AI for business: the case study of Thompson sampling to maximize revenue

Artificial intelligence (AI) and machine learning (ML) are revolutionizing the way businesses operate. These technologies have the potential to optimize revenue and improve decision-making across various industries. In this blog post, we will discuss how machine learning can be used to optimize revenue for an e-commerce business through a case study of Thompson Sampling.

First, let's define what Thompson sampling is. Thompson sampling is a machine learning algorithm used to solve problems with uncertain outcomes. It is a probabilistic method that samples from the posterior distribution of a model's parameters rather than using point estimates. This allows the algorithm to take model uncertainty into account, making it more robust and effective in solving problems with uncertain outcomes. In simpler terms, it is a way of making decisions based on the probability of the outcome, considering all possible outcomes and their probabilities.

In our case study, we will use the Thompson sampling algorithm to optimize revenue for an e-commerce business. The company has nine strategies, each with three different settings. The goal is to find the best combination of parameters for each strategy to maximize revenue. To test the algorithm, we will simulate 10,000 users on the website and depending on the conversion rate of each strategy, we will find the best strategy to maximize revenue.

To begin, we import the necessary libraries and set the parameters for the algorithm. We set the number of rounds to 10,000, the number of strategies to 9, and the product price to $50. Next, we create a simulation environment by generating conversion rates for each strategy and simulating the actions of 10,000 users on the website.

Then, we implement the Thompson sampling algorithm with a random strategy as a reference to compare the results. We define the necessary variables and create the random strategy and Thompson sampling algorithm. For each round, the random strategy selects a strategy at random and records the reward. The Thompson sampling algorithm selects a strategy based on the probability of the outcome and records the reward.

After all rounds, we compare the total rewards obtained by the two strategies and calculate the difference in rewards as the "regret" of not using the better strategy. We then record the regret of the two strategies in different variables. This allows the business owner to see which strategy has yielded the best results over time.

To better understand these concepts, let's take the example of an online clothing and accessories sales company that wants to improve its promotion strategies to maximize their revenue. Promotion strategies include promoting seasonal clothing, new arrivals and sale items. Each of these strategies uses different parameters such as product type, price and target audience. To optimize these strategies, the company uses the Thompson sampling algorithm to simulate the actions of 10,000 users on the website and find the best combination of parameters for each strategy.

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After running the algorithm, the results show that strategy 5, the strategy of promoting new products with a sale price and targeting a specific audience has the highest conversion rate. The company is implementing this strategy and estimates that it could result in an 86% increase in revenue. Although this is a fictional example, it does demonstrate how using the Thompson Sampling Algorithm can help businesses make more informed and certain decisions about promotion strategies, which can result in a significant increase in income. It is important to note that this can vary depending on the complexity of the business and the data available. Using the sampling algorithm.

As specialists in innovation, marketing, data analytics and machine learning, we're here to help businesses like you get the most out of these revolutionary technologies. We can help your business use machine learning to optimize your revenue, as we showed in the example above. We can help your business understand your data and use these insights to improve your business decisions. We can also help set up effective marketing campaigns using the latest AI technologies. Contact us to discuss how we can help your business thrive in an increasingly digital world.