Automating Repetitive Excel Tasks with VBA Macros

Sub CalculateCLV()
    Dim ws As Worksheet
    Dim row As Integer
    Dim sales As Double
    Dim customerLTV As Double
    Dim retentionRate As Double
    Dim discountRate As Double
    Dim customerCLV As Double

    Set ws = ThisWorkbook.Sheets("CustomerData")
    row = 2 ' Assuming headers are in row 1

    Do While ws.Cells(row, 1).Value <> ""
        sales = ws.Cells(row, 2).Value
        retentionRate = ws.Cells(row, 3).Value
        discountRate = ws.Cells(row, 4).Value

        customerCLV = sales * (retentionRate / (1 + discountRate - retentionRate))
        ws.Cells(row, 5).Value = customerCLV

        row = row + 1
    Loop
End Sub
    

Integrating Azure ML API for CLV Prediction

import requests

api_url = "https:///predict"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer "
}
data = {
    "data": [
        {"customer_id": "123", "transaction_history": [100, 200, 300]}
    ]
}

response = requests.post(api_url, headers=headers, json=data)
clv_prediction = response.json()
            

What This Code Does:

This script sends customer transaction data to an Azure ML endpoint to receive CLV predictions

Business Impact:

Enables precise targeting of high-value customers, optimizing marketing spend

Implementation Steps:

Set up Azure ML, deploy a model, and connect it via an API call in Excel

Dynamic Segmentation with Power Query

let
    Source = Excel.CurrentWorkbook(){[Name="CustomerData"]}[Content],
    FilteredRows = Table.SelectRows(Source, each [PurchaseAmount] > 100),
    GroupedData = Table.Group(FilteredRows, {"CustomerID"}, {{"TotalSpent", each List.Sum([PurchaseAmount]), type number}})
in
    GroupedData
            

What This Code Does:

This Power Query script filters and aggregates customer data to identify high-value segments

Business Impact:

Facilitates targeted marketing strategies, enhancing customer retention and growth

Implementation Steps:

Load customer data into Excel, use Power Query to filter and group

Predicting CLV Using Python and Excel

import pandas as pd
from statsmodels.tsa.arima_model import ARIMA

# Load historical sales data
data = pd.read_excel('sales_data.xlsx')
# Fit the ARIMA model
model = ARIMA(data['Sales'], order=(5,1,0))
model_fit = model.fit(disp=0)

# Forecast future sales
forecast, stderr, conf_int = model_fit.forecast(steps=12)

print(forecast)
    

Automating CLV Calculation with VBA

Sub CalculateCLV()
    Dim ws As Worksheet
    Set ws = ThisWorkbook.Sheets("CLVData")
    Dim LastRow As Long
    LastRow = ws.Cells(ws.Rows.Count, 1).End(xlUp).Row

    Dim i As Long
    For i = 2 To LastRow
        ws.Cells(i, 4).Value = ws.Cells(i, 2).Value * ws.Cells(i, 3).Value
    Next i
End Sub
    

Automating Repetitive Excel Tasks with VBA Macros

Sub UpdateCLVData()
    Dim ws As Worksheet
    Set ws = ThisWorkbook.Sheets("CLV_Data")
    Dim lastRow As Long
    lastRow = ws.Cells(ws.Rows.Count, "A").End(xlUp).Row

    For i = 2 To lastRow
        ws.Cells(i, 4).Value = ws.Cells(i, 2).Value * ws.Cells(i, 3).Value ' Example formula for CLV
    Next i
End Sub
        

What This Code Does:

This VBA macro automates the calculation of CLV by iterating over each row, multiplying transaction count by average transaction value.

Business Impact:

Saves time by automating repetitive calculations, reducing manual errors and ensuring up-to-date analytics.

Implementation Steps:

1. Open Excel and press Alt + F11 to access the VBA editor. 2. Create a new module and paste the above code. 3. Run the macro to update CLV data.

Automating CLV Calculations using VBA Macros

Sub CalculateCLV()
    Dim ws As Worksheet
    Set ws = ThisWorkbook.Sheets("Data")

    Dim lastRow As Long
    lastRow = ws.Cells(ws.Rows.Count, "A").End(xlUp).Row

    Dim i As Long
    For i = 2 To lastRow
        ws.Cells(i, "D").Value = ws.Cells(i, "B").Value * ws.Cells(i, "C").Value  ' Lifetime Value = Avg Purchase * Frequency
    Next i
End Sub