The COVID-19 pandemic forced many people out of the office and into work-from-home setups. Use of video conferencing platforms, especially Zoom, skyrocketed during 2020 as meetings, presentations, and interviews started having to take place online. Virtual presence has become critical to professional success, but all too many people have made errors ranging from the silly to the disastrous in trying to adjust to virtual work. This technical note explores best practices for achieving success in virtual presence and virtual presentations. From testing your technology to optimizing your background, adjusting your expression and tone for video presentations, and engaging with your audience, it will help you bring your best self to Zoom meetings and beyond.
External corporate communications and the rapidly changing ways in which companies engage with their customers received a lot of attention between 2010 and 2020. With social media, online chats, blogs, vlogs, and much more, consumers gained unprecedented access to corporate decision-makers, celebrity spokespeople, endorsement-driven athletes-even the US president. Internal communications, through which companies engage with their employees and inside stakeholders, changed just as quickly for organizations undergoing digital transformations during the same period-without receiving due attention. By mid-2020, the novel coronavirus (COVID-19) had made effective internal corporate communications even more essential. The virus shuttered the physical locations of many businesses, requiring huge swaths of corporate staff to work from home. As a result, employees became increasingly reliant on web-based tools-such as virtual meeting applications, email, Facebook, and Twitter-to collaborate, complete projects, stay in the loop on company developments, and simply keep in touch. This note explores the digital media and internal communications tools being used by firms worldwide, presents the importance of these tools, and gives examples from leading companies that are using information and communications technology.
The searchable internet contains almost 2 billion websites. And new, text-rich sites are being added at a rapid pace: more than 700 million popped up from 2016 to 2017, according to the International Real Time Statistics Project. A lot of this web-based text is relevant to marketers: online product reviews, information about purchasing behavior, customer-to-customer interactions, and transcribed tele-sales calls. Marketers now have more information from consumers in the form of written words than ever before. The problem, as with any extremely large data set, is determining how best to use the information. The relatively new fields of text analytics and sentiment analysis offer marketers a solution, enabling them to turn vast amounts of emotion-rich, word-based data into actionable information about consumers. This note explores dictionary-based sentiment analysis using programming language R; it also introduces empirical sentiment analysis.
Netflix Top Picks, Amazon recommendations, the iTunes Genius button. They all have one thing in common: they are driven by clever algorithms that use a technique known as collaborative filtering. Often used in machine learning operations, collaborative filtering is the process by which a firm like Netflix generates predictions about a single user's preferences using data taken from a large number of users. This technical note offers an overview of three of the main collaborative filtering methods: slope one, a purely predictive nonparametric model; ordinal logit, a parametric regression model; and alternative least squares, a matrix factorization technique.
In 2017, Disney announced that in 2019 it would launch Disney Plus, a subscription-based streaming video service that promised to rival Netflix, the dominant player in the market. This was the latest advancement in the history of movie rentals, which had first exploded in the 1980s with the advent of videotape and had gone through several technological transformations before reaching the age of streaming in the 2010s. At the time of Disney's announcement, Netflix dominated the market due to its ever-improving algorithmic recommendation system and its investment in original content. How would Netflix withstand the competition from Disney? What would be an appropriate measure of relative strength for a streaming service? This case offers a way in to discussions of customer lifetime value, market capitalization, and discounted cash flows, as well as the role of technological change in business models and firm valuation techniques.
Hundreds of thousands of would-be hoteliers have been popping up all around the world, hoping to rent their own homes and apartments to complete strangers through a service called Airbnb. The goal of Airbnb's aspiring hosts was to use the company's website to attract guests who were willing to pay the highest rates to stay in their homes for a short time. For Airbnb, the goal was to improve customer review performance so it could, in turn, increase profits. How could the company achieve its goal? Enter text mining, a technique that allowed businesses to scour Internet pages, decipher the meaning of groups of words, and assign the words a sentiment proxy through the use of a software package. In order for text mining to be useful for Airbnb, its marketing professionals first had to gain access to customer review data on the company's own website. The team then had to analyze the data to find ways to improve property performance. Was the team going to be able to leverage this large amount of data to determine a strategy going forward?
This case is used in the Marketing Analytics elective at Darden. A Sticks executive team is interested in opening a second quick-service restaurant in Richmond, Virginia. But before doing so, the team wanted to gain a better sense of who were Sticks' customers, which location would attract the best customers, and how to best connect with customers. An opportunity to gather survey data presented itself. Would the demographic and psychographic assumptions the team had gathered from talking to people in stores align with the survey answers? And what would the data suggest about where to locate new stores and about what marketing channels and messages to use to promote them?
This note provides a primer on paid search advertising, which is an important component of digital marketing. The mechanics of paid search is explained using the Google search engine platform. The note covers metrics for evaluating the performance of paid search, the strategic objective of paid search, the relationship between customer lifetime value and search ads, how to overcome sparse data problems using keyword clouds, and the nature of Google AdWords's enhanced campaigns.
This technical note presents the reason for using a binomial logic regression in marketing applications. It is used in Darden's "Big Data in Marketing" course elective. The issues surrounding the use of a linear regression model when the dependent variable is a dummy variable are identified. A consumer-utility-based behavioral rationale is presented for the applicability of the binomial logistic regression for modeling dummy variables. Simulated and real data examples are used to present the mechanics of the logistic regression and the interpretation of the outputs. The relationship between odds ratio and the logistic regression probabilities are presented. Application areas such as brand choice and customer retention are discussed.
This technical note provides a basic introduction to multiple linear regression. The concept of regression using a single independent variable is first introduced and then some of the practical challenges associated with it--including multiple independent variables in a regression--are discussed. Particular attention is paid to bias in the regression coefficients in the presence of omitted variables. The concept of the economic significance of a model is introduced and is contrasted with statistical significance. At Darden, it is used in a course elective titled "Big Data in Marketing."