Customer Relationship Management (CRM) - Sales Forecasting Tool

 

Notes:

• Problem Solved: Predicts future sales based on pipeline data and historical trends.

• Customization Benefits: Incorporate external data like seasonality or macroeconomic factors.

• Further Adoption: Display results in BI dashboards or CRM widgets.

Python Code:

import pandas as pd

from sklearn.linear_model import LinearRegression

from sklearn.model_selection import train_test_split

df = pd.read_csv("sales_pipeline.csv")  # Columns: 'month', 'opportunities', 'closed_deals'

X = df[['opportunities']]

y = df['closed_deals']

model = LinearRegression()

model.fit(X, y)

# Forecast next month's sales

next_opps = pd.DataFrame({'opportunities': [150]})

forecast = model.predict(next_opps)

print(f"Predicted sales for next month: {forecast[0]:.2f}")