2011 Nov 01

New Metrics for Social Media
David M. Raab
Information Management
November / December 2011

Today’s marketers are increasingly – perhaps excessively – focused on exploring social media. Efforts to date have largely aimed at attracting attention, viagra buy both through viral promotions (think: YouTube videos) and longer-term programs to build relationships (friends, fans and followers). But more sophisticated marketers are already looking at applications beyond message delivery. Here are some challenges they’ll face.

– response tracking. Marketers want to know how many people have seen their messages, how many have reacted, and what those reactions were. At the simplest level, this means tracking actions such as page views, recommendations such as “likes” and “plus signs”, registrations as friends or followers, and content sharing by emailing a link or posting it on their home page. Services like bitly and ShareThis make it easy to track sharing behavior, including re-sharing by people who received the original share. Some services can trace the re-shares back to the original sharer, providing a measure of individual influence.

– audience profiles. Traffic counts are interesting, but marketers care even more about whom they are reaching. Direct audiences include visitors to your Web site, readers of the company blog, and social media connections. Some direct audiences come with an ID that can link to an existing profile, either within the same system (a Facebook friend) or by matching to external data (a LinkedIn profile). In other cases, audience members remain anonymous but it’s still possible to gather data such as location or company (based on IP address), interest (based on search terms), or approximate demographics (based on the referring Web site). Indirect audiences include people discussing or reading about you in forums beyond your control, including blogs, news sites, and interest groups. Vendors like Quantcast and Compete.com build profiles of Web site audiences; in other cases, a forum host may make this data available.

– monitoring. Marketers may give a higher priority to talking than listening, but the good ones do both. In the social media world, monitoring involves scanning blogs, public forums, and discussion groups for mentions of the company, its products, and competitors. The simplest forms of monitoring count these mentions, which can be useful to measure mindshare vs. competitors, track public attention during a crisis, and read the awareness generated by an outbound campaign.

– content analysis. More advanced monitoring goes beyond counting to evaluate the content of social messages. This can identify topics and report on positive or negative attitudes. Content analysis is sometimes done manually, but this gets expensive when message volumes are large. Automated content analysis relies on semantic techniques to make sense of natural language. These systems already do a good job at some tasks, such as extracting keywords to identify topics and products mentioned. More subtle interpretations, such as understanding positive or negative sentiments, are still problematic.

– connections. Social networks often expose formal relationships among individuals, such as whether they are friends or follow each other. But this data can be difficult to process effectively using standard relational databases. Alternative database engines have been designed for social analysis, including Cassandra, FluidDB, and Neo4j. Their key capability is to navigate a network of social connections, making it (relatively) easy to identify friends of friends or friends with shared attributes. This supports analyses and selections that are very difficult or resource-intensive using standard database technologies.

– traffic analysis. Formal relationships are just the start of social analysis. It’s often more interesting to understand the interactions among related individuals: how often they message each other, the size or duration of those messages, whether messages are broadcast to a group or directed at individuals, whether there are patterns and how these change, and so on. Traffic analysis is often used by military, security and law enforcement agencies to infer organizational relationships. But it can also be used by marketers to identify influencers and to track dissemination of marketing messages.

– influence. The number of connections someone has, the number of messages they transmit, and the number of visitors they receive are crude measures of influence. More subtle metrics include how often someone’s messages are retransmitted, linked to, or commented upon, as well as who is doing the retransmitting, linking, and commenting, and how those patterns are changing over time. Vendors including Klout, Social Report, and PeerIndex provide various influence measures.

– case management. Social media are increasingly used for customer service. In fact, since “service” interactions on social media are often visible to the public, the distinction between marketing and service has almost vanished. Social media systems therefore increasingly include a case management component, allowing company staff to identify, track and interact with individuals over time. These interactions could also be managed through a conventional customer service system, but the public nature of social interactions means additional supervision is needed to protect the company’s image. Social media cases also extend beyond service interactions to include sales conversations and conversations with influencers, such as press, bloggers, and expert users.

– cross platform identities. Most individuals maintain separate identities for different social media systems, as well as other channels such as email, telephone, and postal address. Even though major vendors including Facebook and Google offer unified sign-in services, substantial fragmentation is likely to continue. This means that marketers who want to build complete relationship profiles will still need to capture and cross-reference individual identities across platforms. Systems are already in place to handle this sort of identity resolution outside of social media, so it’s most likely that social identities will be managed within the same framework.

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David M. Raab is a consultant specializing in marketing technology and analytics and author of the B2B Marketing Automation Vendor Selection Tool (www.raabguide.com). He can be reached at draab@raabassociates.com.

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