Improving external validity of stated choice experiments. This project aims to deliver more accurate estimates of choice behaviour by reducing biases due to choice task complexity in surveys as well as design artefacts. Extracting 'true' preferences is challenging, not only due to possible hypothetical bias, but also due to increasingly complex choice tasks and the existence of design artefacts. This project will investigate the latter two in the context of marketing, transport, health, and envi ....Improving external validity of stated choice experiments. This project aims to deliver more accurate estimates of choice behaviour by reducing biases due to choice task complexity in surveys as well as design artefacts. Extracting 'true' preferences is challenging, not only due to possible hypothetical bias, but also due to increasingly complex choice tasks and the existence of design artefacts. This project will investigate the latter two in the context of marketing, transport, health, and environmental economics, and proposes new methodologies to extract preferences that more closely reflect true behaviour in real markets.Read moreRead less
Harnessing Business Insights from Unstructured Customer Data. Resulting from customers’ widespread uptake of online channels to buy and communicate has been a surge in online reviews and social media posts. This textual information offers a viable alternative to surveys that Australian businesses currently conduct to obtain customer insights. However, these reviews are unstructured and require substantial pre-processing to extract underlying customer perceptions. Therefore, this project aims to ....Harnessing Business Insights from Unstructured Customer Data. Resulting from customers’ widespread uptake of online channels to buy and communicate has been a surge in online reviews and social media posts. This textual information offers a viable alternative to surveys that Australian businesses currently conduct to obtain customer insights. However, these reviews are unstructured and require substantial pre-processing to extract underlying customer perceptions. Therefore, this project aims to develop a novel machine learning approach to quantify the business-relevant information contained in textual information shared by customers online. This alternative approach will provide significant cost-saving benefits for a range of Australian companies, such as retailers, hotels, airlines and restaurants.Read moreRead less
Econometric Models for Marketing Decision Making. This project aims to develop methods to more efficiently allocate marketing resources across a range of media, including new media, such as the internet and social media, and compare them with with traditional media such as television and newspapers. To achieve this, the project will develop new methods and econometric models that employ data that capture both exposure to advertising media and downstream purchases at the individual-level. The exp ....Econometric Models for Marketing Decision Making. This project aims to develop methods to more efficiently allocate marketing resources across a range of media, including new media, such as the internet and social media, and compare them with with traditional media such as television and newspapers. To achieve this, the project will develop new methods and econometric models that employ data that capture both exposure to advertising media and downstream purchases at the individual-level. The expected outcome is that Australian companies will make more efficient use of their marketing budget, and better assess how to integrate new and old media into multimedia marketing communication campaigns.Read moreRead less
Innovative Use of Customer Data for Business Growth. This project aims to apply and adapt the latest machine learning techniques to enable companies to utilise their existing customer data to reveal purchase motivations, product preferences, and responsiveness to marketing communications for each single customer. A widespread practice in marketing is to partition customers into broad groups, but customers expect products and services that are tailored to their individual needs. This presents ex ....Innovative Use of Customer Data for Business Growth. This project aims to apply and adapt the latest machine learning techniques to enable companies to utilise their existing customer data to reveal purchase motivations, product preferences, and responsiveness to marketing communications for each single customer. A widespread practice in marketing is to partition customers into broad groups, but customers expect products and services that are tailored to their individual needs. This presents extreme challenges due to the size and complexity of customer databases. The expected outcomes will enable Australian companies to attract and retain more customers, and make more efficient use of their marketing budget. Benefits include equipping companies to better compete domestically and globally.Read moreRead less