6 Checkmarks Towards Quality Social Media Research

August 25, 2010 | 1 Comments

Almost anywhere you turn, someone is offering social media tracking, monitoring, measurement, evaluation, or some other form of analysis of social media data. How do you know whether you’re getting quality goods? Here are six things to checkmark before you get started on the journey.

Search Quality: What are the restrictions put around the data you are seeking? Are there methods in place to ensure the right data is being selected in and the wrong data selected out? If your brand is “Target, ” you need to make sure that the data is all about clothing and consumer goods (select in) and not about target practice (select out). Ask whether the data collection processes allow complex “and” and “or” searches so that data can be easily excluded and deliberately included.

Search Population: Is data being gathered from across the entire internet or just the top sites? There are pros and cons to each method. The top sites often account for up to 80% of all of the relevant data, but who’s to say whether the other 20% reflects a unique group of consumers whose voice could change how you think about your brand. You should at least know which process is being used.

Data Volume: Being blessed with millions of online records is a sweet luxury that only a few brands can achieve. But, unlike the survey world where 500 is a great sample size, this just doesn’t cut it in social media research. Most brands fall somewhere in between these two extremes, generating from hundreds to thousands of records each month. If your brand  generates just a few hundred records every month, you might be more suited to a qualitative approach to SMR and some efforts towards building a greater online presence. Brands generating thousands of records each month can take full advantage of both quant and qual approaches.

Scoring Quality: There are many different methods for scoring the sentiment of online conversations. What systems are being used? Is the scoring a manual process, automated, or combination of the two? Is it dictionary based or mathematical based? How do the systems accommodate the rapidly evolving English language? How do the systems account for new and emerging slang? And all the while, you need to remember that no system, not even a human being, can achieve perfect scoring. In this world, perfect isn’t 100%, it’s only 85%.

Coding Quality: Data isn’t useful until it’s categorized into meaningful chunks of data. Knowing that overall sentiment towards a brand is “Very Positive” does nothing to help you decide whether you need to build your product in a different color, shape, or size. But this isn’t an easy process. When Earl Grey Tea gets categorized into a color, you have no hope of generating valid insights from your results. Ask about the process of data quality in the coding process. Find out whether Charlie Brown is a color.

Coding Flexibility: Your brand is unique like no other brand. Your research objectives are like no other brand. There’s no reason to assume that the coding structure any other brand uses should be the same as what you use. Beyond the obvious requirements of purchasing, recommendations, trial etc., you have specific needs. Be sure to ask about how the coding can be customized to meet your unique requirements.
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Also appears in Social Media Today

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1. by Renee Malove

   On August 26, 2010 at 10:28 pm

   Thanks for this! It’s easy to get wrapped up in the social media hype and completely forget that you’re supposed to be running a campaign. Excellent post, thanks!

One Response to  “6 Checkmarks Towards Quality Social Media Research”