What Marketers Can Learn From Machine Learning Concepts - Mohamed Helmy.pdf
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Machine Learning 🦾 is a subfield of Artificial Intelligence that uses statistical techniques to give computers the ability to 'learn' with data, without being explicitly programmed. Simply put, ML models improve their predictions over time with experience 🤓. They are designed to be agile, adaptive, and continuously learning 📖 - attributes that any successful digital marketer should possess. So here's a quick look into concepts that you can adapt to become successful as well, and avoid being "replaced" by another agile resource 🤷
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What Marketers Can Learn From Machine Learning Concepts - Mohamed Helmy.pdf
- 1. Linkedin.com/in/mohamed-helmy Linkedin.com/in/mohamed-helmy What Marketers Can Learn From Machine Learning Concepts
- 2. Linkedin.com/in/mohamed-helmy Linkedin.com/in/mohamed-helmy AI can advance Marketing in many ways ● Audience Analysis ● Budget Optimization ● Outcome Prediction ● Personalized Content Creation ● Automated A/B Testing
- 3. Linkedin.com/in/mohamed-helmy Linkedin.com/in/mohamed-helmy Why Think Like Machine Learning in Digital Marketing Machine Learning is a subfield of Artificial Intelligence that uses statistical techniques to give computers the ability to 'learn' with data, without being explicitly programmed. Simply put, ML models improve their predictions over time with experience. They are designed to be agile, adaptive, and continuously learning - attributes that any successful digital marketer should possess.
- 4. Linkedin.com/in/mohamed-helmy Linkedin.com/in/mohamed-helmy Applicable ML Concepts Data-Driven Decision Making Just like ML models that learn from data, digital marketers need to make decisions based on data analysis. This means continuously collecting data from campaigns, analyzing outcomes, and adjusting your strategies accordingly. Embracing the Learning Mindset Just as an ML model learns from its mistakes, digital marketers need to adopt a similar learning mindset. This includes reviewing what didn't work, understanding why it didn't work, and tweaking your strategies to improve future campaigns. Iterative Optimization Machine learning models work on an iterative process - they make a prediction, measure the error, and then adjust their parameters. After launching a campaign, closely monitor its performance, make necessary adjustments, and optimize for better results continuously.
- 5. Linkedin.com/in/mohamed-helmy Linkedin.com/in/mohamed-helmy Applicable ML Concepts - continued Predictive Analysis ML models excel at predicting outcomes based on historical data. Utilize tools and techniques such as trend analysis, forecasting, and scenario planning to make informed predictions about your marketing strategies. Personalization & Segmentation One significant advantage of ML models is their ability to identify patterns and segments within vast amounts of data. As a marketer, you can adopt this principle by segmenting your audience based on their behavior, preferences, and past interactions. Embracing Change & Uncertainty Machine learning models thrive in changing environments. Similarly, in the world of digital marketing, change is the only constant. As a marketer, you must embrace this change, be it changes in consumer behavior, market trends, or digital platforms.