{"id":47,"date":"2022-12-05T22:07:52","date_gmt":"2022-12-05T22:07:52","guid":{"rendered":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/chapter\/module-4-readings-and-videos-part-1\/"},"modified":"2023-03-13T20:16:15","modified_gmt":"2023-03-13T20:16:15","slug":"module-4-readings-and-videos-part-1","status":"publish","type":"chapter","link":"https:\/\/pressbooks.ccconline.org\/accmarketinganalytics2\/chapter\/module-4-readings-and-videos-part-1\/","title":{"raw":"Module 4: Reading and Videos Part 1","rendered":"Module 4: Reading and Videos Part 1"},"content":{"raw":"

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Recommendations and Approaches to Marketing Analytics<\/h1>\r\nHave you ever heard of six degrees of separation if not let this fun Ted Talk explain this in a fun video:\r\n\r\nCaution this video does contain some sensitive language.<\/span>\r\n\r\n[embed]https:\/\/youtu.be\/n9u-TITxwoM[\/embed]\r\n\r\n \r\n\r\nSocial network analysis identifies relationships, influencers, information dissemination patterns, and behaviors among connections in a network.\u00a0 Social network analysis results in visual maps that trace connections in the population and ultimately represent the size and structure of the networks.\r\n\r\nSocial networks provide an opportunity for companies to communicate with, and start conversations with, customers.\u00a0 Social network analysis ultimately provides a picture of the network.\u00a0 Companies can use this picture to better understand communities, influencers, and conversations that emerge.\u00a0 Social media interactions among participants in the network develop organically from the company\u2019s original post.\u00a0 Other companies also maintain brand pages.\u00a0 Some companies recruit influencers from their followers, like Sephora, while others collaborate or partner with already entrenched influencers.\u00a0 Regardless of the strategy, interacting with existing and potential customers through networks can introduce products or services, increase brand awareness, and improve sales.\u00a0 Using social network analysis, companies can monitor conversations about brands and relationships occurring from those interactions.\u00a0 Using these insights, companies can better understand consumption behavior and brand preferences.\r\n
A node is an entity \u2013 such as a person or a product.\u00a0 Edges are the links and relationships between nodes.\u00a0 Edges can explain friendship or family ties. This visualization enables viewers to understand the relationship between nodes and the importance of nodes.<\/div>\r\nMeasures of centrality indicate the influence a node has in the network and also a node\u2019s strategic network position.\u00a0 Degree centrality measures centrality based on the number of edges that are connected to the node.\u00a0 If the network is directed, there are two measures of degree: indegree and outdegree.\u00a0 Indegree is the number of connections that point in toward a node.\u00a0 Outdegree is the number of arrows that begin with the node and point toward other nodes.\u00a0 Nodes with a higher degree of centrality have more links and are more central.\u00a0 Betweenness centrality measures centrality based on the number of times a node is on the shortest path between other nodes.\u00a0 Betweenness assesses positional centrality, and it shows which nodes serve as bridges between nodes in the network.\u00a0 This measure helps identify individuals who influence the flow of information in the social network.\u00a0 Eigenvector centrality measures the number of links from a node and the number of connections those nodes have.\u00a0 It shows whether a node is well-connected to other nodes, who in turn are also well-connected.\u00a0 This is a useful measure to identify individuals with influence over the network, not just the individuals directly connected to them.\u00a0 The higher the eigenvector centrality value assigned to the node, the more the node has influence over the entire network.\r\n\r\nMarketers may want to predict the next most likely link to be established in the network and link prediction may help.\u00a0 With link prediction, the objective is to predict new links between unconnected nodes.\u00a0 Link prediction uses a variety of methods such as similarity and machine learning algorithms.\u00a0 When nodes are closer together, the more likely there will be a relationship between them.\u00a0 Using link prediction, future associations that are likely to occur can be more accurately predicted.","rendered":"

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Recommendations and Approaches to Marketing Analytics<\/h1>\n

Have you ever heard of six degrees of separation if not let this fun Ted Talk explain this in a fun video:<\/p>\n

Caution this video does contain some sensitive language.<\/span><\/p>\n