Applications of AI Flashcards
___ ____ is an “approach to making
repeated decisions that involves
algorithmically finding patterns in data and using these to make recipes that deal correctly with brand new data”
Machine learning
- Determine price structure
- Calculate and predict customer lifetime value
- Predicting churn
- Market Basket analysis
- Up/cross selling
- Predict advertising campaign performance
- Marketing Mix
- Lead scoring
- Sales forecasting
- Predict if the user will recommend your product or not
Predictive Analytics
- Data Analysis
- Demand Forecasting
- Price Optimization
- Dynamic Pricing
- Personalized Pricing
- Price Sensitivity
Determine Price Structure
– Utilizing advanced algorithms to aggregate customer data and
predict CLV accurately.
– Applying sophisticated techniques to analyze multiple variables
and incorporate predictive models.
Machine Learning for CLV Prediction
ML and AI techniques offer powerful tools for predicting customer churn in digital marketing. Analyzing vast customer data and identifying patterns can help anticipate ___ ___
Predicting Churn
Technique to uncover
product associations frequently purchased together by customers.
Market Basket Analysis
Applied to enhance Market Basket Analysis by mining transactional data to discover item associations, enabling personalized recommendations and predictive analytics
Machine Learning:
a method that helps sales and marketing teams identify which potential customers are most likely to become customers
Lead scoring
Assessing user’s likelihood to recommend your product
Recommendation Prediction
Merges computer science, AI, and linguistics. It transforms unstructured language data into structured formats. It powers chatbots, Alexa, Siri,
etc.
Natural Language Processing (NLP)
Subfield of NLP emphasizing text and speech meaning. Analyzes syntax and semantics.
Natural Language Understanding (NLU)
Enables computers to produce human-like text
Natural Language Generation (NLG)
- Adversarial training: Teaching Neural
Networks to overcome weaknesses. - Two Networks: “Discriminator” and
“Generator”. - Objective: The Discriminator aims for a low error rate, while Generator aims for a high error rate.
GANs
Can uncover threats like old
advertisement potentially
damaging
Visual Listening
- Optimize conversion rates with images
- Visual data for personalization
- Contextual In-Image Ads
- Facial recognition, Tracking User Attention and Emotions
Computer Vision
- This block of code introduces a helper class designed to facilitate the
image classifier. - In Python, a class is a custom data type created by the user,
encompassing both the data and the functions to modify that data.
Helper Class
