Optimization for the Advertising and Marketing Industry - Gurobi Optimization (original) (raw)

Overview

Gurobi solvers can provide a considerable advantage for organizations when deploying advertising and marketing campaigns in today’s highly diverse and competitive world of new media that includes increasing ‘clutter’ and decreasing viewer attention. Optimization gives organizations the power to use their ever-growing amounts of data to make millions of automated decisions in order to maximize return on investments, while both expanding and improving customer relationships by providing the right people with the right messages at the right time.

The Solver That Does More

Gurobi delivers blazing speeds and advanced features—backed by brilliant innovators and expert support.

Unmatched Performance

With our powerful algorithms, you can add complexity to your model to better represent the real world, and still solve your model within the available time.

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Our development team includes the brightest minds in decision-intelligence technology--and they're continually raising the bar in terms of solver speed and functionality.

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Our PhD-level experts are here when you need them—ready to provide comprehensive guidance and technical support. They bring deep expertise in working with commercial models and are there to assist you throughout the process of implementing and using Gurobi.

Peek Under the Hood

Dive deep into sample models, built with our Python API.

Customer Assignment

Sharpen your mathematical optimization modeling skills with this example, in which you will learn how to select the location of facilities based on their proximity to customers. We’ll demonstrate how you can construct a mixed-integer programming (MIP) model of this facility location problem, implement this model in the Gurobi Python API, and generate an optimal solution using the Gurobi Optimizer. This modeling example is at the intermediate level, where we assume that you know Python and are familiar with the Gurobi Python API. In addition, you should have some knowledge about building mathematical optimization models.
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Marketing Campaign Optimization

Companies across almost every industry are looking to optimize their marketing campaigns. In this Jupyter Notebook, we’ll explore a marketing campaign optimization problem that is common in the banking and financial services industry, which involves determining which products to offer to individual customers in order to maximize total expected profit while satisfying various business constraints. You’ll learn how to formulate a mathematical optimization model of the problem (using machine learning predictive response models as parameters) and solve it using the Gurobi Optimizer. This modeling example is at the beginner level, where we assume that you know Python and that you have some knowledge about building mathematical optimization models. The reader should also consult the documentation of the Gurobi Python API.
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Frequently Asked Questions

Mathematical optimization uses the power of math to find the best possible solution to a complex, real-life problem. You input the details of your problem—the goals you want to achieve, the limitations you’re facing, and the variables you control—and the mathematical optimization solver will calculate your optimal set of decisions.

80% of the world’s leading companies use mathematical optimization to make optimal business decisions. For example, Air France uses it to build the most efficient schedule for its entire fleet, in order to save on fuel and operational costs, while reducing delay propagation.

Descriptive and predictive analytics show you what has happened in the past, why it happened, and what’s likely to happen next. But to decide what to do with that information, you need human input—which can introduce bias.
With mathematical optimization, you receive a decision recommendation based on your goals, constraints, and variables alone. You can, of course, involve human input when it comes to whether or not to act on that recommendation. Or you can bypass human input altogether and automate your decision-making.

Additional Insight

Guidance for Your Journey

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