As associations strive to better understand their customers to provide excellent service and relevant products and services, social media strategy and data are growing sources of competitive advantage. Social media is a rich source of customer interests and preferences that complement other data sources, like your membership database, finance, and email marketing systems, to provide a 360° view of your customer.
Social Media Analytics is the process of collecting data from social sources, like Facebook, Twitter, or blogs, and analyzing that data to make decisions. There are three levels of social media analytics. Which level is your organization at?
Level 1. Social Media Management
Your organization likely has a basic strategy to engage on social media. You’re posting to popular platforms to build online presence and share content. You’re using a management tool such as Hootsuite or Sprout Social to connect multiple social media accounts and manage traffic in a single place. But is your association able to measure the effect of these interactions with customers and take action on this information?
Level 2. Social Media Monitoring
Also known as Social Listening, Social Media Monitoring (SMM) is the process of identifying and assessing what is being said about a brand or product in social media. Monitoring tools listen to online conversations for specific keywords. Common keywords include your twitter handle, hashtag, brand mentions, competitors, and links. Monitoring gives a high level view of overall brand sentiment, as well as real-time keyword alerts.
SMM can be used for brand awareness campaigns, improving customer service, finding new customers, or joining online conversations with customers or influencers. Popular SMM tools include Brandwatch, Brand24, and Mention.
Level 3. Social Media Intelligence
Social Media Intelligence (SMI) is the process of analyzing social media data to inform business strategy and guide decision making. It takes monitoring to the next level with a broader reach and deeper analysis of markets, customers and even competitors. This requires the use of more sophisticated tools that automatically mine millions of online conversations, using Natural Language processing and advanced algorithms to determine context well beyond a simple positive or negative.
It’s important to note that social media data is one of many sources that are part of a comprehensive data strategy. Learn more about the power of combining data.