We all have watched the digital revolution disrupt a century of economic, social and political norms and bring a variety of new opportunities—as well as unfamiliar and complex problems—across our desks. As a media psychologist and researcher, I am excited by the new approaches to audience analytics enabled by the digital and social technologies that let us “listen” to the consumer. Buzzwords such as big data and sentiment analysis reflect our eagerness to put large-scale data gathering and sophisticated analytical tools to use in hope of capturing new insights and improved predictive capabilities. The avalanche of data techniques and allure of new insights, however, can distract us from remembering three key facts:
- Data is about people.
- People adapt to changes in their environment.
- Data measures past activity, not what consumers will do in the future.
Integrating media psychology frameworks such as narrative inquiry into data analysis enables us to dig deeper and learn who our consumers really are and what they really want. Narrative patterns can reveal the stories and cognitive belief structures behind consumer behavior. This approach adds a depth of understanding to quantitative analysis and can improve our confidence in predictive analytics. It also gives us actionable insights to position products and processes to satisfy the customers of the future.
Measuring Behavior in Changing Times
Predicting human behavior requires us to make assumptions about cause and effect, which are proxies for the consumers’ priorities, motivations and goals. Due to habit, history or management directives, we may not question the underlying assumptions behind our analytical processes. While expedient, “doing business as usual” may perpetuate embedded cognitive biases that cause us to overlook the effects of our continually evolving media and technology- rich environment on consumer needs and expectations. We know that consumers, ourselves included, are adopting new ways to discover, connect and transact with information for both work and play. In doing so, consumers establish new behavioral norms that reflect changing life priorities and a redefinition of some very important beliefs—like what constitutes success, safety and acceptable risk.
Media psychology studies the implications of this intersection of human experience with media technologies. As a media psychologist, I use various tools to mine social media data for emerging themes and narrative patterns to shine a light on what matters to my clients: how shifting consumer beliefs, motivations, needs and goals impact engagement and product adoption. Narrative analysis brings in the human component. To be clear, it doesn’t replace quantitative analysis. It is a valuable addition that can provide a check on the behavioral assumptions and probe for deeper understanding to produce more robust audience profiles and actionable insights.
Consumer behavior is a manifestation of internal motivations and goals that reflect beliefs, assumptions and innate cognitive patterns in the context of socio-cultural experience. In a changing environment, behavioral drivers are fluid, not fixed. The confidence we had in predicting the future from historical behaviors is eroding. Relying on the past puts us all at risk of missing critical changes in future behavioral trends.
Media Psychology 101
Self-determination theory highlights the primacy of human connection, a sense of control over one’s actions and the ability to take action and achieve results.1 Recognizing these drivers helps us understand the adoption patterns of new technology and the appeal of technology-driven interfaces that increase consumer control over actions such as information acquisition and purchase paths …
We know people adjust their behaviors in response to technology. It is not true, however, that technology works in reverse. Yes, behaviors change, but deep-seated needs and goals do not. People are driven by the same primary needs that ensured their social and physical survival when we all roamed the savanna. Changes in technology enable people to pursue goals in different ways. Applying psychological science to technology allows us to get in front of trends. Like a surfer waiting to feel the swell, it lets us monitor movement in the sea of narratives.
Three theoretical groupings form the root of my approach to narrative analysis and allow me to tease out the “why” in the “what” of the data analysis.
- The innate drive for social connectedness, agency and self-efficacy
- Instinctive responses
- Social influence
This theoretical foundation allows me to make sense of patterns and trends. For example, people have flocked to social media in spite of consistent press coverage on the negative impact of virtual connections. Why? Empirically, it has been shown to have many positives that manifest in consumer narratives, such as the ability to facilitate the creation of social capital,1 support intimate relationships,2,3 and enhance individual agency and civic participation.4 The popularity of streaming entertainment and the ability to watch more than one episode of a show at a time, called “binge-watching,” underscores the changing patterns of viewer behaviors in response to the prevalence of portable and navigable streaming devices. It also indicates a more fundamental shift—the consumer’s desire for increased personal control over leisure activities and devices.5
There is a lesson for all businesses as we watch revenue from the global streaming companies like Netflix outflank box office sales.6 This is a trend toward increased individual agency that is disrupting many industries. As consumers realize they can have more choice and control, they increasingly demand it from the products and services they choose. Access to social technology, content and services in real-time—whether on Snapchat, Google Scholar or Amazon Prime—is changing expectations and priorities as they redefine social norms.
A World of Quicker-Than-Ever Response Times
Amazon’s business practices have changed our expectations about how long it should take to receive what we buy online. By offering Amazon Prime subscriptions that include “free” two-day delivery, they have made shipping a critical part of the value-proposition for all online shopping experiences …
Social norms are critical because they define the socially accepted “need” for any given product or service. We are seeing marriage and childbearing at older ages, delayed homeownership due to increased costs, and career paths adjusting to longer life expectancy. These trends, amplified by digital technologies, redefine what it means to be an “adult” and to have a life well-lived. These changes in turn impact perceptions of risk, success and safety.
Narrative analysis can identify the difference between behavioral shifts versus lags, highlighting new needs. Millennials who use Uber or Lyft instead of purchasing automobiles don’t need insurance. This trend also signals the preference for engagement via mobile devices. Understanding “why” helps companies design the right financial products.
Looking for “Why”
Narrative analysis has two main strengths:
- It captures the complexity of media experience in social context.
- Narrative shows the subjective and storied nature of life.
For consumer profiling, analyzing narrative patterns allows us to deconstruct the stories people tell about themselves and others. These stories expose perceptions, beliefs, priorities and desires, allowing us to derive insights about consumer intention and product-related cognitive frames.
Intention in Image
A valuable marker for intention is “image language”—evidence that a customer can “see themselves” using a company’s product. Because imagery is the precursor of symbolic representation, or language, the reference to image often reflects precognitive desire and perceptions of agency that lead to intention.
Qualitative Research in a Big Data World
Qualitative research traditionally has been restricted to small samples due to the time-consuming nature of the analysis. Thanks to innovative software programs, it can now be applied to social media’s large data files using text-based natural language programs …
Cognitive psychologists have long recognized visualization’s role in behavior change. Similarly, narrative researchers have identified visualization as the critical component in the persuasiveness of a story.7 Every planned action is accompanied by a visual image so we can see the steps necessary to accomplish our goals. We look for the presence of image in language as an indicator that desire has moved to intention. The visualization of a solution, such as buying insurance, is more potent than the need alone because it establishes the behavior path for goal attainment.
Narratives Are Frames
Throughout narrative analysis, we group, code and decode language and comments to identify the “frame” of an audience. Frames are innate mental structures that influence how we see the world. If a message doesn’t fit our frame, we ignore it.8 Frames form our natural cognitive processing patterns, guide our decision-making9 and impact our interpretation of information. For example, many people hold the frame that flying is more dangerous than driving in spite of staggering statistics to the contrary.10
Narrative analysis helps us identify consumers’ frames and expose perceptions of value and causality. We use frames to evaluate how well a consumer understands a company’s product and if the product is the exemplar (leader) or a follower in its category. A brand with a strong exemplar position becomes the label for its category—think Jell-O or Geek Squad. Identifying frames allows companies to construct more effective communications. When the message-frame fits salient consumer frames, the messages are more persuasive—whether it’s changing health behaviors or encouraging product purchases.11
Examining frames is equally important from the company’s side. Consumer analysis can uncover discrepancies between the company’s frame and the consumer’s actual goals that, unexposed, can thwart adjustment and innovation. Kodak, Blockbuster, Nokia and Borders are a few of the companies that stuck to their own frames and failed to innovate.12,13
Reframing: Actions Follow Beliefs
Changing the frame, or reframing, drives most marketing communication. Successful reframing allows the consumer to see things in a new way while increasing personal relevance, perceptions of need and buy-in. Without care, however, frames can constrain the value proposition. Something as simple as pricing can influence perceptions of a product being a good or bad deal. Consumers routinely perceive prices ending in .99 to be significantly lower than a price one cent higher (e.g., $2.99 versus $3.00).14
The Actuarial Connection
Sentiment analysis can be used on the nursing narratives of hospice patients to predict when a patient might discharge from hospice care to seek aggressive treatment, transfer to another facility, revoke their care due to an improvement in condition or in the event of death. This type of predictive model can aid in the analysis of expected Medicare reimbursements.
Reframing can effectively communicate a misunderstood brand or product. Canon effectively reframed its brand from a camera company to a more customer-centric storytelling brand.15 Marketers who are blinded by their own frame are in danger of creating campaigns that don’t deliver. Pepsi did not understand the frame accompanying #BlackLivesMatter, and its reputation suffered from a commercial showing a pop culture celebrity “solving” social injustice with a can of Pepsi.16 Nationwide Insurance underestimated social norms, generating negative responses by running ads emphasizing accidental child death scenes during the Super Bowl in 2015.17
Processes and assumptions become institutionalized in all businesses. The seismic social and environmental changes enabled by the internet and mobile access are amplified by coincident demographic shifts, as millennials begin to outnumber baby boomers and the U.S. population continues to become more culturally diverse. Social media data, while idiomatic and varied, can capture consumers’ stories so we can monitor changes in priorities and behavioral trends that don’t emerge in historical data.
Understanding the “why” along with the “what” of measured behavior is very powerful. Connecting big data with human experience gives us the ability to identify the consumer beliefs, priorities and intentions that manifest in purchase and engagement behaviors. These result in actionable insights throughout the product pipeline, and perhaps more important, create a process for improving the responsiveness and adaptability of future strategies.
- 1. Steinfield, C., N.B. Ellison, and C. Lampe. 2008. Social Capital, Self-esteem, and Use of Online Social Network Sites: A Longitudinal Analysis. Journal of Applied Developmental Psychology 29, no. 6:434–445. ↩
- 2. Yang, Hsing-Chen. 2014. Young People’s Friendship and Love Relationships and Technology: New Practices of Intimacy and Rethinking Feminism. Asian Journal of Women’s Studies 20, no. 1:93–124. ↩
- 3. Walther, J.B. 1996. Computer-mediated Communication: Impersonal, Interpersonal, and Hyperpersonal Interaction. Communication Research 23, no. 1:3–43. ↩
- 4. Picazo-Vela, S., I. Gutiérrez-Martínez, and L.F. Luna-Reyes. 2012. Understanding Risks, Benefits, and Strategic Alternatives of Social Media Applications in the Public Sector. Government Information Quarterly 29, no. 4:504–511. ↩
- 5. Steiner, E., and K. Xu. 2018. Binge-watching Motivates Change: Uses and Gratifications of Streaming Video Viewers Challenge Traditional TV Research. Convergence: The International Journal of Research into New Media Technologies, 1–20. ↩
- 6. Roxborough, Scott. Global Streaming Revenue Set to Outpace Box Office in 2019, Study Finds. The Hollywood Reporter, December 17, 2018, (accessed January 7, 2019). ↩
- 7. Green, M.C., and T.C. Brock. 2002. In the Mind’s Eye: Transportation-imagery Model of Narrative Persuasion, in Narrative Impact: Social and Cognitive Foundations, 315–342. M.C. Green, J.J. Strange, and T.C. Brock, eds. Mahwah, New Jersey: Lawrence Erlbaum Associates Publishers. ↩
- 8. Lakoff, G. 2004. Don’t Think of an Elephant!: Know Your Values and Frame the Debate—The Essential Guide for Progressives. White River Junction, Vermont: Chelsea Green Publishing. ↩
- 9. Kahneman, Daniel. 2011. Thinking, Fast and Slow. New York: Farrar, Straus and Giroux. ↩
- 10. Jenkins, Aric. Which is Safer: Airplanes or Cars? Fortune, June 20, 2017, (accessed January 12, 2019). ↩
- 11. Uskul, A., and D. Oyserman. 2009. When Message-frame Fits Salient Cultural-frame, Messages Feel More Persuasive. Psychology and Health 25:321–337. ↩
- 12. Thangavelu, Poonkulali. Companies That Went Bankrupt From Innovation Lag. Investopedia, October 15, 2018, (accessed January 3, 2019). ↩
- 13. Aaslaid, Katrina. 50 Examples of Corporations That Failed to Innovate. Valuer, November 22, 2018, (accessed January 6, 2019). ↩
- 14. Manoj, T., and V.G. Morwitz. 2005. Penny Wise and Pound Foolish: The Left-digit Effect in Price Cognition. Journal of Consumer Research 32:54–64. ↩
- 15. Vizard, Sarah. Canon on Reframing the Business to Avoid Further Smartphone Disruption. Marketing Week, May 11, 2018, (accessed January 3, 2019). ↩
- 16. Ibid. ↩
- 17. O’Reilly, Lara. Nationwide’s Super Bowl Ad About Dead Kids Was a Huge Buzzkill. Business Insider, February 1, 2015, (accessed January 8, 2019). ↩
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