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The ethics of AI-powered marketing technology

Martech

AI has now enhanced this capability, but it also raises ethical concerns. However, AI also introduces a new legion of ethical considerations for marketers to navigate. Data privacy: The cornerstone of ethical marketing For years, data privacy has been one of the primary ethical concerns in marketing technology.

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4 Practical Tips to Avoid Confirmation Bias with AI

Vision Edge Marketing

Let’s look at these three common aspects of research to understand how easy it is for confirmation bias to play out, especially in market and customer research and competitive analysis: Literature Reviews : Conducting a literature review is a common first step in any research endeavor.

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Giles Palmer on Old vs. New Work Ethic

Oktopost

Listen to the podcast: For more thought leadership on work ethic, check out our Radically Transparent podcast on Apple Podcasts , Spotify , YouTube or LinkedIn. He spun Brandwatch out as a product company in 2006 and launched the first version of ‘Brandwatch Analytics’ in August 2007. Catch all episodes here. Episode Summary.

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The Top 9 Social Networks For Businesses

Marketing Insider Group

Competitor Analysis: Observing competitors’ social media activities can provide insights into market trends and uncover areas of opportunity. Transparent Privacy Policies: Clearly explain how user data is collected and used, and ensure users agree to these terms.

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AI-Powered Personalization in Marketing: Enhancing Customer Experiences

Navigate the Channel

Key Components of AI-Powered Personalization #1: Data Collection and Analysis The foundation of AI-powered personalization lies in collecting and analyzing user data. When predictive analytics are repackaged and repurposed as recommendations, they transform how people perceive, experience and exercise choice.

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The role of artificial intelligence in business in 2024

Sprout Social

NLP and sentiment analysis Natural Language Processing (NLP) and sentiment analysis enable businesses to understand and interpret human language, making them essential tools for analyzing customer feedback, social media content and other textual data while automating report generation.

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The future of marketing research

Modern B2B

By leveraging techniques such as natural language processing and sentiment analysis, AI can distil unstructured data from sources like customer reviews, emails, and social media posts into valuable insights. One of the most compelling applications of ML in marketing research is predictive analytics.