Quantitative data is generally numeric in nature and can be used in true scientific analysis, with sample sizes of statistical significance and results that are repeatable.
Followers/fans: This is one of the most common metrics we see brands track. Be sure you’re not placing too much weight on this one. It may be gratifying to see growth, but if it’s not tied to something more meaningful, it’s just a number.
Engagement: An incredibly meaningful metric—perhaps one of the most important in measuring your own success and efforts—engagement can actually measure a host of different items depending on the channel. All of these different metrics combine to give you a sense for how well your audience is responding to your content.
For a blog post, this could be the number of shares and comments per post. On Twitter, this could be the number of mentions, retweets, favorites, and responses. Engagement tells you how well you’re doing in having conversations with your community and whether the content you create piques their interest.
Timing: Take a look at the timing of your community’s activity as well as your own. You want to ensure you’re active when they are. This is often overlooked, as many accounts are only managed during business hours, but that isn’t always when your customers are listening.
You can gain a general sense for when your target audience is online just by looking at the timestamps on their comments (and other activity), but you’ll get a much better idea if you use a tool that can analyze an entire audience. Check out the tools recommended in chapters 6-11 of this guide for examples.
Click-through rate (CTR): Click through rate is a familiar metric for most Internet marketers, and it can be valuable in social as well—especially if one of your goals happens to be driving traffic back to your website. Think of it as a sort of social conversion that you can work to optimize.
Qualitative data is based on observations, and it often takes the form of hypotheses that stem from smaller sample sizes than you’d normally need for a true scientific study. These hypotheses can then be tested using quantitative data.
Influence: This one’s a bit controversial. Everyone wants to find their community’s influencers, but there is currently no universal standard for measuring influence or finding those people. There are several tools available that offer “influence scores.” (Klout and our own Social Authority are popular ones.) Though if you choose to use such a tool, you should have a good sense for how it determines the score; you’ll want to ensure it aligns with what you are actually trying to measure. Beyond tools, also consider looking at Twitter and Google rankings for influencers within a certain topic. If you have access to a relevant forum and its data (perhaps your own), look for influencers there too. This can help you target the individuals that will have the audience you’re looking to reach. Our own Twitter tool, Followerwonk, can be a great resource for this type of research as well.
Sentiment: Sentiment analysis attempts to measure the tone and tenor of a conversation around a stated topic or item. In social media, this is largely used to tell if people love, can’t stand, or are neutral about your brand or campaigns. Most sentiment measurement tools are automated these days, and if you choose to go this route, you’ll want to make sure you understand the methodology behind the tool—particularly the margin of error—to help you understand the context of your reports. There are also manual sentiment analysis tools out there to use. However, there are many drawbacks to these including labor costs and your time. Not to mention that a really great manual solution may be much more expensive than an automated one.
Conversation drivers: With the right tools, we can look at nearly any platform (or all of them for that matter) and see what people are talking about. When it comes to your brand, you’ll want to know the topics and context of conversations about you, your competition, and your niche. This incredibly useful knowledge can tell you, for example, who your customers see as your closest competition, what they’re sharing in relation to your product, their concerns, etc. This is one of the most important and insightful qualitative measurements you can use.