Data Driven-Campaign Infrastructures in Europe: Evidence from Austria and the UK

Figures & data

Table 1. Classification of “types” of data.

Category	Data type	Description
Voter data	Public data	Data on voters held by public bodies which are made available to campaigns (i.e., voter registration data)
	Canvasing data	Data gathered through direct contact with voters, typically face-to-face or via phone conversations. Typically voting intention or other political attitudes.
	Purchased data	Data bought from a third party. Examples include data from “data-brokers,” such as lifestyle, purchase history or demographic data, or opinion polls.
	Social media data	Data on voters held by social media platforms, who campaigns can target by providing either a list of individual voters, or other targeting criteria
	Digital trace data	Data observed about voters from their online activity (i.e., browsing activity)
	Modeled data	Data based upon predictions made about voter preferences and/or characteristics from the data that campaigns already possess about them
Campaign data	Supporter data	Data held collected about the characteristics and activity of campaign activists/donors which allows them to efficiently mobilize them
	Evaluation data	Data which is collected to evaluate the effectiveness of the campaign and specific campaign interventions (i.e., message testing)

Table 2. Overview of case study parties.

Country	Party	Ideology	Date party created	Number of interviews	Interview codes
Austria	Social Democratic Party of Austria (SPÖ)	Social Democratic	1889	1	3
	Austrian People’s Party (ÖVP)	Conservative	1945	1	1
	Freedom Party of Austria (FPÖ)	Right wing populist	1956	1	2
	The Greens—The Green Alternative^a	Environmentalist	1993	1 (2 people)	4
	New Austria and Liberal Forum (NEOS)	Liberal	2021	1	5
UK	Labor Party	Social Democratic	1900	7	6, 7, 8, 9, 10, 11
	Conservative Party	Conservative	1834	3	12, 13, 14
	The Green Party of England and Wales	Environmentalist	1990	1	18
	Liberal Democrats	Liberal/Social Democratic	1988^b	3	15, 16, 17

^aIn 1986 there was a merger of Vereinte Grüne Österreichs and Alternative Liste Österreichs to form this party.

^bThe Liberal Democrats were founded through the merging of the Liberal Party and Social Democratic Party.

Table 3. Example questions.

Category	Example questions
Data practices	Within your party, what kind of activity is data used to inform? (strategy, policy development, communication, member management)? What are the sources of data used in your campaign? What insights are you trying to collect about voters? What information is most valuable for you? What kind of data analysis do you perform? Do you use data to create models? For example, voter targeting models, models about the likelihood of an individual being a supporter or being persuadable?
Perceptions of data	When you think of the word data, what do you understand this term to mean in the party context? What motivates the use of data in your political party? Would you describe your party/campaigns in the UK as data-driven? If not, Why?

Table 4. Coding schema.

Main code	Sub code (first phase)	Sub code (second phase)
Data practices	What are the Types of Analysis/Activities?	Modeling Segmentation Targeting Testing
	What are the sources of data?
	What is data used for?
	What data is valuable?
Perceptions of data	Is party data-driven?
	How is data understood?
	What are the motivations for using data?
	What is the history of data within [party]?

Table 5. Commonalities and differences in data-driven campaigning in Austria and the UK.

	Commonalities	Differences
Voter data	Targeting data held by social media platforms	UK campaigns collect individual level data on all registered electors from public sources UK parties append build individual level records with canvasing data and purchased demographic data UK parties model individual level characteristics Austrian parties collect less individual level voter data in an unsystematic fashion.
Campaign data	Engagement metrics provided by social media platforms A/B testing Membership data	UK campaigns measure performance during the campaign Austrian parties rather measure a campaign’s success after the election
Perceptions of data	Data deemed valuable. Data seen to optimize efficiency of electoral outcomes.	Greater concerns about ethics in Austria Austrian campaigns data-informed, UK campaigns data-driven

Table 6. Commonalities and differences in data-driven campaigning for parties of government and minor parties.

	Commonalities	Differences
Voter data	All parties target on social media All (UK) parties integrate public and canvasing data	Larger parties purchase more individual level data Larger parties use predictive modeling
Campaign data	Engagement metrics provided by social media platforms Membership data	Larger parties are able to test digital content at scale
Perceptions of data	Data deemed valuable. Data seen to optimize efficiency of electoral outcomes.	Resources impacts campaigns’ ability to be data “driven,” but also creates an incentive to campaign efficiently