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Use Algorithms

We use high-end AI algorithms to improve marketing lead scores, predict customer turnover, analyze dynamic pricing models, perform sentiment analysis, improve website experience, personalize the customer experience with targeted ads, and more.

Statistical Models

Use AI and deep learning to build statistical models based on relationships between variables to predict consumer behavior, geo-targeting, content creation, identify interests, and more.

Computer Systems

High-performance processing power to generate AI-based solutions and build a robust marketing strategy.

Mathematical Model

Process complex mathematical models to predict consumer behavior, business sales, etc. based on model interpretation, model validation, numerical abstraction, etc.

Computational Statistics

At Lead Million, we use computational statistics based on machine learning models that build engagement strategies based on tons of data received from data mining.

Mathematical Optimization

We use Mathematical Optimization based on self-learning algorithms to get a larger target audience, generate sales, and garner better ROI.

Data Mining

Perpetual data mining through machine learning algorithms creates a large consumer database, behavioral patterns, etc.

Predictive Analytics

Predicitve analysis algorithms through machine learning help digital marketing experts track risks, customer behavior, data mining, leverage qualified leads, personalized messaging, and more. Classification and regression models respond to data that delivers results based on valuable relationships to make informed decisions.

Frequently asked questions

Get answers to what Machine Learning is all about, and how it can help in Digital Marketing.

What is Machine Learning?

Machine learning is the application of AI that provides modern systems to learn and improve from perpetual experience without any coding or programming. It focuses on the development of programs that can access and use data to learn for themselves.

How Machine Learning Works?

Machine learning uses two types of techniques supervised and unsupervised learning that analyzes data and finds patterns or structures in input. This navigates to clustering, classification, and regression.

Why Machine Learning is Important?

Machine Learning is important in areas of marketing wherein it has the potential to enhance customer experience, create revenue streams, develop products and services, engage customers with chatbots, reducing marketing waste, improve personalization, and more.

Why Machine Learning is required in Digital Marketing?

Machine Learning is important in areas of marketing wherein it has the potential to enhance customer experience, create revenue streams, develop products and services, engage customers with chatbots, reducing marketing waste, improve personalization, and more.

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