Courtney Carlson

This week we dug into the consumer purchasing journey and how it connects to advertising or sales promotion. Before class on Tuesday we read three articles that outlined some key points to the process and how there are essential steps that influence greatly the consumers purchase. The articles focused on word of mouth and moments of truth. Word of mouth is extremely important to a brand success or failure. Obviously word of mouth is an uncontrollable factor but if they want positive feedback, they must live up to their brand's reputation and provide consumers with a quality product. As consumers ourselves we hear and see word of mouth everywhere especially with today's great expansion of the internet. E-WOM is a huge thing in today's world. Social media is a presence that is very daunting and influential. There are millions upon billions of social media accounts out in the inter-web that are based off of opinion. These individuals speak honestly and truly of goods or servic...

Interesting: 1.) Event study format is the process of replicating specific effects of past studies in a more general context, and provided external validity to the data used in the current study. 2.)  Google did not provide the raw data on search-term activity; thus the results were based on anonymized search logs and provided a volume index statistic for specific search terms. 3.) A majority of social conversation took place in the seven days prior to and three days after game day. Questions: 1.) How do you increase pre-game conversation? 2.) What is the difference between an normal regression analysis and a subsequent analysis? What is multi-colinearity? 3.) If you increase brand engagement and it does not correlate with higher recommendations or promotions, how will you be able to get back that wasted time and make up for the losses?

Interesting: 1.) First Moment of Truth (FMOT) is the decision to purchase. Second Moment of Truth (SMOT) is the actual use of the product. Zero Moment of Truth (ZMOT) is the online research action. Third Moment of Truth (TMOT) is sharing your experience of the brand with others. 2.) Customers will soon be able to search for products by image, voice, and gesture; automatically participate in others’ transactions; and find new opportunities via devices that augment their reality. 3.) To create similarly friction-less experiences, some companies have created 24/7 digital “window shops” to test product ideas and customer interactions and collect rapid feedback without the need for additional labor or inventory. Questions: 1.) How do companies let their customers know what e-WOM is credible and what is not? 2.) How do companies transition into a central data mart? 3.) What is the most cost effective way to get "scrum teams" and new information systems?

This week we dove head first into the actual marketing metrics we will use and how they pertain to analytics. The OREO company example helped us bring together what we have learned in the past of thinking like a data scientist and then now what we are being introduced to with cross tab tables, different variable components, and regression. Learning about cross tabs was a huge aid in furthering my knowledge of how to separate variables and metrics. They are very helpful in showing how clear numbers can be if you just put them into context and then compare them. They also helped solidify what nominal and ordinal data is. Nominal is something that is categorical such as male or female and the central tendency measure is mode. Ordinal is a sequential category that can be greater than or less than the other and its measure of central tendency is the median. Other then these two concepts, there is interval or ratio data which is strictly numbers, no categories. The central measure of tendenc...

The Consumer Decision Journey Interesting: 1.) The consumer decision journey is more of a circle rather then a funnel with four primary phases where marketers can either win or lose ; initial consideration, active evaluation, closure, and post purchase. 2.) Passive (buy but don't recommend)  vs Active (buy but continue to recommend and push the brand to others) loyalists 3.) One consequence of the new world of marketing complexity is that more consumers hold off their final purchase decision until they’re in a store. Questions: 1.) How do you tailor a message that can appeal to most consumers but not offend or turn off others? How can you make them so that there are no open ended promises? 2.) In what way can you push products but also be informative, supportive, and provide them with the full experience without seeming out of touch? 3.) How do you influence word of mouth or internet information sites if those are strictly processed by consumers themselves?

Interesting: 1.) Marketing science should be at the consumer level not the competitive level. When focusing on competitors you automatically move from a marketing point of view toward a financial/economic point of view. 2.) Factors creating competitive intensity : bargaining power of buyers, bargaining power of suppliers, the threat of new entrants, the rivalry amount existing firms, and the threat of substitute products. 3.) An insight must be measurable and there should be some financial implications with it.If there is not a measured increase in revenue or satisfaction then the validity of the analyses should be questioned. Questions: 1.) Stephan Sorger's moves say that when a flank attack occurs, your counter attack is to just not have any weaknesses. How can you make sure and be positive that your competitors cannot pick out anything wrong with you market approach? (Nobody is perfect) 2.) If CEO's or higher ups have such little confidence in data analytics, why do t...

This week we talked about the intricate aspects that go into the lather, rinse, repeat process. This process is important in outlining how to get the most effective outcome without wasting time or money. We used the article about how publicity and advertising spending effects a companies performance to help go through the process. The first aspect of the process is figuring out the problem, how the data can solve that problem, and where you can get that data. In terms of the article, the problem was finding what is more effective or what out weighs the other, publicity or advertising spending. To find how the data can solve this problem we had to go through the metrics. These metrics included corporate brand attitude, sales revenue, corporate reputation, profitability, and firm value. We found out that these are not actually the metrics but the avenues or routes taken to get the right metrics. Sales revenue is obviously the monetary value, the corporate reputation is a scaling system (...

Interesting: 1.) Regression analysis: how you can create a predictive model for others who weren't in the sample. (CH 9) 2.) The regression line shows the relationship between the independent and dependent variables. (Ch 10) 3.) You cannot always take action based on a correlation finding. You must have the upmost confidence that the correlation is true and you must know the trade-offs between risk and reward. (Ch 11) Questions: 1.) If key variables and time are always changing, how can you be sure your assumptions are accurate? (Ch 9) 2.) What happens if you use correlation and causation interchangeably? (Ch 10) 3.) In what ways can you avoid any grey area of confidence in yore correlation? What is the most efficient way to have the truest correlation? (Ch 11)

Grisby Chapter 1 & 11, HBR Guide to Analytics Chapter 13, "The impact of publicity and ad spending on marketing and company performance" article. Interesting information: 1.) With bigger sample sizes you're less likely to get results that reflect randomness (Ch 13) 2.) Public relations is found to be more effective than advertising, particularly in new product contexts and for existing product contexts (article) 3.) Deductive vs inductive thinking (how you can infer things logically versus statistically) (Ch 1) Questions: 1.) How can you eliminate non-sampling errors? 2.) How does advertising spending show strong positive influence on sales revenue but only moderate influence on profitability? 3.) Why do firms try to use super small control groups to save money if in the end it gives them inconclusive results and defeats the purpose of statistical testing? (Ch 11) 4.) What is the main difference between a strategically picked control group with...

This week we talked more about how important communication is between someone seeking analytical help and those data scientists that are providing the information. When a company or firm is looking to require analytical information about a certain topic it is vital for them to make sure their objective is clear to those getting the data. If there is any vagueness or grey area it can be detrimental. This can lead to wrong or unclear data or there could have been a surplus of money spent when it did not have to. A big part of this is the fact that there are steps that should be followed when going through this process. The first aspect is that a question or objective that is clear ad concise must be presented. When we did our ping pong example in class, it was very apparent how one word can completely alter what the final destination is. After this objective/question is proposed now you have to look at what data you are going to need. This is where you analyze the pros and cons or how yo...

Interesting: 1.) Using ads to reduce price sensitivity is typically twice as profitable as trying to increase sales. (4) 2.) Data may not contain all the relevant information needed to answer the initial questions and it may also be influenced by latent factors that can be difficult to recognize. (4) 3.) There are customer and employee controlled activities that achieve the objective cohesively. (6) Questions: 1.) Even tho experiments are expensive but yet are the most reliable way to contain information, why are data analysts reluctant to use them as much? (4) 2.) How do you sort out your vanity metrics from you meaningful metrics? (6) 3.) What is the next step if your correlation between data and activities within the company are not positive? (6)

Interesting: 1.) You need more than quantitative and qualitative data 2.) Companies collect data that is available rather then what is needed 3.) Looking at past periods is less effective when trying to predict future performance Questions: 1.) How do you know how much information to get to create you information story? 2.) How do you know data passes the "interesting and important test"? 3.) How important is a CEO's approach to data acquisition?

Interesting things learned: 1.) Lather, rinse, towel - how processes are so important 2.) The intricate skills needed thinking wise in order for marketing analytics to be beneficial 3.) Barriers and catalysts Questions: 1.) How do you determine what metrics will be important or directly related to revenue? 2.) What happens if A/B testing is not a successful approach? 3.) How many metrics should be in your portfolio? What I have learned this week: Marketing analytics is vital to the success of a business. In order for a company to be able to change for the better they have to put in the work to find out the specifics of making their company function. Marketing analytics is a process of its own and has many steps that require certain skills and proficiency. It is a way of measuring a company's success and failures which can then be used to transform the company. In order for this process has a whole to work, it must be done efficiently and effectively. There are some diffi...