At this point, companies, like Socedo, can associate activities on Twitter to the leads in one’s marketing automation database, and tell you which of your existing leads is researching your product category or business space based on their Twitter activities in real-time. For example, if you’re selling business intelligence software to BI professionals who are using SQL Server, you’ll be able to see whom in your database is engaging with other BI/data visualization vendors, who just joined a professional group for SQL users, and who just followed one of your competitors. Conversion Data on Socially Engaged Leads Now you might think that Twitter is a really noisy place and wonder how many relevant signals you can actually get.
To answer this question, you’ll want to look at compare conversion rates for leads who have taken relevant actions on social media versus your baseline (all leads). The specific conversion metric you choose will depend on your use case. For example, if you want to use intent data to nurture your leads / personalize emails to increase engagement, you Italy Phone Number List may look at your lead-to-MQL rate and expect a higher lead-to-MQL rate for leads who’ve taken relevant social actions. Some of our customers have provided us with list of leads and let us analyze their data.
Once we’ve added historical social media activities onto lead records, we can segment our customers’ leads by behaviors, and use conversion rates (by segment) to determine the extent to which intent signals from social media are predictive of purchase behavior. In all cases, we found that socially engaged leads are more likely to convert compared to the typical or average lead in an organization’s database. One of our customers—one of the largest technology companies in the world—is currently tracking leads’ Twitter activities around their own product lines, competitors in the cloud computing space, and a few key topics in their space.