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Malhotra & Bhattacharyya (2022).pptx

The document discusses leveraging co-followership patterns on social media to identify brand alliance opportunities, highlighting the need for scalable automated methods. It illustrates how brand networks, created using publicly available Twitter data, can capture potential collaborations by mapping out audience interests across various industries. The analysis provides insights into brand connections and user relationships, emphasizing the dynamic nature of these interactions for marketing stakeholders.

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From: Malhotra and Bhattacharyya (2022) Leveraging Co-Followership Patterns on Social Media to Identify Brand Alliance Opportunities
From: Malhotra and Bhattacharyya (2022) Brand Alliances “By mashing up two bona fide brands, especially in diverse industries, the impact can be exponential” - Forbes (2020) Problem: Need for automatic scalable methods for identifying brand alliances across a broad ecosystem of brands Starbucks & Spotify Apple & Nike
From: Malhotra and Bhattacharyya (2022) Brand Networks for Identifying Potential Alliances Using publicly available co- followership data on Twitter to create network of brands. This can capture audience interests (and potential collaborations) across industries
From: Malhotra and Bhattacharyya (2022) Americanair Delta Spiritairlines Emirates United Starbucks Louisvuitton Spacex Facebook Disney Nfl Microsoft Expedia Intel Disneycruise Fourseasons Hilton Hyatt Radisson Ritzcarlton Westin Burberry Chanel Uber Amazon Victoriassecret Carnivalcruise Royalcaribbean Sierranevada Netflix Audi Bmw Lamborghini Mercedesbenz Armani Fifa Sony Nokia Skype Tagheuer Wimbledon Samueladams Subway Mcdonalds Ikea Craigslist Wayfair Olympics Pinterest Tesla Honda Apple Htc Lenovo Accenture Budlight Budweiser Cocacola Pepsi Kfc Redbull Spotify Chickfila Tacobell Oreo Bestbuy Guinness Urbandecay Lays Walmart Tropicana Cheesecake Godiva Lindt Snickers Sunchips Hersheys Lipton Dasani Paypal Homedepot Tjmaxx Safeway Sears Walgreens Adidas Reebok Colgate Neutrogena Blackberry Ebay Philips Xerox Yahoo Menards Hulu Jeep Infiniti Mazda Bulova Tagheuer Tissot Rolex Cisco Armaniwatches Salesforce Us Open Adobe Logitech Box Dropbox Oculus Azure Gap Bananarepublic Ralphlauren Prada Sephora Thebodyshop Illustrator −15 −10 −5 0 5 10 −10 0 10 x y Category a a a a a a a a a a a a a a Airlines Automotive Beer Cruise Dining FoodBeverages Lodging LuxuryGoods Media Miscellaneous Retail Sports Technology Travel Visualization of Brand Co- followership Patterns across Categories
From: Malhotra and Bhattacharyya (2022) Brand–Brand Asymmetrical Connections Mercedes Benz Louis Vuitton Nike Chanel Puma Converse Hublot Adidas Reebok Hugo Boss Nautica Bulova Diesel TAG Heuer Tissot Omega Rolex Seiko Armani watches Tommy Hilfiger Lacoste Outbound links from Mercedes Inbound links to Mercedes Leverage asymmetry for nuanced co-branding insights… • Top 20 brand–brand connections of Mercedes with brands in the luxury and retail categories. • The direction and weight of the edges represent the asymmetry and strength of the brand–brand connections. • For instance, the weight of outbound edge from Mercedes to Tissot represents the percentage of Mercedes’s audience that is interested in Tissot, while the weight of inbound edge from Tissot to Mercedes represents the percentage of Tissot’s audience that is interested in Mercedes.
From: Malhotra and Bhattacharyya (2022) • Brand networks make it easy to understand brand follower data for research and business application purposes. • Brand Network is a novel digital artifact to deliver insights into users and brands in a timely manner.  Data collection and network analysis fully automated.  Focus on broad ecosystem of brands in multiple categories. • User-brand relationships change over time— marketing stakeholders can watch how these relationships change over time Practical Implications