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The Next Wave of Digital Marketing: Predictive Marketing and AI

Core Content

This report, commissioned by Rocket Fuel and conducted by Forrester Consulting in 2017, explores the evolving landscape of digital marketing, emphasizing the importance of predictive marketing and artificial intelligence (AI) in delivering personalized, real-time customer experiences. The findings highlight that marketers are increasingly adopting AI-driven predictive marketing to overcome the challenges of managing vast amounts of data and delivering relevant, tailored interactions across multiple channels.

Main Viewpoints

• Predictive marketing is defined as the use of data science, particularly machine learning and AI, to make smarter marketing decisions by predicting which actions are more likely to succeed.
• Customer recognition is a fundamental component, as customers use multiple devices and channels, requiring marketers to identify individuals across these touchpoints.
• Nonlinear customer journey presents a significant challenge, as customer paths are no longer linear and require a holistic view of interactions.
• Real-time decision making is essential for timely, relevant, and personalized marketing, especially as customer attention spans decrease.
• AI-based intelligent decision making is seen as a key enabler to automate processes, surface insights, and deliver optimized, personalized customer experiences.
• Using first-party data over external data is crucial for gaining deep insights into customer behavior and interactions with the brand.

Key Information

Survey Overview

• The survey was conducted among 579 marketing decision makers responsible for programmatic marketing with at least $250,000 media spend per year.
• The study covers France, Germany, Italy, UK, US, and Australia.

Top Marketing Initiatives (Next 12 Months)

• 86% of marketers plan to improve personalization capabilities.
• 86% aim to drive customer-centricity.
• 84% want to achieve marketing that learns and optimizes from every interaction.
• 80% plan to increase customer loyalty and reduce churn.
• 80% intend to optimize marketing across the customer journey.
• 80% plan to increase the use of AI to drive marketing insights.
• 80% look to implement predictive marketing capabilities.
• 80% want to deliver consistent and optimized cross-device content.
• 80% intend to leverage their own data rather than external sources.

Challenges in Predictive Marketing

• 68% of marketers find it difficult to create a single customer view.
• 69% struggle with reaching consumers at multiple points along the purchase journey.
• 62% find it challenging to activate insights from analytics due to time constraints.
• 67% lack the necessary skills and expertise to implement AI.
• 65% find it difficult to leverage their own CRM data effectively.

AI Readiness

• 65% of marketers understand the potential of AI to change how they create and deliver value.
• 63% know that marketing activities benefit from AI.
• 63% have the right structure to deliver AI initiatives.
• 61% are already using machine learning in certain areas of marketing.
• 62% believe they have the necessary technology to execute their AI strategy.

Predictive Marketing Benefits

• 69% of marketers who have used predictive marketing for at least two years reported serving more relevant messages and improving personalization.
• 57% said they achieved higher conversion rates and greater ROI.
• 53% observed improved performance across the entire customer journey, from brand awareness to conversions.
• Predictive marketing allows for real-time, two-way, insight-driven interactions with customers, optimizing campaigns based on anticipated outcomes rather than observed behaviors.

Conclusion

Predictive marketing is positioned as the next wave in digital advertising, powered by AI and data analytics. It enables marketers to move from post-campaign optimization to predictive execution, delivering 1:1 marketing interactions that are contextually relevant and timely. However, the implementation of predictive marketing requires overcoming significant challenges, including data integration, real-time decision making, and the need for skilled AI partners. Marketers who successfully navigate these challenges are likely to see substantial improvements in efficiency, personalization, and overall marketing performance.