14 years ago (March 21, 2006) Jack Dorsey sent the first Tweet signalling the beginning of a public conversation that has grown to encompass hundreds of millions of people around the world who share their thoughts, experiences and opinions as they happen. Not too long after that first Tweet our first API was launched, giving developers the ability to access and analyze data created from that public conversation. Like Twitter, the impact of social media data analysis has evolved considerably over the years. Today, people are tapping into Twitter data to support a broad array of information needs including measuring content and campaign performance, trend detection, influencer discovery and market research.
Based on my experience and personal observations working with hundreds of organizations over the years, when it comes to putting this unique data source to work to support better decision-making, most organizations can be categorized within three stages of social intelligence maturity.
In the first stage of maturity, it’s likely to be the marketing and communications teams engaging with social data - primarily using social media monitoring tools to track social media content performance and brand mentions for public relations and crisis alerting purposes. In fact, according to Twitter’s Social Data Insights Report (based on data from a study commissioned with the Harris Poll), 9 out of 10 companies use social data for marketing purposes. Metrics such as likes and follows as well as the volume of mentions and associated sentiment are front and center. At this stage, organizations tend to view social data analysis purely through an isolated lens of optimizing their social media campaigns and monitoring brand health. What’s missing is a broader awareness of the value that social data can provide across their organization.
Companies at this emerging stage of maturity would benefit from a few simple efforts that could expose the wider business to the value of social insights. "Oftentimes people have to experience social data for themselves before they really get it, so starting small with a defined project, and sharing relevant insights is key to growing adoption," says Jillian Ney, Founder of The Social Intelligence Lab.
At the established stage, social media data analysis branches out from the marketing communications function and starts to be viewed as a useful source of consumer insights. It, however, tends to be leveraged in an ad hoc, reactive manner with requests bubbling up from different parts of the business to whoever has access and training on the organization's social listening tool. And due to this lack of clear ownership, organizations are slow to develop competencies in this area and tend to have multiple social media listening and analytics tools which are underutilized or not fit for purpose. And while organizations at this stage are starting to get clear value from social media data, for the most part it remains a siloed data source not used in conjunction with other research methodologies and/or data sources.
Many organizations at this stage feel they have checked the box of social listening and yet are vastly underutilizing its potential. They would do well to clearly define their social listening objectives and align those with the key questions the business needs answering.
An organization becomes an innovator when social media data is viewed as an important and unique source of consumer intelligence, helping to make more informed decisions across their business. As a result, it is embedded into their market research and customer feedback management efforts. In these organizations, you typically find a central analytics or consumer insights team driving cross-functional data analysis efforts that encompass social media data, integrating it with other data sources such as their own 1st party data. These organizations are not only advanced users of their social media listening and analytics tools but are also comfortable working with raw social media data and connecting directly to the social media platforms’ APIs. This allows them to pull social media data into their business intelligence tools to look for patterns and relationships between various data sets. Some may even employ their own approaches to NLP(natural language processing) for topic modelling and sentiment analysis.
Organizations at this stage have gone beyond the simple volumetric analysis common of stage two behaviours and strive to understand the context behind social media conversations. Crucially, they understand social media data’s strengths, the questions it’s good at answering and when it should be utilized. Generally speaking, they excel at social media data analysis because they excel at data analysis and see it as a competitive advantage.
In the fourteen years since Jack’s first tweet, social media data analysis has become an accepted part of consumer research. It’s not without its challenges and detractors, but remains an incredible realtime source of insight into our moods and mindsets as well as our views on anything and everything from the trendy to the mundane. It is the world’s largest focus group, unique in its ability to provide answers to questions we didn’t think to ask.
So regardless of which stage of maturity you currently find yourself, if leveraging this giant focus group called Twitter is important to you, we are here to help. Visit data.twitter.com for social listening case studies, a list of Twitter Official Partners or to get in touch with our team. And if you are interested in social customer care, check out our maturity model on that specific topic.