By Rich Pasewark
Social media data continues to grow at enormous rates each day, month and year. In fact, Facebook indicates that its system alone processes 2.5 billion pieces of content and 500-plus terabytes of data daily (and counting). That growth, however, contributes to the challenge of capturing, measuring and extracting insights from the big data produced on social networks.
After all, both the sources from which the data originates and the existing processes to gather the insights don't always fit the same mold as other customer data, such as sales figures or customer relationship management (CRM) records.
So what is the right approach for social media intelligence? The answer is counter intuitive: thinking about precise insights versus pure big data.
Leading marketers realize that insights gained from social media are not a result of capturing every post, tweet or blog mention, but rather zeroing in on the conversations that matter. With more than 400 million tweets being produced each day, it is essential to determine which ones meet an enterprise's set criteria - like about its brand, profile, sentiment or influence - in order to generate meaningful insight. What's more, it isn't necessary to store every mention to derive context or meaning for a brand. Identifying and analyzing only the content that matters should be the number one priority as it enables marketers and customer support teams to respond efficiently and effectively in the real-time model of social.
As marketing teams evolve, the key drivers of change are the increasing prominence of customer data and the rise of marketing automation. To inform data-driven decision making and program execution, marketing teams are responding by adding new tools and staff that understand how to work on large-scale automation initiatives.
For traditional CRM systems the focus is on the customer record. For marketers the goal of compiling this information has been to create a unified view of the customer from multiple records, including opinions from surveys, purchase behavior, demographic and even psychographic elements. Tying this information together is not easy, but the customer is still the common denominator.
Social media intelligence, however, changes this dynamic, as the data is more voluminous, anonymous and unprompted. Today, these same marketing teams have instant access to customers and customer segments, and understand immediately how they are feeling or reacting to something related to that company's brand or product. That means with proper information, marketing teams can determine what immediate action the brand should take, if any.
While the promise of social media intelligence is clear, it does create a challenge from a data perspective. Why? Social media data is unstructured. It doesn't follow a traditional pattern of customer records, and it doesn't follow the same construct as traditional market research data. For a long time, marketing teams have simply allowed this data to exist in a vacuum - failing to communicate and act on these customer records for the betterment of their enterprises.
Today, however, there is increasing pressure to combine social media intelligence with other forms of marketing data. This is where the sheer volume of content becomes a challenge. With social data increasing exponentially, IT and marketing teams don't have the infrastructure within their organizations to process and categorize this vast amount of data to drive decisions. Thus, the emergence of software as a service (SaaS) marketing platforms, which constantly capture and categorize that information for ready access, make a great difference for the data-driven marketer. These tools enable precise focus on the content that matters - without the overhead of systems, storage and support.
Discover the top platforms to gather and act on social media intelligence at wsm.co/sintelligence Zero-In on Relevancy
IT and technical marketing experts have an awesome opportunity to educate marketers on how to harness relevant insights from social media. Many marketers initially focus on data counts and basic measurements, instead of focusing on the rich data that matters. Proper tools and practices can enable marketers to hone in on the most influential and insightful data, and add timely support to modern customer relationships.
In order to focus on acquiring precise data, marketers must understand how to harness key information. By adapting social intelligence to business practices, it is easier to illuminate the most valuable information. For example, a marketer focused on an upcoming digital marketing campaign should configure their social analytics platform to capture information about the product and the brand at specific timeframes before and after launch. Doing so enables marketers to find insights that come from specific market segments such as moms, millennials, geo-located customers, advocates, detractors, and other categories and combinations.
Once this information is captured, it is important to be able to quickly showcase it in a dashboard or report that the marketer can leverage for internal and executive audiences. Frequently, this is done through the use of a social intelligence dashboard. Because marketers have many campaigns and programs in place at any given time, it is important to set up many of these intelligence dashboards in order to match a specific business objective or answer a specific business question. Again, the key is to get relevant insights that can drive action in a timely manner, using tools and best practices that help show meaningful results.
While marketers are shifting spend to social media intelligence, now is the perfect time for data experts and marketing savvy technologists to step in and guide enterprises to optimize the tools and best practices that can deliver actionable insight.
The most important thing to remember is that social marketers should create specific examples of leveraging social listening and analytics platforms with use cases, and determine which type of precise data will drive insights. Once that practice is established, take advantage of integrating those insights with other customer data, such as CRM or research results. This will drive more successful campaigns and programs - enabling efficient and effective management of the promise of big data and the necessity of precision.
Rich Pasewark is the former CEO of Visible Technologies, where he brought more than two decades of experience as a business leader, strategist and software visionary for industry leaders such as Quark, Adobe and EDS.