This document discusses various methods for conducting social media research for marketing insights. It describes primary research approaches like surveys and experiments conducted directly on social media. Qualitative approaches include observational research, ethnography, and netnography which adapts ethnographic techniques to online communities. Quantitative research methods covered include social media monitoring, sentiment analysis to determine attitudes, and content analysis to classify themes. The document cautions that social media research faces challenges like ensuring accurate sentiment analysis given linguistic nuances, and avoiding coverage errors from non-response bias.

1. SOCIAL MEDIA
FOR CONSUMER
INSIGHTS
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2. The Role of Social Media in Research
 Marketers rely on several variants of
marketing research to make decisions.
Options include:
 Secondary research – information already
collected and available for use.
 Primary research – information collected
solely for the research purpose at hand.
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3. Primary Social Media Research
 The possible approaches to collecting primary data
in social spaces include the use of consumer diaries,
interviews and focus groups, surveys, and
experiments.
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4. Qualitative Social Media Research
 Observational Research involves recording
behavior or the residual evidence of behavior.
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5. Qualitative Social Media Research
 Ethnographic Research occurs when marketing
researchers conduct field research by visiting
people’s homes and offices to observe them as they
go about everyday tasks.
 Netnography is a rapidly growing research
methodology that adapts ethnographic research
techniques to study the communities that emerge
through computer-mediated communications.
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6. Steps in Netnography
 Identify online communities.
 Select those with high traffic, high levels of
activity.
 Learn about the group’s culture.
 Select material for analysis.
 Classify material.
 Keep a journal of reflections about the data
collection.
 Use member checks to assess accuracy of
interpretation.
Social Media Marketing, 2e©
©Tracy L. Tuten and Michael R. Solomon 2015
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7. Quantitative Social Media Research
 Monitoring and Tracking
 Social media monitoring occurs by carefully
choosing and searching the appropriate key words
and the relevant social communities.
 This process answers four basic questions:
1. How many times was the search term found?
2. When was the search term found?
3. Where was the search term found?
4. Who mentioned the search term?
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8. Quantitative Social Media Research
 Sentiment Analysis refers to
determining how people think or feel
about an object.
 The analysis consists of four steps:
1. Crawl, Fetch and cleanse.
2. Extract entities of interest.
3. Extract sentiment.
4. Aggregate raw data into a summary.
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9. Quantitative Social Media Research
 The challenges of sentiment analysis
 Accuracy in gauging sentiment with automated tools
 Cultural factors, linguistic nuances and differing contexts
 Defining the sentiment dictionary
 Accuracy in the categorical data needed to make better
use of data
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10. Quantitative Social Media Research
 Content Analysis
 Deep insight into the text (or other content)
 Pieces of information are classified and analyzed
for themes
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11. Content Analysis Codes
 Context codes
 Respondent perspective codes
 Process codes
 Relationship codes
 Event codes
 Activity codes
Social Media Marketing, 2e©
©Tracy L. Tuten and Michael R. Solomon 2015
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12. Caution! Research Errors and Biases
 Coverage and Sampling Errors
 Coverage error is the result of a failure to cover all
components of a population being studied.
 Sampling error is the result of collecting data from only a subset,
rather than all, of the members of the sampling frame; it heightens
the chance that the results are wrong.
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13. Caution! Research Errors and Biases
 Nonresponse Bias
 Nonresponse error is the potential that those
units not included in the final sample are
significantly different from those that were.
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14. Potential Problems
 Volume of conversation
 Cultural factors in the meaning of language
 Multiple meanings – e.g., BP
 Accuracy in the categorical data
Social Media Marketing, 2e©
©Tracy L. Tuten and Michael R. Solomon 2015
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