Data, Data, Data Everywhere
As consumers have embraced social media, they have discovered new ways to connect with friends, comment on products, interact with brands, and make buying decisions. This explosion in social behavior has resulted in an increase in data for marketers to leverage in gaining new insights about their customers. In response to the consumer adoption of social media, marketers now have:
- Social listening tools to “listen” to their customers and understand their sentiment, opinions, discussion
- Community management tools to engage with their Facebook audiences
- Facebook media tools to manage this new display ad medium
- Facebook app tools to engage fans and drive a deeper relationship
- Open Graph management tools to integrate the site and social experience
These are all great new tools to help marketers better manage their marketing initiatives in the new social landscape. However, these new tools also create both a challenge and an opportunity for marketers. The challenge is disparate data sets that are not connected and are under-leveraged as a marketing asset.
On other side, this is a fantastic new opportunity for marketers is to turn this data into a new marketing asset – connecting social behaviors with customers to drive more relevant marketing messaging. Here’s a framework to help you get started evaluating your social data sources.
- Identifiable: does the data source help you connect to a customer? Is the data permissioned for marketing purposes?
- Actionable: if identifiable, can this data source be used to power more targeted marketing – either via email, social, or site content?
- Scalable: how large is the population of identifiable and actionable records now and what is its expected growth.
For example, we are working through this process with a current client who has cataloged more than 15 social data sources. Their largest data set is social listening data – but it falls lower in the priority because it is less identifiable and actionable. Their site social data is smaller but more actionable and identifiable so it ranks higher on the data integration list.
Once these data sets are integrated, they can be used to improve marketing initiatives inside and outside the social landscape. We recommend developing repeatable use cases to help move from insight to action. Here are a few examples:
- Email messaging: target customers with relevant email messages based on products they like, wish for, or comment on
- Site personalization: display targeted content based on what they like or what their friends like
- Targeted Facebook posts: send a customized Facebook post to users based on their engagement with the brand
With some careful planning and process development, your currently disparate social data sets can be turned into a new marketing asset. So get ahead of your competition by connecting social behaviors with targeted marketing opportunities.