Intellimize's AI Guide for CMOs, but it's not just CMOs, it's marketers' guide
Intellimize itself is a place that does advertising optimization and website optimization, so it has a bit of a salesy vibe.
If the leader says , "I heard artificial intelligence is good, so tell me about it ," this is a good resource to show them.
AI for CMOs 2023.pdf545KB
Summation
AI is expected to be a powerful tool to improve business performance in marketing
There are many ways to leverage AI: to gain more insights from your marketing data, to reduce the time spent on repetitive data-driven tasks, to shorten your sales cycle, or to drive greater value from your marketing technology.
Data analytics to improve customer experience
Provide answers to customer questions and collect feedback
Providing relevant resources, content and products to our customers
Handling customer questions and comments
Provide personalized messages and suggestions
Customer Churn Prediction
Unify customer data for rich behavioral profiles
Predict advertising performance and manage campaigns efficiently
A 10-Step Framework for Scaling AI in Marketing
1.
Setting business goals
2.
AI applicability assessment
3.
Data Preparation and Integration
4.
AI Model Selection
5.
AI model training
6.
AI Model Testing
7.
Deploying AI Models
8.
Performance Measurement and Evaluation
9.
AI model optimization
10.
AI warrior expansion
Implementing AI can be challenging due to technical expertise, resource constraints, data quality issues, and data security concerns, so working with AI experts can help overcome these challenges.
Many marketers are already leveraging AI in a variety of ways.
Use AI to analyze marketing data, optimize advertising campaigns, improve customer experiences, deliver personalized messages, predict customer churn, and perform effective marketing operations.
However, the vast majority of marketers are afraid and worried about the era of AI. They are worried about the lack of technical know-how and human resources required to implement and maintain AI, data quality issues, and data security issues.
Above all, it is difficult to convert the results obtained using AI into actual business performance → The AI industry is also in a situation where the cost-benefit ratio is not balanced
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