Data Strategy: Listen to Your Consumers’ Stories

The digital revolution has disrupted a century of economic, social and political norms bringing a variety of new opportunities as well as unfamiliar and complex problems.  As a media psychologist and researcher, I am excited by the new approaches to audience analytics enabled by digital and social technologies that let us ‘listen’ unfiltered to the consumer’s voice.  Buzz words such as ‘big data’ and ‘sentiment analysis’ reflect the eagerness to put large scale data gathering and sophisticated tools and algorithms to use in hopes of capturing the promised 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: 

1. data is about people; 
2. people adapt to environmental change, and 
3. data measures past activity, not what consumers will do in the future.  

Integrating media psychology frameworks and methodological approaches such as narrative inquiry into data analysis enable data and research teams to dig deeper and learn who their consumers really are and what they really want.  Narrative patterns reveal the underlying stories and cognitive frames and biases behind consumer behavior.  This type of analysis forms a bridge between qualitative and empirical that not only improves confidence in predictive analytics but gives decisionmakers actionable insights to position products and processes that can speak in the consumer’s voice and satisfy the customers of the future.

Measuring Behavior in Changing Times 

Predicting human behavior implies building models with a host of underlying assumptions about priorities, motivations and goals.  These are often accepted at face value or drawn unquestioningly from historical practices.  These assumptions create an embedded cognitive bias. This is not unique to any single industry but a result of doing “business as usual” in a world that is completely different.  

Today’s continually-evolving media and technology-rich environment enables a range of social behaviors.  Therefore, the underlying assumptions need to be frequently examined to see if they reflect the consumers’ current expectations and goals.  As consumers adopt new ways to discover, connect and transact, they establish new behavioral norms that can reflect previously unachievable goals, redefinition of life priorities and reevaluation of core concepts such as markers of success, safety, relationships and acceptable risk across the lifespan.  

Media psychology studies the intersection of human experience with media technologies.  It uses various tools to mine social media data for emerging themes and narrative patterns that shine light on what matters most for understanding future behavior: shifting consumers beliefs, motivations, needs, and goals.  Through narrative analysis, media psychologists bring in the human component to compliment quantitative analysis by providing a check on the behavioral assumptions.  It further anchors those assumptions to psychological and neuroscience theory for more robust audience profiles and actionable insights.

Measuring Behavior in Changing Times 

Behavior is a manifestation of motivations and goals.  These, in turn, reflect beliefs, assumptions, and innate cognitive biases that are a product of individual differences and socio-cultural experience.   In a continually evolving tech-enabled environment, assumptions and cognitive frameworks are fluid–not fixed.  Where once it may have made sense to predict from historical behaviors, relying solely on them today runs the risk of overlooking critical fluctuations in behavioral trends. 

There is little debate as to whether people adjust behaviors in response to technology.  They do.  It is not true, however that technology also changes deep-seated needs and goals.  People have been driven by the same primary needs that ensured their social and physical survival and wellbeing from prehistoric times to present.  These needs and goals can be conceptualized in theoretical clusters that are useful rules of thumb for decision making and hypothesis testing: 1) the self-determination theory’s triad of social connectedness, agency and self-efficacy, 2) instinctive and evolutionary responses, and 3) social influence. (See the sidebar for a brief explanation.) For practical purposes, these three theoretical groupings form the root for meaning-making and narrative creation and can effectively shift analytical understanding by implying a ‘why’.

While innate goals are psychological constants, goal attainment manifests differently as technology changes, providing a continuous menu of new mechanisms and avenues to achieve primal needs such as social connectedness and agency.  For example, in spite of naysayers focusing on the negatives of virtual connections, using social media has been shown to facilitate the creation of social capital (Steinfield, Ellison, & Lampe, 2008), support intimate relationships (Walther, 1996; Yang, 2014) and to enhance individual agency and civic participation (Picazo-Vela, Gutiérrez-Martínez, & Luna-Reyes, 2012).  The popularity of streaming entertainment on personal devices and the phenomenon of ‘binge-watching’ content also speaks to the trends toward the desire for increased personal control and agency over media consumption, much to the studios’ and networks’ chagrin.  

Redefining Normal

There is a lesson in the struggle for control between producers and consumers over consumers’ entertainment consumption.  This trend toward increased individual agency is disrupting other industries as well.  As consumers realize they can have more choice and control, they increasingly demand it from the products and services they choose.

Technology has altered the expectations and assumptions about what is attainable, normal and desirable.  Access to social connections, content, and services in real-time and largely unconstrained by geography or time, has shifted priorities, and instigated subtle and not-so-subtle modifications to behavioral trends and social norms.  Amazon’s Prime shipping, for example, has redefined shipping in consumers’ eyes, forcing other online companies to scramble to meet that hurdle.  (See the sidebar.)  

Expectations of fast response extends beyond shipping practices to other forms of customer service and engagement.  New understandings about response times influence the consumer’s more general mental model of how the world works and impacts social norms about all kinds of personal and commercial interactions.   Social norms are critical because they reflect the current conceptualization of core constructs that fuel the “need” for any product or service.  Lifespan changes, such as later marriage and childbearing, increased costs of housing, population density, and longer life expectancy with better health, coupled with the social norms of digital communication, are redefining what it means to be an “adult,” the role of marriage, timing of homeownership, and retirement as well as more nebulous concepts such as risk, success and desired life trajectories. 

Narrative analysis can highlight behavioral shifts versus lags and highlight new needs.  Millennials using Uber in lieu of purchasing automobiles don’t need car insurance.  Understanding ‘why’ helps companies know if it’s a shift or a lag.  Boomers faced with rising costs, lack of savings and reduced benefits are staying in the workforce longer. Understanding ‘why’ helps companies design different financial and retirement products.  

Looking for “Why”

Qualitative narrative analysis is employed in media psychology research for two main reasons: 1) media impact and experience is often difficult to empirically isolate since context is critical and 2) it shows the subjective and storied nature of life.  Combined with quantitative analyses, qualitative approaches offer a means of connecting the “what” of data with the subjective “why” of consumer-behavior.   

Qualitative research, traditionally restricted to small samples due to the time-consuming nature of analysis, can now be applied to social media’s large data files using text-based natural language programs that sort words and show networked relationships.  The idiomatic idiosyncrasies of conversation on platforms like Twitter, the variations across demographics and cultures, use of emojis and the tendency of people to respond in  kind have made machine-generated analysis of constructs like sentiment difficult to trust and operationalize without human intervention.   There are tools, however, that enable a qualitative approach at scale while still allowing for on manual oversight and manipulation.  As with most qualitative research, the critical phase is translating the output into supportable theoretical hypotheses to derive actionable insights.

Tools such as the software program Leximancer (Harwood, Gapp, & Stewart, 2015) is among those that allow a researcher to process large data files and identify preliminary thematic groups, narrative patterns, and visualize relationships at the macro level while retaining the ability to dive into any single data point for subjective confirmation of the narrative analysis. 

The Power of Narrative in Audience Profiling

In consumer profiling research, analyzing narrative patterns allows for the identification and deconstruction of the stories people tell about themselves and others.  These embedded stories expose their perceptions and beliefs as well as their priorities and desires.  Social media provides a wealth of providing personal, subjective snapshots—often literally– of the consumer’s life experiences.  The ability to analyze consumer stories provide insights about the drivers of behavior and decision making, such as intention and cognitive frames.

Intention in Image

One of the markers of behavior or attitude change is the ability to visualize, to see oneself adopting a new way of being.  A valuable marker for intention is ‘image language’ or evidence that a customer can “see themselves” engaging in the company’s desired activity.   

Imagery occurs prior to symbolic representation, the foundation for language.  The brain ‘speaks’ in image.  Image communicates the multi-sensory nature of experience prior to activating the cognitive processes that translate experience into spoken or written word.  Therefore, references to image often reflect precognitive impressions and internal perceptions of agency and efficacy.  

Visualization is the precursor to action and behavior change, from purchase decisions to indications of personal relevance.  Cognitive therapy has long relied on visualization in a therapeutic context and narrative researchers have identified visualization as a key component to narrative persuasion, the ability of a story to influence attitudes and interest  (Green & Brock, 2002).   Every planned action is proceeded by a visual image that enables an individual to cognitively anticipate and navigate intended goals.  The presence of image in language can indicate that desire has moved to intention and planning.  As a communicator, helping a customer visualize a solution, such as seeing themselves buying insurance, is more powerful than creating need alone.  

Narratives as Frames

Throughout narrative analysis, language and comments are grouped and decoded to identify and understand the ‘frame’ of an audience.  Frames, also known as mental models, social scripts and cognitive schemas or cognitive biases, are constructed out of beliefs and a synthesis of all interactions with the environment, culture, people, media,  and current context.  These external factors are moderated by cognitive processing patterns that simplify decision making by relying on heuristics to decrease the cognitive load (Kahneman, 2011).

In this way, frames become a powerful lens that color every consumer’s perceptions, expectations and plans.  Frames are sufficiently powerful that things like word choice or accompanying image can completely alter a consumer’s perception of information.  For example, stories reporting actions of ‘freedom fighters’ in lieu of ‘terrorists’ changes how readers interpret the moral intention and increases the likelihood of public support.  Similarly, most people view flying as inherently more dangerous than driving.  However according to the National Safety Council calculations in 2017, the odds of dying in a car accident were 1 in 114 as compared to 1 and 9,821 in an air accident over a lifetime (Jenkins, 2017, June 20). 

Using narrative analysis, we can identify consumers’ frames to better understand their priorities and perceptions of causality.  We can also evaluate if consumers understood a company’s product or even remembered their communications.  Information that doesn’t fit into a person’s frame is very difficult for people to understand and, if it significantly challenges a person’s frame, may result in hostility and avoidance due to the discomfort of cognitive dissonance.  When consumers’ conversations are full of comparisons to other products or services rather than reflecting the advertised product, it is an indication that a company has left a gap and missed the consumer’s frame. 

Examining frames is equally important from the company’s side.  Consumer analysis can be used to instigate conversations about the inherent assumption within a company.  If a company doesn’t understand the consumer’s frame, they can’t design customer-centric products or services or communicate the  benefits of their products to them.  Kodak, Blockbuster, Nokia, Yahoo and MySpace are a few of the companies who stuck to their own frames and failed to innovate rather than listen to the needs and goals of their customers.

Reframing: Actions Follow Beliefs  

Changing a one’s frame, or reframing, a key concept in cognitive-behavioral therapy and conflict resolution, drives most marketing communication with the goals of creating a need or desire or driving a purchase.

Changing frame facilitates behavior change because it allows the consumer to see things in a new way, altering expectations and beliefs.  For example, people react emotionally to potential loss, but more likely to take action for potential gains.  The frame constrains and often dictates the value proposition.  Even a brand name establishes a frame.  When Apple named the Apple Watch, they tapped into the “watch as time-telling device” frame and have had a hard time getting consumers to think of it as a fitness device.

Reframing can be an effective way to communicate a misunderstood value-proposition of any product or service.  Reframing begins with identifying one’s own frame and recognizing it as a frame rather than “truth.”   For many companies, this is the most challenging step.  Once companies accept that their perspective is just that, one point of view, they can see the validity in all and and that no one person has the right frame.

While reframing in conflict resolution suggests that no one person has the ‘right’ frame, in marketing, acknowledging the consumer’s frame is essential as a starting point to reinforce or reframe. Canon was able to effectively reframe their brand from a camera company to a more customer-centric storytelling brand.  Marketers who are blinded by their own frame are in danger of creating campaigns that either have no impact or, worse, create consumer backlash.  Pepsi’s did not understand the frame accompanying #BlackLives Matter and their reputation suffered after it ran commercials with the vacuous pop culture celebrity Kendall Jenner solving social injustice with a Pepsi in a faux protest march.  Nationwide underestimated the power of social norms and associated their brand with negative emotions and perceptions of manipulation by trying to sell insurance products by emphasizing accidental child death scenes in a Super Bowl ad. 

Conclusion

Processes and assumptions become institutionalized in all businesses. The seismic social and environmental changes resulting enabled by the Internet, and mobile real-time access is amplified by coincident demographic shifts, as Millennials begin to outnumber Baby Boomers and the US populations shifts towards a more culturally diverse composition.  Social media data, while idiomatic and varied, can capture varied consumer stories and voices to  monitor shifts in priorities and behavioral trends that don’t emerge in historical data. 

Today’s media-rich environment needs the ability to extract the ‘why’ behind behavior to accompany the ‘what’ of current quantitative approaches. Media psychology has a rich set of tools and theories, such as narrative analysis, that can be used by data and research teams to identify the drivers that influence consumer beliefs and behaviors.  This not only provides actionable insights throughout the product pipeline but creates a new process for improving the responsiveness and adaptability of future strategies. 

An abridged version of this article appeared in The Actuary.

REFERENCES

Ariely, D. (2009). Predictably Irrational. New York: HarperCollins.

Cialdini, R. B., & Trost, M. R. (1998). Social Influence: Social Norms, Conformity and Compliance. In D. T. Gilbert, S. T. Fiske & G. Lindzey (Eds.), Handbook of Social Psychology (4th ed., Vol. 1 and 2, pp. 151-192). New York: McGraw Hill.

Cosmides, L., & Tooby, J. (1997). Evolutionary Psychology: A Primer. Retrieved October 2, 2007, from http://www.psych.ucsb.edu/research/cep/primer.html.

Deci, E. L., & Ryan, R. M. (2000). The “What” and “Why” of Goal Pursuits: Human Needs and the Self-Determination of Behavior. Psychological Inquiry, 11(4), 227-268. 

Green, M. C., & Brock, T. C. (2002). In the Mind’s Eye: Transportation-Imagery Model of Narrative Persuasion. In M. C. Green, J. J. Strange & T. C. Brock (Eds.), Narrative Impact: Social and Cognitive Foundations (pp. 315-342). Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.

Harwood, I., Gapp, R. P., & Stewart, H. (2015). Cross-Check for Completeness: Exploring a Novel Use of Leximancer in a Grounded Theory Study. The Qualitative Report, 20(7), 1029-1045. 

Jenkins, A. (2017, June 20). Which Is Safer: Airplanes or Cars? Fortune. Retrieved January 7, 2019 from http://fortune.com/2017/07/20/are-airplanes-safer-than-cars/.

Kahneman, D. (2011). Thinking, Fast and Slow. New York: Farrar, Straus and Giroux.

Kahneman, D., Slovic, P., & Tversky, A. (Eds.). (1982). Judgment under Uncertainty: Heuristics and Biases. New York: Cambridge University Press.

Lysova, A. (2018). 3 Examples of Influencer Marketing in the Insurance Industry. Sensei Marketing,  (September),  from https://senseimarketing.com/3-examples-of-influencer-marketing-in-the-insurance-industry/.

Picazo-Vela, S., Gutiérrez-Martínez, I., & Luna-Reyes, L. F. (2012). Understanding Risks, Benefits, and Strategic Alternatives of Social Media Applications in the Public Sector. Government Information Quarterly, 29(4), 504-511. 

Spidermarketing (2016). Omnichannel Evolution. Retrieved January 2, 2019 from https://www.altitude.com/resources/omnichannel-evolution-of-customer-experience.

Steinfield, C., Ellison, N. B., & Lampe, C. (2008). Social Capital, Self-Esteem, and Use of Online Social Network Sites: A Longitudinal Analysis. Journal of Applied Developmental Psychology, 29(6), 434-445. 

Walther, J. B. (1996). Computer-Mediated Communication: Impersonal, Interpersonal, and Hyperpersonal Interaction. Communication Research, 23(1), 3-43. 

Yang, H.-C. (2014). Young People’s Friendship and Love Relationships and Technology: New Practices of Intimacy and Rethinking Feminism. Asian Journal of Women’s Studies, 20(1), 93-124.