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| """Streamlit entrypoint""" | |
| import time | |
| import numpy as np | |
| import streamlit as st | |
| from helpers.thompson_sampling import ThompsonSampler | |
| np.random.seed(42) | |
| st.set_page_config( | |
| page_title="Dynamic Pricing", | |
| page_icon="💸", | |
| layout="centered", | |
| initial_sidebar_state="auto", | |
| menu_items={ | |
| 'Get help': None, | |
| 'Report a bug': None, | |
| 'About': "https://www.ml6.eu/", | |
| } | |
| ) | |
| st.title("Dynamic Pricing") | |
| st.subheader("Setting optimal prices with Bayesian stats 📈") | |
| st.markdown("""In this demo you will see \n | |
| 👉 How Bayesian demand function estimates are created based on sales data \n | |
| 👉 How Thompson sampling will generate concrete price points from these Bayesian estimates \n | |
| 👉 The impact of price elasticity on Bayesian demand estimation""") | |
| st.markdown("""You will notice: \n | |
| 👉 As you increase price elasticity, the demand becomes more sensitive to price changes and thus the | |
| profit-optimizing price becomes lower (& vice versa). \n | |
| 👉 As you decrease price elasticity, our demand observations at €7.5, €10 and €11 become | |
| increasingly larger and increasingly more variable (as their variance is a constant fraction of the | |
| absolute value). This causes our demand posterior to become increasingly wider and thus Thompson | |
| sampling will lead to more exploration. | |
| """) | |
| st.markdown("""If you are looking for more insights into how dynamic pricing is done in practice, | |
| check out our blog post here: https://medium.com/ml6team/dynamic-pricing-in-practice-99fe2216a93d""") | |
| thompson_sampler = ThompsonSampler() | |
| demo_button = st.checkbox( | |
| label='Ready for the Demo? 🕹️', | |
| help="Starts interactive Thompson sampling demo" | |
| ) | |
| elasticity = st.slider( | |
| "Adjust latent elasticity", | |
| key="latent_elasticity", | |
| min_value=0.05, | |
| max_value=0.95, | |
| value=0.25, | |
| step=0.05, | |
| ) | |
| while demo_button: | |
| thompson_sampler.run() | |
| time.sleep(1) | |