Week 9 Reflection

I received a file that held 4 years of sales and promotional data within 5 regions. The data was sent to to have the sales of widgets be analyzed. The question I asked myself while analyzing was, "What region has the most sales due to promotional data". The promotional data that was being analyzed in particular were, Direct Mail, Email, SMS,and Advertising. The equation that was determined to be used to further look at the data was:

=a+(b1*DMAIL)+(b2*EMAIL)+(b3*SMS)+(b4*ADVERT)

This equation was used over all regions to try to predict future sales. The information found that the model predicts certain regions expect to sell way more widgets then others for the first quarter of 2019. This could be due to outside factors such as climate, weather, or location of the different regions from each other. Further, the fifth region was predicted to have the most unit sales while the first region was predicted to have the least. This is important because it must be noted that the fifth region spent $400 on direct mail, while the first region spent $175, and the fifth region also spent $25 more on SMS, and $100 more in Advertising. 

file:///Users/jeremymorris/Downloads/Widget%20Sales%20Spreadsheet.htm

For Class October 11th

For this weeks set of readings, the topic was buyer personas. The purpose of buyer personas is for marketers to gain insights on buyers to gain knowledge about their spending habits and emotional buying to specifically target them in groups. Each link delivered the same message, they are very important, but don't be frustrated if they don't answer every question every time. I really understood what the authors said because it opened my eyes to ways I can target my own customers in my own business's. With online customers still trending more positively, online research and the creation of buyer personas can be a huge step in the marketing aspects of any business.

One thing I found very interesting was the creation of an actual person when creating a buyer persona. All articles said that it is a huge help to marketers as they can create an emotion and a face when creating buyer personas to target certain audiences. This is something very new to me as I have never heard of that before, and I believe thats why I found it to be so interesting.

Another thing that interested me were two concepts "keep it fictional, but keep it realistic" and, "the first draft is not the final draft" . These concepts stuck with me because I believe it goes hand in hand with the creation of a face and identity for the buyer personas. Because this is fictional, its good to realize that wen doing research in order to keep focus and research on what your actually looking for. If the fiction gets in the way, the research may end up in a waist of time. The second concept stuck with me because just learning what buyer personas are it was good to hear that they are not finalized the first time around. Because you can edit things gave me confidence when being forced to create my own.

The third thing that interested me was the social media side of buyer personas. What I found most interesting was how marketers will quite literally stalk consumers into their LinkedIn, Facebook, and Twitter, in hopes to find information on what kind of engagements they have, and what kind of buyers they are. This led me to the question, have I ever been searched by marketers into my own social media?

3 questions:

Are their certain businesses that buyer personas work best for compared to others?

How do you know who to focus most on to create buyer personas?

Are surveying customers better then online research when creating buyer personas?

For class September 27th

For class Thursday we had to read a lengthy article focusing on social media presence, and how social media advertising can effect television, and specifically the super bowl. Because social media is beginning to hold a lot of power in marketing and brand awareness, it has a major role in effecting consumer emotions for super bowl commercials, as well as just the consumer in general.

One thing I found interesting throughout the article is how specific advertisements may have an immediate influence on internet search activity when the TV advertisement is coming from a huge event. For example, the commercials surrounding the Olympics had immediate  on and off line purchase behavior with its commercials. What I found to be most interesting about this is that the author says that the "moment of truth" feeling we talked about Tuesday almost becomes diminished. Instead of their being a moment of truth, consumers just go immediately to google as their first search. I think I found this interesting because regardless if I'm watching the olympics, the Super Bowl, or just a daily rerun of ESPN, I too just google exactly what I'm looking for after commercials have been aired and I like a product I saw. I can take this personally because yesterday I bought a pair of shoes after seeing a commercial for it and google was in fact my first search.

Another thing I found interesting was the researchers educated guesses on what would happen with the Super Bowl advertisements. Because of the high elevated status and focus on the Super Bowl and its commercials, the authors expected that social media will positively influence viewer engagement on game day, and after the game has been played. I found this to be interesting because before I continued reading to see the results I immediately agreed with what their expectations were from personal experiences with the Super Bowl, and it simply makes sense that viewer engagement would be positively influenced by the brands and commercials. The results found were that the commercials on that day overall focus on the execution of the commercial, and the brand itself. I found no surprise by this because throughout younger life in elementary school through high school, the first question teachers ask are what commercials were the best and why? This engagement is proven true as kids throughout the class remember the ones that had an influence on them, and were often big name brands that kids would remember the next day. After this part of the article it has confirmed with me that the Super Bowl still generates massive buzz with its commercials and the brands that do it right often get remembered and talked about during and post game.

The third interesting point of the article in my eyes, were the results that ended up being given from the Super Bowl. The results stated that, 60-75% more people liked watching super bowl advertisements over regular television airings, and that 23% of viewers actually said the commercials are more important then the game. The last result that stuck with me is that over 70% of people said that they pay more attention to Super Bowl commercials over regular commercials. I found these results to be so interesting because it was nothing that I was surprised about. Personally, when I watch the Super Bowl and my favorite team, the LA Chargers, aren't playing, I focus more on commercials and advertisements too. I feel that many people are like this, and if it isn't because of their favorite teams not playing, some people may watch the Super Bowl that have no real interest in who wins or football. The results showed that tweets, texts, and social media conversations hold high value when it comes to brands and their Super Bowl commercials especially when compared to regular television advertisements.

3 questions:

Is the rarity behind Super Bowl advertisements and engagements actually because of brands, or is it because of the past where people just expect to see better and more numerous commercials on that day?

 With NFL T.V ratings decreasing will the buzz behind social media engagements and Super Bowl commercials ever reverse negatively? or will it continue to soar in the future?

Will a new brand ever make a commercial and make a splash on social media on Super Bowl game day  or will it continue being big brands like Doritos, Pepsi etc?

For class September 25

The assigned readings for this class session are all focused on the consumer. The consumer purchase decision and journey is what decides everything about the success of a marketer, so its very important to me and to everyone learning marketing. Three things that really stuck out at me during the readings were the history behind the consumer decision journey, the new use and importance of E-
WOM (Internet word of mouth) and company " moments of truth" which basically give a company the chance to make an impression to customers.

The first thing I found really interesting in the readings were the history behind consumer decisions. I had always thought that marketers and researchers had the upper advantage when it came to influencing consumers, but apparently that is not true. Because consumers had the leg up on purchasing power, companies have made recent changes to try to change that, where their marketing can influence people to buy. The updated action that businesses are taking include 4 steps that ultimately target the consumer. Those four steps include, engage experience through technology, use information about a customer, use knowledge about where the customer is in their journey, and to extend interactions through value and services.  Because customers have have the power right now, its very interesting to see how businesses can overcome that to gain control.

Another thing I found interesting in the required readings was the E-WOM, or internet word of mouth, and how big it plays in the consumers journey to purchasing. The biggest thing with the power of the internet word of mouth is that consumers are going away from traditional marketing and promotions, and simply wanna hear their peers experiences before purchasing similar   products. Because of this, brands are pressured to communicate through social media, as well as create really good products that are going to have high reviews and praises so other consumers buy. With big businesses like google+ and Facebook jumping in on the internet word of mouth, it is extremely important for a company's products to be good their, where millions of active users could be potentially listening to others experiences.

The last thing I found very interesting was company " moments of truth" that happen and ultimately define certain experiences. The Moment of truth is the contact point between companies and the consumer that overall give them a chance to make an impression. This is very important because like stated, its the "moment of truth" in which a company will bring a new customer in, or potentially fail to a competitor. What I found most interesting about this idea is how all big name companys are using moment of truths, like Amazon, Google, Facebook, and Proctor and Gamble, which all have heavily influences online.


3 questions:
If big companys like Facebook, Amazon, Google, and Proctor and Gamble use the importance of moments of truth and contact experiences, why wouldnt every business follow this model for success?

If customers have been in the drivers seat when it comes to purchasing power and influince, does that mean marketers have overall failed in recent years?

Will electronic word of mouth continue trending upward as the new way that consumers will purchase? if so what does that mean for businesses and their competitors?

What I learned Week 4

A different week of classes for me, I unfortunately didn't make it to either class due to being sick. With this being the case, I feel I probably lost a lot of valuable class time with what we had learned, and judging by class recaps it seemed everyone learned cross tabulation analysis.

Cross tabulation analysis seems to be a very important form of analysis for managers. The class example that got used was for Oreos, where the class used Simmons online database to find numbers on Oreos and learn how to interpret the numbers that they see. After extra lab sessions to catch up I will understand how to read Simmons data better to be fully caught up to speed with the rest of the class.

Because I didn't get to fully learn what my classmates did this week, another thing I learned from our readings was the consumer decision theory. This really focused on the consumer, and what is going through their heads as they purchase new products, and how marketing needs to change in order to continue being successful. The ultimate goal of marketers is to get consumers to purchase at the moment they are most influenced, so by understanding the customers better, the better position the marketer is in. One thing I found most important in this reading was the importance of touch points. Touch points are different things like advertising, news reports, commercials, or even just conversation with family or friends, it ultimately decides when a product "touches" the consumer it is trying to reach. I believe this was most important because to understand a customer and their behavior I think its even more important to understand how to reach the customer with products.

This week was a weird one, and I look forward to getting back to class action to not only catch up, but dive more in depth into the analytics and numbers that are class is moving forward into.

What I learned week 3

This weeks classes got the deepest they have yet in material, and we even took a full class to go over absolutely any questions that the class had. I wasn't able to attend Tuesdays class, but I understand that the class had a discussion about the interesting things they learned from chapters 4 and 6 of the HBR guide,  as well as an article that we were asked to read called "The Impact of Publicity and Advertising on Marketing and Company Performance." Thursdays class we played a little game to decide who would be asking the questions. One person would roll a die and the number it landed on would be the person to ask a question. Different questions were asked about sentimental analytics, linear regressions, correlations and causation, and it gave everyone an overall better understanding of the concepts.

The main things I learned in Thursdays class was the above concepts, although its stuff we learned in earlier chapter readings, the class discussion ensured confidence in understanding the material. Sentimental analytics is an algorithm that takes all data such as impressions, Facebook likes, tweets, shares, etc. and decides if the data they receive could be used positively or negatively. This was really crazy to learn because marketers do this on a daily basis and I know my own personal information every day gets analyzed and put into an algorithm to help push products of my own interest my way. The biggest example I can think of personally is when I will google something to find info on it or a price, and immediately their will be promotions for it while I search through Instagram posts. Once understanding the concept it becomes much more apparent in every day life.

We also talked about correlations with data, and how two variables can either have a complete correlation and one causes another, or there could be none at all. This information is important because when it comes down to taking risks using data, it is extremely important to understand if that data actually shows what you think it is. An example of correlation is for instance, when the weather is hotter, more people buy ice cream. With this information you know more ice cream gets sold in summer months. Although this is an obvious correlation, marketers and business owners analyze any data that helps them figure out correlations in their business. In my own online business, I have seen correlations with products we sold. We went from selling clothes and accessories, to kitchen, outdoor and garden products and saw a 20% increase in sales. The correlation was simple, it was easier to drop ship other products then clothes because people are afraid to buy clothing through drop shippers and wholesalers when theres many trusted company's already.

Overall Thursdays class discussion was very helpful and made the material we have learned so far more clear. I expect this next week of classes to be longer and even more in depth to marketing and analytics and I look forward to learning more about how marketers use data in ways to improve efficiency and overall profit.

Readings for 9/13/18

For our class discussion Thursday we were assigned to read chapters 9, 10, and 11. Chapter 9 talks about predictive analytics and how businesses use them regularly . Chapter 10 talks all about regression analyst, how they are used, their benefits, and errors that commonly get made. Chapter 11 focuses on correlations and the risks behind correlations with business's.

One thing I found interesting in chapter 9 was the use behind predicative analytics and how they are used more often then I thought. The reading gives examples like Customer lifetime value, and forecasts of sales for the next quarter, and I never realized how important this is in every business. I made a personal connection with this aspect of chapter 9 because I'm a very habitual buyer, with products and the store I get it from. Because of this, I see how important I am as a customer from the various places I spend my money at. Whether it is gas for my car, deli sandwiches, or the clothing I wear, I am very important to the customer lifetime value of the stores I go to. One thing I didn't fully understand was the data aspect of the predictive analytics. The author says that its important to make sure you use good data, but how does one specifically understand what is good data or bad? Without the knowledge of knowing what is good data or bad, I feel like the risk would still always be there to analyze it.

Another thing I found interesting in chapter 10 was the example used to explain regression analyst. Not fully understanding how regression analyst are used or when they are supposed to be used, the example broke it down to help me learn. The example used a business manager  trying to predict next months sales. I now understand why regression models are so important for business's as the variables that relate to the cause almost usually show a correlation. In the example there was a clear correlation with sales and rain fall, which directly effects their sales and how they go about promotions. The question I have for chapter 10 is the reading says that you must be specific to the data analyzer, but in what ways can you be most specific to not run into problems?

Chapter 11 teaches the importance of a correlation and when to act on it or not. What I found most interesting was the two most important reasons to decide if a correlation is worth taking a chance on. Those reasons were that confidence that the correlation will reliably happen again in the future, and the trade off between how big the risk and reward is. I found these important because I didn't know that before, and it stuck with me when thinking about future business risks myself. One example I think of is real estate, where my best friend and moms boyfriend are both heavily involved in. Correlations within the market, what other houses were sold for, and what are other houses are available definitely have a huge role in deciding what properties people end up with next. The question I have for this chapter is one chart shows that its worth it to go through with correlations when the benefits outweigh the risks, but is that always the case? is their ever cases of correlation where everything can look perfect but acting may still not be the best idea?