Social media is now a mainstream capability with hundreds of millions of active users on Facebook, Twitter, and LinkedIn. Although many of us are avid users of social media, how do we translate these metrics into actual value? To translate this data to value requires a three-part process.
First, collect the primary data associated with volume, reach, traffic, and conversions for your key accounts. These data points will be slightly different from platform to platform. For instance, on Twitter, you will care about your followers, keyword usage, participation in the form of replies and retweets, and web traffic referrals although each of these has a different role. In contrast, for Google+, the key metrics are related to page views, traffic, and keywords, since your Google+ profile is also a powerful search engine optimization tool for those who follow you. Facebook stands out because it also provides demographic and interest-based information, but often lacks the context and business interactions that users have on other social networks.
These primary measures will provide you with the basic information necessary to understand your social media activity, but they are not sufficient to provide companies with insight regarding the value of social media. To understand value, companies must take a second step of assigning relevant data to business processes.
For sales, this data may be as simple as tracking any social-based website referrals. For social participants, there may be data that equates their participation either with direct sales or with lead generation for that participant’s community. In the social gaming sphere, the expectation is that a viewer will need to see an offer at least 25 times before making a purchase conversion (source). Does your own social media outreach have a similar ratio? If so, will it help to increase your social output with appropriate messaging?
For innovation and research, it may be better to track projects or ideas originating from combing social media through sentiment analysis and keyword analysis. Are there specific themes that come up that align with your organization’s current marketing or product themes? If so, are you following the people who have the best ideas about these themes?
And for HR, you want to find both the thought leaders and the technical experts for key talent gaps in your organization. By aligning your primary social data with the key terms and time frames for your talent searches, you can figure out who stands out from a talent acquisition perspective.
The third step is to integrate this data with external third-party data to provide a geographic view of social media participants or to tie Facebook demographic information and preferences with key trends associated with those demographics. So, social media metrics end up being far more than just tracking “likes” and “tweets”; a proper approach requires a data warehouse of some sort that brings all relevant data sources together to get the social insight.
For sales, this may mean mapping social lead generation to geographic and industry-specific data sources. For HR, it may be more useful to link this information with ADP-related employment data. And in the research or innovation spaces, these social inputs could be appropriately linked to key research journals or articles.
You may wonder if the tools are already out there for social media analytics. The answer is Yes… at least in some regards There are hundreds of social media tools out there, with SocDir being a good source to check these tools out. You could spend weeks just trying out all of these tools, but they tend to be focused only on analyzing the data within a specific platform or set of platforms. To move from data to insight, link your existing social media data to your relevant business data to get an understanding of how social media actually affects sales, marketing, service, HR, and other business departments. Without the data, all this is simply a guess.
As you start designing your social media metrics, I recommend that you set up your analytics and data integration tools before starting the campaign. The reason for this is that with the ephemeral and Big Data nature of social media, it is easy to track many social media trends in real-time or near real-time, but data that is more than a few days old can be very expensive to find and organize. By collecting information every few minutes rather than every few days, companies can make social media-based decisions with all relevant data. This will allow your organization to progress from simply collecting social data to gaining social insights for your business.