Nathan Gilliat, one of my favorite bloggers on the topic of social media intelligence, recently posted a great discussion on Combining Social Media and Traditional Research.  Social media analytics - “buzz” trending, sentiment analysis, semantic analysis, profiling - are still very new technologies that have a long way to go before their results will be standardized, replicable, and able to stand up to the same academic research standards that we expect from traditional methodologies. I’ve listed some of social media’s relative merits to traditional research in a separate post, “the strengths and weaknesses of social media research“.

I encourage you to read Nathan’s missive on this topic, and I agree with it on pretty much every point. However, that doesn’t mean that social media analysis is without value; it can serve an valuable role as an exploratory tool, and can give competitive intelligence as part of a comprehensive research strategy that combines qualitative and quantitative research methods to fully validate and contextualize data collection efforts.

Envision some examples how social media analytics can be coupled with traditional research:

• Product launches: After traditional market research is complete and the product is launched, day-by-day social media mining can help to spot where additional “niche” research and rebranding should take place.
• Exploratory: Conduct a full spectrum of social media sentiment, buzz, and semantic analysis to identify research questions and hypotheses for traditional research efforts (surveys, focus groups, demographics, interviews, ethnographies, etc.).
• Instrument development and testing: After survey questions are developed, run them out on Facebook Polls or other social media to test them against a well-defined target demographic for quick, albeit superficial results and a good idea as to whether participants will interpret the question as intended.  With a little further mining, it may be possible after the poll to mine conversations regarding reactions to the survey questions.
• Monitoring: Utilize a social media analysis dashboard to monitor key markets for issues, trends, alerts that might require more in-depth public relations or marketing research to investigate.
• Confirmatory: A major social media analysis effort can be followed up by a targeted survey, demographics, or qualitative research effort to confirm the social media findings and establish a baseline for future confidence estimates, projections and extrapolation.
• Training and Customizing.  Some of the more sophisticated (middle market and higher) analytics providers have dashboards and technologies that can “learn” from a baseline to provide more accurate results.  This is particularly important when studying niche markets with unique languages, terminology, or other characteristics.  A traditional research effort including survey sampling can identify key online communities, lexicons, and other semantic information that could help improve the accuracy and utility of the social media research as a business intelligence tool.

There’s probably a lot more that can be said regarding combining social media analytics such as sentiment and buzz to securities, financial and investment markets that have their own research disciplines as well.

If anybody can share examples of how social media analytics have been successfully - or unsuccessfully - combined with other primary research methods, I’d love to hear them.

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