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Reading: What’s the Difference? – A Social Media Monitoring Strategy that Analyzes Intentions Instead of Mentions
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SmartData Collective > Big Data > Data Visualization > What’s the Difference? – A Social Media Monitoring Strategy that Analyzes Intentions Instead of Mentions
AnalyticsData VisualizationMarket ResearchPredictive AnalyticsSentiment Analytics

What’s the Difference? – A Social Media Monitoring Strategy that Analyzes Intentions Instead of Mentions

Jennifer Roberts
Last updated: 2012/03/07 at 6:18 PM
Jennifer Roberts
4 Min Read
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At CI we talk a lot about analyzing consumer intentions, extracting consumer expressions of preference with regards to products, viewing intentions or services from social data.  We talk so much about it that sometimes we fail to fully explain why a social media strategy focused on understanding consumer expressions of intent is so much more valuable to a company than one that relies on volume-based monitoring. Both are important metrics of value but only one can show how specific campaigns, advertising or other outreach efforts are influencing concumser behavior and impacting ROI.

Contents
Counting MentionsWhat’s the Big Deal with Intentions

At CI we talk a lot about analyzing consumer intentions, extracting consumer expressions of preference with regards to products, viewing intentions or services from social data.  We talk so much about it that sometimes we fail to fully explain why a social media strategy focused on understanding consumer expressions of intent is so much more valuable to a company than one that relies on volume-based monitoring. Both are important metrics of value but only one can show how specific campaigns, advertising or other outreach efforts are influencing concumser behavior and impacting ROI.

But what’s the difference really? What are the unique insights these data points provide?

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Counting Mentions

What is a mention? A mention is simply a record that your brand has been used by a consumer in a blog posting, a tweet, a Facebook status update, etc. For example, a mention may look something like this:

Of course, when you begin to aggregate those mentions into charts and graphs,you can derive additional insights into consumer activity, like:

  • trending information –  level of activity over time
  • anomalies –  conversation activity spikes or falls
  • competitive – brand value changes across a competitive landscape

The downside of mentions is that they don’t provide any context, like is a consumer responding to a new ad or discount; nor does the mention explain ‘the why’ driving the conversation, like is a consumer delighted with a purchase or identifying a favorite show from a fall lineup. Not having this broader understanding of the drivers of consumer conversations limits not only what an organization is able to understand about a customer but the ability to appropriately engage with a customer with relevant information.

What’s the Big Deal with Intentions

Now that we’ve defined mentions, let’s expand our analysis to define consumer intentions. For example, consumer intentions can be defined as consumers expressing:

  • an intent to purchase or view
  • loyalty, affinity
  • problem with a product or service

There’s a lot of great information contained in these charts and yet they don’t represent the only way to track consumer language around purchasing or affinity. What they do is provide an example of how an organization may want to begin to looking at their social data. Monitoring the competitive landscape in a context that tracks consumer activity as it relates to outreach efforts means bringing an ROI lens to your outreach effort. Now you can begin to monitor the influence of ads and campaigns on consumer conversations and ultimately purchasing data. Being able to extract language around consumer behavior provides much more robust insight into consumer behavior than a simple mention.

Architecting a social media analytics strategy that is able to track  consumer reactions and intentions will provide your organization with actionable insights instead of passive data.  This more robust social data allows an organization to add to and extend their understanding of their consumer and provide predictive and real-time insights into the effectiveness of campaigns and other outreach programs.

Jennifer Roberts March 7, 2012
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