In political marketing, micro-targeting and personalization of campaign messages have become well-established communication strategies. What I will show in this post, though, is that tailoring the visual design of political communication assets might be of similar importance as tailoring of the message to win votes in political campaigns.
During the late 1960s, a new paradigm in the analysis of communications models which came to be referred to as ‘audience reception’ or ‘reception theory’ was introduced with Hans Robert Jauss as one of its main contributors. According to reception theory, the connotation of a text is created within the relationship between the text and the reader, and its meaning always will result from the readers previous life experiences and cultural background.
Stuart Hall, one of the main proponents of this theory, also came to develop his own approach to reception theory centred around television, which focus on the scope of “negotiation” and “opposition” by the audience based on the following reception models:
- Dominant (or ‘hegemonic’) reading
- In a dominant reading, the audience will share the same values as the sender of a message and fully accept the authors preferred reading.
- Negotiated reading
- The negotiated reading-model proposes that the reader broadly accepts the preferred/dominant reading but resists and modifies part of it to reflect their personal position.
- Oppositional (‘counter-hegemonic’) reading
- In an oppositional reading, the preferred reading is understood but rejected by the audience.
Hall’s model of ‘encoding/decoding’ has become one of the leading models of modern reception theory and is an effective instrument to understand how different audiences perceive information.
Reception theory in political marketing.
Hall’s model fits well in political marketing where the importance of identifying distinct issues of a voter segment and turning it into a message of communication (copy, imagery, graphic design) has been well understood since the dawn of political marketing.
Simplified, Halls encoding/decoding model translated to a political communication model can be illustrated as follows:
- Core voters fully agreeing with a political message -> Dominant reading.
- Mainstream voters agreeing with most but not all of a political program or message -> Negotiated reading.
- Voters of an oppositional party in total opposition to a political message – Oppositional reading.
Most political campaigns are structured around this model with distinct messages to each segment of core, mainstream, and oppositional voters. As an example; according to Issenberg (2013), one of the main reasons for Obama’s victory in the 2008 US presidential election was the way in which big data was used to identify significant segments of voters for which tailored campaign messages were created and communicated to. This enabled Obama to focus his main campaign messaging on the fundamental values of his politics summarised under the ‘Hope’ slogan—while he at the same time reaching out to highly specific audiences, such as military veterans normally voting Republican; directly addressing their biggest concerns with his political program and conclusively convincing them to vote for him.
Personalization of the message.
In the modern marketing vernacular, the terms ‘adaptive content’ and ‘personalised digital advertising’ have quickly become two of the hottest buzzwords (Chandra, 2017). The idea of this communication strategy is to deliver product offers, search results, messaging, and editorial content adapted to the interests and needs of distinct demographic- and psychographic audience segments.
According to reception theory, though, the connotation of a message will depend on—not only how the core message communicated in the copy—but also how the message is conveyed through the choice of colours, typefaces, the position of type and imagery, content hierarchy, and composition of photographs. In short, the connotation of any advert will depend on the reader’s personal psychographics, demographics, life experiences, cultural and religious background. To communicate efficiently, marketers, thereby, need not only to create efficient copy, but also need to adapt the design to the preferences of each audience segment the advert is targeting.
How political marketers can benefit from using an audience-adapted design strategy.
Modern political campaigning has become a game of statistical analysis and in the 2016 US-presidentials, all four leading political organizations (Republican, Democratic, Libertarian and Green parties) used big-data analysis and micro-targeting to win votes (Woodie, 2017).
While the paradigm of ‘audience-adaptive content’ and ‘micro-targeting’ in political marketing now are well-established concepts (Forbes.com, 2017; Preimesberger, 2017; Woodie, 2017); what is much less understood in this domain of communication is the impact of design when political marketing assets are decoded.
As an example. Visiting Hillary Clinton’s campaign website (Hillaryclinton.com, n.d) 2016-10-25 using my personal computer, my wife’s laptop and a friend’s mobile phone, it surprised me to see that even though the three of us having very different demographics and psychographics, I still got presented with the exact same model of design and messaging, and this was also repeated when visiting Donald Trumps campaign website (Donaldjtrump.com, n.d).
With my wife being a European female in her early thirties with no interest in American politics, my friend a hard-core republican soon turning sixty, and myself a strong liberal in the lower forties; the tree of us, according to reception theory, will decode both the design and the messaging of these websites very differently. To communicate more efficiently, adapting the design of these campaign websites to the distinct preferences of our demographics and psychographics, using the same targeting methods and technologies that already were in place for micro-targeting and delivering audience-adaptive messages (Forbes.com, 2017; Preimesberger, 2017; Woodie, 2017); both the Trump and the Clinton campaigns would have been much more efficient in their communication.
- Bibliography
- Adobe.com. (2017). Enterprise content management, ECM | Adobe Experience Manager. [online] Available at: http://www.adobe.com/marketing-cloud/enterprise-content-management.html#x [Accessed 15 Mar. 2017].
- Chandra, A. (2017). AdobeVoice: Why Personalization Is Key To The Future Of Marketing. [online] Forbes. Available at: https://www.forbes.com/sites/adobe/2014/05/12/why-personalization-is-key-to-the-future-of-marketing/#1956855ccd8a [Accessed 15 Mar. 2017].
- Donaldjtrump.com. (2017). SHOW YOUR SUPPORT FOR DONALD J. TRUMP. [online] Available at: https://www.donaldjtrump.com/ [Accessed 15 Mar. 2017].
- Forbes.com. (2017). Big Data Analytics And The Next President. [online] Available at: https://www.forbes.com/sites/metabrown/2016/05/29/big-data-analytics-and-the-next-president-how-microtargeting-drives-todays-campaigns/#54bc3beb6c42 [Accessed 15 Mar. 2017].
- Hall, S. (1973). Encoding and decoding in the television discourse Birmingham Centre for Contemporary Cultural Studies. 1st ed. [Place of publication not identified]: University of Birmingham.
- Hillaryclinton.com. (2016). Hillary Clinton 2016. [online] Available at: https://www.hillaryclinton.com/ [Accessed 15 Mar. 2017].
- Holub, R. (2013). Reception Theory. 1st ed. Taylor & Francis, p.14.
- Issenberg, S. (2013). The victory lab. 1st ed. Broadway Books.
- Machor, J. and Goldstein, P. (2009). Reception study. 1st ed. New York: Routledge.
- Preimesberger, C. (2017). Why Winning Politics Is Now Tied to Big Data Analytics. [online] Datanami. Available at: https://www.datanami.com/2016/05/10/winning-politics-now-tied-big-data/ [Accessed 15 Mar. 2017].
- Triblio. (2017). Personalized Content Marketing – Triblio. [online] Available at: http://triblio.com/personalized-content-marketing/ [Accessed 15 Mar. 2017].
- Woodie, A. (2017). Big-Data Analytics Plays Big Role in 2016 Election Campaigns. [online] eWEEK. Available at: http://www.eweek.com/big-data-and-analytics/big-data-analytics-plays-big-role-in-2016-election-campaigns [Accessed 15 Mar. 2017].