Technological advances have opened up new opportunities for marketers, consumers, and marketing researchers. Marketers are leveraging new approaches for creating and capturing customer value (e.g., new product design, dynamic pricing) and communicating that value (e.g., social media influencers). Consumers are engaging in new ways with products, services, organizations, and each other. Researchers have access to new forms of data from multiple sources—and potentially new ways for their research to contribute.
In this special issue, we will publish papers testing new and improved methods for the future of marketing. These methods may collect insights from new sources, analyze new or existing data in new ways, combine data from multiple sources or multiple media, or improve on existing methods by analyzing data more accurately or efficiently. We share several examples below:
- New sources of data: A dramatic expansion in consumer genetic testing has allowed governments and firms to amass huge genomic data sets, and we are just starting to understand how these data can be leveraged to better understand consumer preferences (). Large language models (LLMs) have the potential to generate marketing research data (), though cautions have been raised about using recursively generated data (). Which other new data sources should marketers consider?
- New experiences: LLMs offer researchers new possibilities for designing products (e.g., ), creating new consumer environments (e.g., virtual fitting rooms; ), generating content (), and interacting with customers (e.g., virtual agents). What are the opportunities and limitations of these methods for customers, firms, and policy makers? How can researchers effectively utilize these opportunities in their research?
- New insights from traditional data sources: Longitudinal transaction data have been analyzed for decades, but new techniques may allow these data to offer new insights, such as flexibly estimating customer routines (). New techniques are also needed to draw additional insights from unstructured data, such as applying machine learning models to online review data () or adding metaphors to analyze marketplace sentiment ().
- New modality-specific frameworks: While there are emerging frameworks for text analytics (), there is still room for advancement (e.g., study paralinguistics). Marketing also needs more methodological guidance for modalities such as images and voice () and for multimodal channels such as video.
- New combinations of data from multiple sources, media, and modalities: JMR’s highlighted work combining data across sources and modalities, such as acoustic features, metadata, and text (). Recent work has combined sources such as social media post histories with survey responses (). Where are there opportunities for deriving new insight by combining sources and modalities at critical points in the customer journey?
- Improvements on existing methods: We’d also like to see submissions that focus on increasing the accuracy or efficiency of existing methods, such as more effectively eliciting sensitive information in surveys (), better measuring willingness to pay (), or reducing bias in estimates of endogenous regressors (). New methods may have practical benefits, such as improving the predictions of critical outcomes such as whether customers will return to a store () or increasing scalability, such as the ability to handle large video content ().
These are only a few examples; we look forward to reviewing your papers proposing and testing new and improved methods across behavioral, quantitative and strategy domains in marketing.
Special Issue Submission and Review Process
All submissions will go through JMR’s double-anonymized review and follow the journal’s standard norms and processes. Submissions must be made via , with author guidelines available here.
Submission deadline: September 15, 2025
Special Issue Editorial Team
The current JMR Coeditors—Rebecca Hamilton, Brett R. Gordon, Raghuram Iyengar, Kapil Tuli, and Karen Page Winterich—will handle submissions for the special issue.