to your company, How do you get this info?  Surveys. Credit card companies have this kind of info.  Miller Lite “Catfight” commercial­ clearly targeting men with this commercial (women  fighting with little clothing over beer. In 2004, sales of Miller Lite were up 10.5% by volume, compared with just 0.9% for the rest of the industry and 3.7% for Bud Lite.  What they have shown­ when you segment based on why people might like a  commercial­ it does not drive behavior. When companies go overly sexual without any  info on the product it does not drive behavior. It worked for GoDaddy because no one  know about them­ it doesn’t work for companies that are already known.   Segmentation variables MUST be related to purchase decisions ( must be  determining dimension)  Unrelated psychographics can create “cute” advertising doesn’t work  But psychographics of segments that are already formed based on relevant variables can be informative  What can we deduce­ There is a difference between qualifying dimensions and determining dimensions.  Companies are not advertsing based on what variables matter   Best practices of segmentation­  1. Select the broad product­market  2. Identify potential customers’ needs  3. Form homogenous submarkets  4. Identify the determining dimensions  5. Name the possible product­markets  6. Evaluate why product­markets behave as they do Potential problems­ cannibalization­ When new products steal customers and sales  from existing ones. Can be planned or unplanned. Example Coke Zero­ Segment bleed­   When communication with a segment overlaps into other segments. Redlining The practice of denying, or charging more for, services such as banking, insurance, access to health care, or even supermarkets to residents in particular, often racially determined, areas. February 18, 2016  Research­ Chick Fil’a spent $50 Million in order to get people to like their grilled  chicken sandwiches. Used small groups to ask people what they like about gilled  chicken sandwiches. They offer surveys for a free sandwich to ever ten customers.  Lego­ reseach found that the “secret to play” is that kids play the longest when  there is a task involved with what they are playing with.  The goals of most marketing research is to uncover unique (and actionable)  customer (and market) insight.    4 step approach to market research­ 1­ define the problem 2­ develop the plan 3­  collect and analyze the data 4­ interpret and report  Define problem step­ 3 categories for searching out problem­  Exploratory­ exploring what your problem is­ PBR hipster example­ they had to  figure out what was driving up sales (even though this was a good thing. Go out  and talk to people to pin point what is going on Descriptive research­ flesh it out­ we’ve figured out that hipsters are driving sales­ now we need to figure out what is a hipster. Quantify things now and bring  number into the equation Causal­ now we have to pin point the causal mechanism going on. Pin point  precisely what is driving the problem (or sales with the PBR case). Maybe we  find out that it’s because PBR is cheap or maybe its authentic. Experimentation  happens here.   Causation or correlation? Ex­ ice cream sales go up and violent behavior goes up? Is one causing the other? No­ summer time makes people more violent.   Predictive doesn’t mean causal.  People who have sex more than 4 times a week make more money­ maybe you’re  happier and healthier which means you’ll have more sex/make more money.  Before you jump to the conclusion that one is causing the other­ you need to  consider a compound (a third variable) that could be causing both.   Big Data­ weather can affect sales­ Wal­Mart puts umbrellas at the front of the  store when its raining. People also don’t like to eat berries when it’s really windy.  They did things to direct people to buy berries on days when it’s calm. Long story short you don’t know the relationship between things until you research what  causing things to happen  Developing a plan­ every company lives under the constraints of money and  time. So you have to come up with a plan that will help you accomplish your goal. Primary­ you go and get the information yourself­ ex­ Wal­Mart acquired berry  sales from the weather channels. More expensive­ to get customers to talk (focus  groups) you have to pay them. You also have to replicate things several times.  ­Research approach, contact method, sampling plan, research instruments. ­Observation, surveys (most common form of research­ have to be careful though  cause sometimes people don’t know/lie), panels and experiments, IT and data  mining Secondary­ Companies go to this first. There is a problem though­ it has to be  relevant, accurate, current and impartial.  ­Mail (small amount of response) , telephone, personal (expensive), telephone,  online.  Companies use samples­ they select people from what group I am interested in  and hope that it is representative of the whole group. However there are 2 main  problems with sampling­ Bias and Margin of Error (+/­ 3%)  How to get over than­ random sampling and sample size (try to make it bigger  because MOE gets smaller but this is more expensive and takes more time)   Micro Soft­ Vista­ why did it bomb? Software did not work on it a lot and they  had a lot of pop ups.  The sample group said they we worried about privacy­  account control drove people crazy­ Apple made ads making fun of how you had  to “allow” everything.  Perceptions of PC­ doesn’t work/ not cool.   What did Microsoft try to do­ Explain what account control was­ They tried to run ads about how people needed to see for themselves.  Apple strikes again­ made fun of Microsoft by saying that they were only putting  money towards advertising rather than fixing the problems.   Windows 7­ Microsoft did a lot of research and windows 7 was much better.   Windows 8­ people didn’t like it­ too much going on­ people just want to go to  their desktop. People didn’t like the touch screen.   So what can we deduce? For new insights, new methods are sometimes needed. •Every method has its limitations. •Even new methods and new data can still lead you into trouble so a balanced approach using multiple methods and data is needed. So what can we do? Triangulation "For every data point that we get, there is often a triangulation required…thatmeans talking to more customers, looking at telemetry data, and drilling more into a complaint, bug report, or suggestion.” Be aware of the “unknown unknowns ”Understand the noise-to- signal ratio is growing


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