import streamlit as st

# st.set_page_config(
#     layout="wide"
# )

def glossary_run():
    st.header("Glossary")
    with st.expander("Model MMM Terminology"):
        st.subheader("Glossary of MMM Terminology")
        st.write("**• Model R-squared \(R\)\:** This is a statistical measure used to determine the percentage of variation in the dependent variable that the independent variables explain collectively. It ranges between 0 and 1, where 1 indicates a perfect fit and 0 indicates no linear relationship. An R2 greater than 0.8 usually indicates a great model fit.")

        st.write("**• Mean Absolute Percentage Error \(MAPE\):** This is a measure used to determine the accuracy of a predictive model. It calculates the average absolute percentage difference between the actual and predicted values, expressing the result as a percentage to provide a sense of scale for the error.")

        st.write("**• Media & Baseline Elasticity:** It refers to the percentage change in the number of prospects in response to a percentage change in a marketing input \(media channel spends\) or a baseline factor \(like seasonality. macro factors, competitors spending, etc.\). It is a measure of the responsiveness of the number of prospects to changes in the marketing input or the baseline factor")

        st.write("**• Media Half-Life:** This represents the time it takes for a media spend's impact to reduce to half of its initial impact. It is a key aspect of media decay rates, which represent how the effect of advertising diminishes over time \(in weeks\). This term refers to a curve that illustrates the relationship between media spend and the resulting number of prospects.")

        st.write("**• Support:** Equivalent to Impression or Click depending on the media channel.")

        st.write("**• Contribution Share:** Unit is %. It refers to the percentage contribution of a specific marketing channel to the number of prospects. It is calculated by dividing the contribution from a particular channel by the total number of prospects from all media channels \(not including base contributions\).")

        st.write("**• Spend Share:** Unit is %. It refers to the percentage of the total marketing budget that is allocated to a specific marketing channel. It is calculated by dividing the amount spent on a particular channel by the total marketing spend")

        st.write("**• Support Share:** Unit is %. It refers to the percentage of the total media impression that is allocated to a specific marketing channel. It is calculated by dividing support on a particular channel by the total marketing spend")

        st.write("**• Efficiency Index:** it is a metric that measures the cost-effectiveness of a campaign. It is calculated by dividing Contribution Share by Spend Share. An efficiency index above 1 suggests that a channel is more cost-effective than the benchmark, while an efficiency index below 1 suggests it is less cost-effective. The higher the efficiency index, the more cost-effective its channel is")

        st.write("**• Effectiveness Index:** It is a metric that measures how well a particular marketing channel is performing relative to its support/impression. It is calculated by dividing the Contribution Share by the Spend Share for each channel")

        st.write("**• Estimated CPM \(Cost Per Thousand Impressions\):** This is an estimation of the cost for every thousand impressions \(or views\) of its advertisement via that media channel. The default values are generated from historical averages.")

        st.write("**• Estimated CPC \(Cost Per Click\):** This is an estimation of the cost for each time someone clicks on its advertisement via that media channel. The default values are generated from historical averages.")
    with st.expander("Deployment Plan"):
        st.image(r"image (2).png")
glossary_run()