Business Intelligence 8
Chapter 7 • Text Mining, Sentiment Analysis, and Social Analytics 447
COMMUNICATION NETWORKS Communication studies are often considered a part of both the social sciences and the humanities, drawing heavily on fields such as sociology, psychology, anthropology, information science, biology, political science, and econom- ics. Many communications concepts describe the transfer of information from one source to another and thus can be represented as a social network. Telecommunication compa- nies are tapping into this rich information source to optimize their business practices and to improve customer relationships.
COMMUNITY NETWORKS Traditionally, community has referred to a specific geographic location, and studies of community ties had to do with who talked, associated, traded, and attended social activities with whom. Today, however, there are extended “online” communities developed through social networking tools and telecommunications de- vices. Such tools and devices continuously generate large amounts of data that companies can use to discover invaluable, actionable information.
CRIMINAL NETWORKS In criminology and urban sociology, much attention has been paid to the social networks among criminal actors. For example, studying gang murders and other illegal activities as a series of exchanges between gangs can lead to better understanding and prevention of such criminal activities. Now that we live in a highly connected world (thanks to the Internet), much of the criminal networks’ formations and their activities are being watched/pursued by security agencies using state-of-the- art Internet tools and tactics. Even though the Internet has changed the landscape for criminal networks and law enforcement agencies, the traditional social and philosophical theories still apply to a large extent.
INNOVATION NETWORKS Business studies on the diffusion of ideas and innovations in a network environment focus on the spread and use of ideas among the members of the social network. The idea is to understand why some networks are more innovative, and why some communities are early adopters of ideas and innovations (i.e., examining the impact of social network structure on influencing the spread of an innovation and innovative behavior).
Social Network Analysis Metrics
SNA, the systematic examination of social networks, views social relationships in terms of network theory consisting of nodes (representing individuals or organizations within the network) and ties/connections (which represent relationships between the individuals or organizations, such as friendship, kinship, or organizational position). These networks are often represented using social network diagrams, where nodes are represented as points and ties are represented as lines.
Application Case 7.8 provides an interesting example of multichannel social analytics.
If Tito’s Handmade Vodka had to identify a single social media metric that most accurately reflects its mission, it would be engagement. Connecting with vodka lovers in an inclusive, authentic way is some- thing Tito’s takes very seriously, and the brand’s social strategy reflects that vision.
Founded nearly two decades ago, Tito’s credits the advent of social media with playing an integral role in engaging fans and raising brand awareness. In an interview with Entrepreneur, founder Bert “Tito” Beveridge credited social media for enabling Tito’s to compete for shelf space with more established liquor
Application Case 7.8 Tito’s Vodka Establishes Brand Loyalty with an Authentic Social Strategy
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448 Part II • Predictive Analytics/Machine Learning
brands. “Social media is a great platform for a word- of-mouth brand, because it’s not just about who has the biggest megaphone,” Beveridge told Entrepreneur.
As Tito’s has matured, the social team has remained true to the brand’s founding values and actively uses Twitter and Instagram to have one-on-one conversations and connect with brand enthusiasts. “We never viewed social media as another way to adver- tise,” said Katy Gelhausen, Web & social media coordi- nator. “We’re on social so our customers can talk to us.”
To that end, Tito’s uses Sprout Social to under- stand the industry atmosphere, develop a consistent social brand, and create a dialogue with its audi- ence. As a result, Tito’s recently organically grew its Twitter and Instagram communities by 43.5 percent and 12.6 percent, respectively, within four months.
Informing a Seasonal, Integrated Marketing Strategy
Tito’s quarterly cocktail program is a key part of the brand’s integrated marketing strategy. Each quarter, a cocktail recipe is developed and distributed through Tito’s online and offline marketing initiatives.
It is important for Tito’s to ensure that the rec- ipe is aligned with the brand’s focus as well as the larger industry direction. Therefore, Gelhausen uses
Sprout’s Brand Keywords to monitor industry trends and cocktail flavor profiles. “Sprout has been a really important tool for social monitoring. The Inbox is a nice way to keep on top of hashtags and see general trends in one stream,” she said.
The information learned is presented to Tito’s in-house mixology team and used to ensure that the same quarterly recipe is communicated to the brand’s sales team and across marketing channels. “Whether you’re drinking Tito’s at a bar, buying it from a liquor store or following us on social media you’re getting the same quarterly cocktail,” said Gelhausen.
The program ensures that, at every consumer touch point, a person receives a consistent brand experience—and that consistency is vital. In fact, according to an Infosys study on the omnichan- nel shopping experience, 34 percent of consumers attribute cross-channel consistency as a reason they spend more on a brand. Meanwhile, 39 percent cite inconsistency as reason enough to spend less.
At Tito’s, gathering industry insights starts with social monitoring on Twitter and Instagram through Sprout. But the brand’s social strategy does not stop there. Staying true to its roots, Tito’s uses the plat- form on a daily basis to authentically connect with customers.
Application Case 7.8 (Continued)
Used with permission of Sprout Social, Inc.
Chapter 7 • Text Mining, Sentiment Analysis, and Social Analytics 449
Sprout’s Smart Inbox displays Tito’s Twitter and Instagram accounts in a single, cohesive feed. This helps Gelhausen manage inbound messages and quickly identify which require a response.
“Sprout allows us to stay on top of the conver- sations we’re having with our followers. I love how you can easily interact with content from multiple accounts in one place,” she said.
Spreading the Word on Twitter
Tito’s approach to Twitter is simple: engage in per- sonal, one-on-one conversations with fans. Dialogue is a driving force for the brand, and over the course of four months, 88 percent of Tweets sent were replies to inbound messages.
Using Twitter as an open line of communication between Tito’s and its fans resulted in a 162.2 percent increase in engagement and a 43.5 percent gain in followers. Even more impressively, Tito’s ended the quarter with 538,306 organic impressions—an 81 per- cent rise. A similar strategy is applied to Instagram, which Tito’s uses to strengthen and foster a relation- ship with fans by publishing photos and videos of new recipe ideas, brand events, and initiatives.
Capturing the Party on Instagram
On Instagram, Tito’s primarily publishes lifestyle content and encourages followers to incorporate its brand in everyday occasions. Tito’s also uses the platform to promote its cause through marketing
efforts and to tell its brand story. The team finds value in Sprout’s Instagram Profiles Report, which helps them identify what media is receiving the most engagement, analyze audience demograph- ics and growth, dive more deeply into publish- ing patterns, and quantify outbound hashtag per- formance. “Given Instagram’s new personalized feed, it’s important that we pay attention to what really does resonate,” said Gelhausen.
Using the Instagram Profiles Report, Tito’s has been able to measure the impact of its Instagram marketing strategy and revise its approach accord- ingly. By utilizing the network as another way to engage with fans, the brand has steadily grown its organic audience. In four months, @TitosVodka saw a 12.6 percent rise in followers and a 37.1 percent increase in engagement. On average, each piece of published content gained 534 interactions, and men- tions of the brand’s hashtag, #titoshandmadevodka, grew by 33 percent.
Where to from Here?
Social is an ongoing investment in time and atten- tion. Tito’s will continue the momentum the brand experienced by segmenting each quarter into its own campaign. “We’re always getting smarter with our social strategies and making sure that what we’re posting is relevant and resonates,” said Gelhausen. Using social to connect with fans in a consistent, genuine, and memorable way will remain a cor- nerstone of the brand’s digital marketing efforts.
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450 Part II • Predictive Analytics/Machine Learning
Over the years, various metrics (or measurements) have been developed to analyze social network structures from different perspectives. These metrics are often grouped into three categories: connections, distributions, and segmentation.
Connections
The connections category of metrics groups includes the following:
Homophily: The extent to which actors form ties with similar versus dissimilar oth- ers. Similarity can be defined by gender, race, age, occupation, educational achieve- ment, status, values, or any other salient characteristic.
Multiplexity: The number of content forms contained in a tie. For example, two people who are friends and also work together would have a multiplexity of two. Multiplexity has been associated with relationship strength.
Mutuality/reciprocity: The extent to which two actors reciprocate each other’s friendship or other interaction.
Network closure: A measure of the completeness of relational triads. An individu- al’s assumption of network closure (i.e., that their friends are also friends) is called transitivity. Transitivity is an outcome of the individual or situational trait of need for cognitive closure.
Propinquity: The tendency for actors to have more ties with geographically close others.
Distributions
The following relate to the distributions category:
Bridge: An individual whose weak ties fill a structural hole, providing the only link between two individuals or clusters. It also includes the shortest route when a lon- ger one is unfeasible due to a high risk of message distortion or delivery failure.
Centrality: A group of metrics that aims to quantify the importance or influence (in a variety of senses) of a particular node (or group) within a network. Examples of common methods of measuring centrality include betweenness centrality, closeness centrality, eigenvector centrality, alpha centrality, and degree centrality.
Density: The proportion of direct ties in a network relative to the total number possible. Distance: The minimum number of ties required to connect two particular actors. Structural holes: The absence of ties between two parts of a network. Finding and
exploiting a structural hole can give an entrepreneur a competitive advantage. This concept was developed by sociologist Ronald Burt and is sometimes referred to as an alternate conception of social capital.
Using Sprout’s suite of social media management tools, Tito’s will continue to foster a community of loyalists.
Some highlights of Tito’s success follow:
• A 162 percent increase in organic engagement on Twitter.
• An 81 percent increase in organic Twitter impressions.
• A 37 percent increase in engagement on Instagram.
Questions for Case 7.8
1. How can social media analytics be used in the consumer products industry?
2. What do you think are the key challenges, poten- tial solutions, and probable results in applying social media analytics in consumer products and services firms?
Source: SproutSocial Case Study, “Tito’s Vodka Establishes Brand Loyalty with an Authentic Social Strategy.” http://sproutsocial. com/insights/case-studies/titos/ (accessed July 2016). Used with permission.
Application Case 7.8 (Continued)