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2020 | OriginalPaper | Chapter

Digital Marketing Effectiveness Using Incrementality

Authors : Shubham Gupta, Sneha Chokshi

Published in: Advances in Computing and Data Sciences

Publisher: Springer Singapore

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Abstract

Digital marketing is one of the fastest-growing advertising channels and crossed the $330 billion mark in 2019. With exponentially increasing budgets, measuring the impact of marketing investments and driving effectiveness becomes essential for brands. The complexity of the digital ad-tech ecosystem is constantly evolving with brands running marketing activities across multiple channels, new targeting capabilities, and different formats. Due to this intricacy, traditional digital measurement metrics like cost per click, return on investment, cost per conversion, etc. just scratch the surface while measuring the actual impact of marketing strategies remains unsettled. We bridged this gap in marketing measurement by using the incremental lift as a metric to measure the impact of a marketing strategy. Incrementality testing is a mathematical approach to differentiate between correlation and causation. We formulated the Viewability Lift method by applying the concepts of A/B testing which can be implemented in the digital marketing ecosystem. In this method, we measure the effectiveness of an ad by comparing the users who are exposed to an ad versus users that are not exposed to an ad. Our methodology covers concepts of test environment setup, randomization, bias handling, hypothesis testing, primary output and understanding different ways of using this output. We used this output for digital marketing strategy planning and campaign optimizations leading to improved campaign efficiency.

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Literature
1.
go back to reference Saura, J.R., Palos-Sánchez, P., Cerdá Suárez, L.M.: Understanding the digital marketing environment with KPIs and web analytics. Future Internet 9(4), 76 (2017) Saura, J.R., Palos-Sánchez, P., Cerdá Suárez, L.M.: Understanding the digital marketing environment with KPIs and web analytics. Future Internet 9(4), 76 (2017)
3.
go back to reference Yuvaraj, C.B., Chandavarkar, B.R., Kumar, V.S., Sandeep, B.S.: Enhanced last-touch interaction attribution model in online advertising. In: 2018 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER), Mangalore (Mangaluru), India, pp. 110–114 (2018) Yuvaraj, C.B., Chandavarkar, B.R., Kumar, V.S., Sandeep, B.S.: Enhanced last-touch interaction attribution model in online advertising. In: 2018 IEEE Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER), Mangalore (Mangaluru), India, pp. 110–114 (2018)
4.
go back to reference Zhao, K., Mahboobi, S.H., Bagheri, S.R.: Revenue-based attribution modeling for online advertising. Int. J. Market Res. 61(2), 195–209 (2019)CrossRef Zhao, K., Mahboobi, S.H., Bagheri, S.R.: Revenue-based attribution modeling for online advertising. Int. J. Market Res. 61(2), 195–209 (2019)CrossRef
5.
go back to reference Du, R., Zhong, Y., Nair, H., Cui, B., Shou, R.: Causally driven incremental multi touch attribution using a recurrent neural network (2019). arXiv:1902.00215 Du, R., Zhong, Y., Nair, H., Cui, B., Shou, R.: Causally driven incremental multi touch attribution using a recurrent neural network (2019). arXiv:​1902.​00215
6.
go back to reference Gordon, B.R., Jerath, K., Katona, Z., Narayanan, S., Shin, J., Wilbur, K.C.: Inefficiencies in digital advertising markets (2019). arXiv:1912.09012 Gordon, B.R., Jerath, K., Katona, Z., Narayanan, S., Shin, J., Wilbur, K.C.: Inefficiencies in digital advertising markets (2019). arXiv:​1912.​09012
7.
go back to reference Vaver, J., Koehler, J.: Measuring ad effectiveness using geo experiments (2011) Vaver, J., Koehler, J.: Measuring ad effectiveness using geo experiments (2011)
9.
go back to reference Gordon, B., Zettelmeyer, F., Bhargava, N., Chapsky, D.: A comparison of approaches to advertising measurement: evidence from big field experiments at Facebook (2016) Gordon, B., Zettelmeyer, F., Bhargava, N., Chapsky, D.: A comparison of approaches to advertising measurement: evidence from big field experiments at Facebook (2016)
10.
13.
go back to reference Bounie, D., Morrisson, V., Quinn, M.: Do You See What I See? Ad Viewability and the Economics of Online Advertising (2017) Bounie, D., Morrisson, V., Quinn, M.: Do You See What I See? Ad Viewability and the Economics of Online Advertising (2017)
15.
go back to reference Davis, R.B., Mukamal, K.J.: Hypothesis testing: means. Circulation 114(10), 1078–1082 (2006)CrossRef Davis, R.B., Mukamal, K.J.: Hypothesis testing: means. Circulation 114(10), 1078–1082 (2006)CrossRef
Metadata
Title
Digital Marketing Effectiveness Using Incrementality
Authors
Shubham Gupta
Sneha Chokshi
Copyright Year
2020
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-6634-9_7

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