Thanks Sophie!

Finally, we’d like to thank everyone who has played an invaluable role in supporting this project and helping to develop and encourage our ideas. In particular we want to thank our series editors @dkreiss.bsky.social and Nikki Usher, our colleagues and friends

We’re really proud of the vignettes after our 4 main chapters. We had leading experts write their own short accounts and hope these will be valuable for teaching DDC - so thanks @katieharbath.bsky.social @mcgregor.bsky.social Michael McEvoy, Jochen Koenig, Matthew McGregor, Hannah O'Rourke

We hope this book provides a framework for more in-depth, comparative analysis of DDC, helping us to understand how this practice looks in different national and party contexts. We look forward to engaging in lively debate about our ideas, so do reach out and get in touch.

If regulation is required we also suggest that data and privacy regulation isn’t the only route to reform. Changes to system, regulatory and party-level factors may help to induce more acceptable forms of DDC, suggesting a range of possible responses.

This is particularly important given our tendency to be cautious about new technology. But we also need to think about what is ok in different contexts - what's acceptable in Australia may be out of place in Germany. So there's unlikely to be a uniform response to DDC

We argue these findings are crucial for any attempt to think about the threat DDC practice poses. Rather than being one thing, DDC comes in different forms that may be more or less problematic. We shouldn’t, therefore, be inherently critical, but need to think about what is ok.

To explain this variation, we introduce a new framework that looks at systemic, regulatory and party-level factors and considers how, in each case, these influence the type of DDC. Discussing each in relation to our cases, we show how each factor can affect the form of DDC.

We show real variation, suggesting that DDC is not one homogenous practice, but something that varies by party and national context. DDC in Australia and Germany therefore look very different, raising questions about whether there are uniformly concerning practices in evidence.

To study how DDC varies, we then look at practice in Australia, Canada, Germany, the UK and US. Drawing on over 300 interviews with campaigners, we trace the types of data, analytics and tech used in parties - and the people involved in each process.

To understand DDC we think you need to know how each of these components is evident. We therefore classify each, outlining the forms of data, analytics, tech and personnel that can make up a modern campaign, providing frameworks to help guide future study.

We define DDC as “A mode of campaigning that seeks to use data to develop and deliver campaign interventions with the goal of producing behavioural or attitudinal change in democratic citizens.”
And we see a data-driven campaign defined by: Data, Analytics, Technology & Personnel

Our book sets out to demystify DDC by asking 3 questions:
1) What is data-driven campaigning?
2) How does it vary?
3) Why explains these differences?
Only by answering these questions can we work out if our concerns are justified, and what our options are for reform.

Modern election campaigns are now seen to be data-driven. We’ve seen campaigns use personal data, microtargeting, AI & analytics to try to win. Many of these practices have raised democratic concerns. But what exactly is a data-driven campaigning (DDC) & are our fears justified?