Marketing Data Science 2023: The Year of Causality

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What’s happening in the world of causal inference(CI)? Industry expert Judea Pearl shared his 2022 year in review, his report outlined the significant progress and challenges CI faced in the last year. From new techniques and methods, to updates on ongoing research projects and real-world applications, he provided key insights to the rapidly growing field.

His recap was a great reminder of this rise of causal inference and how it’s transforming machine learning and AI – which in return is changing the way we do business. It caused us to take a step back and think about what 2023 has in store for CI and how we can use it to empower our Revenue Scientist. 

Causal Inference in Marketing

Like Pearl said, causal inference has been taking many industries by storm. It’s being used in health care, finance and marketing and it’s gaining traction because it helps professionals understand the cause and effect relationship between different variables. By understanding these relationships, experts in these fields can make better decisions.

When it comes to marketing, CI has enabled marketers to become experts in their customer’s behavior. This kind of data enables marketers to understand the relationship between different decisions that influence consumer buying behavior – such as advertising, promotions, product designs and pricing. Marketers can move beyond correlation and toward a more precise understanding of the underlying causes of consumer behavior. This can lead to more effective marketing campaigns and ultimately, better business outcomes.

This is exactly what Dealtale does. Our dashboards use machine learning and causal inference to help marketers get better insights to their users. We were excited to see that Pearl had recognized us as one of the companies using CI to transform the marketing industry. For an example of our causal inference in action, check out our Worthy.com case study.

For a long time using methods like causal inference to evaluate cause and effect relationships was a task left for research and data science teams. With easy to use dashboards we’re making better data more accessible to marketers of all backgrounds.

Causal Inference: What’s Trending

In 2022, Gartner identified causal artificial intelligences as one of emerging technologies in their Hype Cycle. This got us thinking, how else might we see this technology being used in marketing? 

As businesses become more focused on using data, we see that understanding how different factors influence customer behavior is becoming increasingly important for marketers. Because of this, we are beginning to see new trends emerge in the field of marketing that make use of this CI to help make better decisions. 

Here are just a few of the ways we see marketing teams adopting causal inference in their day-to-day in 2023:

 

    1. Personalization and targeting: With the growth of data and sophisticated machine learning techniques, companies are using causal inference to personalize their marketing efforts and target specific segments of the population.

    1. ROI measurement: Companies are using causal inference to more accurately measure the return on investment (ROI) of their marketing campaigns and make more informed decisions about where to allocate resources.

    1. Attribution modeling: Companies are using CI to improve their understanding of which marketing channels are driving conversions and revenue. This allows them to make more informed decisions about which channels to invest in and how to allocate budgets.

    1. Prescriptive modeling: Companies are using causal inference to develop prescriptive models that can be used to recommend marketing actions for various consumer behaviors and make better decisions.

2022: The Year of Recognition for Causal Inference; 2023: The Year of Accessibility

As a company that specializes in causal inference, we’ve certainly noticed the significant increase in recognition that this field has received in 2022. This has been highlighted by the prestigious prizes such as the Nobel Prize in Economics, the BBVA Frontiers of Knowledge Award, and the Rousseeuw Prize for Statistics, all given to individuals and groups for their work on CI-related research accomplishments.

We couldn’t agree more with Pearl that 2022 was a game-changing year for causal inference. The awards and increased recognition have led to a surge in academic and commercial activities in the field.

We believe that with this rising popularity, use, and recognition, 2023 will be the year of accessibility for causal inference. As more people start to recognize the power of CI, we expect to see it used in more and more industries to solve pressing problems and move towards creating AI that’s on par with human intelligence.

If you’re ready to see how causal inference can transform your marketing strategies, we invite you to give Dealtale a try.

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