Add introduction

app.py

@@ -27,8 +27,27 @@ st.set_page_config(
 st.title("💸 Dynamic Pricing 💸")
 st.subheader("Setting optimal prices with Bayesian stats 📈")
 
-# (1) Intro
-st.header("Let's start with the basics 🏁")
+# (0) Intro
+st.header("Why care about dynamic pricing? 💭")
+
+st.markdown("""Dynamic pricing aims to actively adapt product prices based on insights about 
+customer behaviour.  \n
+This pricing strategy has proven exceptionally effective in a wide range of industries: from 
+e-commerce (e.g., eBay) to airlines (e.g., Delta Airlines) and from retail (e.g., Walmart) to 
+utilities (e.g., Tampa Electric) as it allows to **adjust prices to changes in demand patterns**.""")
+st.markdown("""It is hardly surprising that recent times of extraordinary uncertainty and volatility
+caused a surge in adoption of dynamic pricing strategies with an [estimated 21% of e-commerce 
+businesses reportedly already using dynamic pricing](https://www.statista.com/statistics/1174557/dynamic-pricing-ecommerce-companies-worldwide/) 
+and an additional 15% planning to adopt thestrategy in the upcoming year.""")
+st.markdown("""To find a big success story, we should look no further than Amazon who (on average)
+change their products' prices once every 10 minutes. They attribute roughly [25% of their e-commerce
+profits](https://dzone.com/articles/big-data-analytics-delivering-business-value-at-am)
+to their pricing strategy.""")
+st.markdown("""In what follows we'll discuss the working principles & challenges in the field of
+dynamic pricing, followed by an interactive demo and some final considerations.""")
+
+# (1) Basics
+st.header("Back to basics 🏁")
 
 st.markdown("The beginning is usually a good place to start so we'll kick things off there.")
 st.markdown("""The one crucial piece information we need in order to find the optimal price is