Letting the Computers Take Over: Using AI to Solve Marketing Problems

Letting the Computers Take Over: Using AI to Solve Marketing Problems

This article, "Letting the Computers Take Over: Using AI to Solve Marketing Problems," published on August 01, 2019, by Gijs Overgoor, Manuel Chica, William Rand, and Anthony Weishampel, addresses the growing need for businesses to leverage Artificial Intelligence (AI) in their marketing strategies. It highlights a common challenge faced by firms: the lack of a clear process for executing Marketing AI projects, despite the recognized potential of AI in various applications.

The Core Problem: Bridging the Gap in Marketing AI Implementation

The article identifies that while AI has proven its utility in areas like autonomous vehicles and customer service, its application in marketing decision-making is often hindered by a lack of structured methodology. Many companies aspire to use AI to enhance their marketing efforts but struggle with the practical implementation.

A Framework for Marketing AI Projects: CRISP-DM

To address this gap, the authors propose a systematic approach based on the established Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. This framework provides a robust, step-by-step process that managers can follow to successfully execute Marketing AI projects. The CRISP-DM methodology typically involves:

• Business Understanding: Defining the marketing objectives and requirements.
• Data Understanding: Collecting and exploring initial data to gain familiarity.
• Data Preparation: Cleaning, transforming, and selecting data for modeling.
• Modeling: Applying various AI and machine learning techniques.
• Evaluation: Assessing the model's performance against business objectives.
• Deployment: Implementing the AI solution into marketing operations.

Real-World Applications and Case Studies

The article further elaborates on how this CRISP-DM-based framework was utilized to develop three cutting-edge Marketing AI applications. These examples likely demonstrate the practical benefits and outcomes of applying AI systematically to marketing challenges, showcasing how AI can support and improve marketing decisions.

Product Details and Availability

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Related Topics and Products

The article is categorized under several related topics, including:

• Social media
• Analytics and data science
• AI and machine learning
• Marketing

Additionally, the page suggests related products such as:

• "When Should You Use AI to Solve Problems?"
• "Can We Solve AI's 'Trust Problem'?"
• "What It Will Take for Us to Trust AI"

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The page encourages user engagement through a review system, allowing customers to rate the product and write reviews. It also prompts educators to register as Premium Educators for academic discounts.

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In essence, the article serves as a practical guide for marketers looking to implement AI, offering a structured approach and real-world examples to overcome common implementation hurdles.