The Limitations of Social Media Monitoring

Like the life of the Internet at the close of the 20th century, there is a wild-west mentality that dominates the corporate conversation about social media.  Strategy is secondary as we scramble to find meaning behind numbers and learn to generate capital out of something that is still in its infancy. But for the most part, current social media monitoring stops with providing data.  Numbers are gathered around an area of interest, a few correlations are run between data points and the findings are handed off to the client without any emphasis placed on what the data means.  Data provides an answer to the question “what is happening” but fails to address why it’s happening. Anthropology works from an assumption of the inherent interconnectedness of people, focusing on culture as the starting point of investigation.

It seeks to connect the dots and uncover relationships between data points by going beyond the search for statistical significance and focusing on producing valid, actionable insights. “Validity” is the extent to which it gives the correct answer. Imagine a spike in Twitter conversations in late December with negative commentary about your company. The information is statistically reliable but it lacks meaning. It doesn’t even begin to approach an understanding of “why” in any meaningful way.  All too frequently, the questions asked and the metrics we assign to them have very little to do with the subtleties of human behavior. The data does not address who those people are, what social and cultural conditions are motivating the commentary, or how independent variables influence the data. The result is that we make assumptions and ask questions that are simply wrong.

To overcome these issues an anthropologically-trained researcher (or research team) filters data through a system of questions that tie each data point back to what we know about cultural patterns and trends. For example, if there is a spike in conversations about bacon, it might be tied to agricultural conditions, but it might also be tied to the fact that Anthony Bourdain talked about bacon martinis on his show the night before.  Add to that the fact that people who self-identify as “foodies” have doubled in the last few years and you start to realize that the conversation isn’t so much about the product, but how the product fits into the larger pattern of how people live their lives.  The spike in discussion reflects the need to be part of a special group with extensive knowledge that makes them extraordinary in the eyes of other people…or so they hope.

This same principles applies to all social media and online activity.  Whether your company is selling soap or helping people make multi-million dollar transactions, human behavior is usually more complex than the numbers alone would suggest.  This is where real opportunities lie.

Other companies have the same data you do.  They are searching the Web with the hope of uncovering something meaningful.  The good news is that they face the same dilemma of not being able to connect the dots between seemingly unrelated topics.  Uncovering these connections and understanding the reasons behind them means uncovering new revenue streams, new avenues of messaging, and new business opportunities before the competition can act.  Anthropology moves social media monitoring from “what” to “why” to “what next.”

By Gavin

Published by gavinjohnston67

Take an ex-chef who’s now a full-fledge anthropologist and set him free to conduct qualitative research, ethnography, brand positioning, strategy and sociolinguistics studies and you have Gavin. He is committed to understand design and business problems by looking at them through an anthropological lens. He believes deeply in turning research findings into actionable results that provide solid business strategies and design ideas. It's not an insight until you do something with it. With over 18 years of experience in strategy, research, and communications, he has done research worldwide for a diverse set of clients within retail, legal, banking, automotive, telecommunications, health care and consumer products industries.

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  1. Nice piece, great to see a market research viewpoint on social media monitoring. You identify some key issues in social media monitoring but I wouldn’t necessarily say they are limitations per se, more opportunities to identify where to direct your research, resources and business decisions.

    I think it is becoming a more regular occurrence that brands, agencies and other organisations are seeing social media data as an opportunity to gain insight and to tie the social data into what they already know or another existing in-house data set, be this ratings of some sort, transactional data or other to build a fuller picture.

    Social media monitoring offers an opportunity to identify trends, the spikes of which you speak, and give direction as to where to look for the what, where, why and when of such online conversations and what to do with that data set. This will be and should always be underpinned with an oversight of the industry within which the brand/agency/organisation operates but can get you there much quicker than more traditional market research methods and often in a more cost-effective manner too.

    Thanks for the opportunity to comment on your blog. Consider me subscribed!

    James Ainsworth
    Community Manager for Social and Web Solutions – Alterian

    1. I really like the article. I think to your point, there are significant gaps that are best bridged by using a mixed methodology and triangulating the results. Businesses are too prone to looking for a simple solution that yields only a partial answer — rely on ethnography alone and you’re in trouble, rely on statistical methods alone and you’re in trouble.

  2. Thank you for an insightful article. You write “human behavior is usually more complex than the numbers alone would suggest”. From a computational/anthropological point of view how would you quantify this complexity?

    Iason Demiros

    1. I would be disinclined to quantify it at all, or rather, I would be disinclined to think that the numbers tell the whole story. There are plenty of techniques out there for operationalizing the complexities — word frequency, word proximity, culture modeling, material culture alignment, etc. — all of which do a marvelous job of putting substantial numbers to what is said and what is seen. The dependent variables are easy to pin down, but the independent variables are harder and determining there affects are harder still. That isn’t to say that you don’t code and systematize, but it does mean that the outlier becomes as important in telling the tale as the center of the bell curve.

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