AI-Based Customer Service Analytics in Excel

For medium-sized service providers, AI-powered customer service analytics in Excel can help track feedback, response times, and resolution rates. By automating these processes, businesses can identify pain points, improve service quality, and enhance customer satisfaction.

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Step 1: Setting Up a Customer Service Dashboard in Excel

Create an Excel sheet with the following columns:

Ticket ID

Customer Name

Issue Category

Submitted Date

Resolved Date

Response Time (hrs)

Resolution Time (hrs)

Sentiment Score

Status

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Step 2: Automating Response and Resolution Time Calculation

1. Calculate Response Time

Use this formula to calculate response time (in hours):

=IF(E2<>"", (E2-D2)*24, "")

• D2 (Submitted Date) & E2 (Resolved Date)
• Multiplied by 24 to convert days to hours.

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2. Calculate Resolution Time

If a ticket is resolved, use this formula to track resolution time:

=IF(E2<>"", (E2-D2)*24, "Pending")

• If resolved, it returns the time in hours.
• If unresolved, it shows “Pending”.

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Step 3: Sentiment Analysis on Customer Feedback

To analyze sentiment from customer reviews, assign a score (0 to 1) based on feedback:

Feedback

Sentiment Score

“Great service, very responsive!”

0.9

“Took too long to fix my issue.”

0.4

“Worst experience, no one responded!”

0.1

Use VLOOKUP or an AI-powered API to classify sentiment.

If using a basic rule-based model, apply this formula:

=IF(ISNUMBER(SEARCH("great", A2)), 0.9, IF(ISNUMBER(SEARCH("worst", A2)), 0.1, 0.5))

For advanced sentiment analysis, use a Python script with NLTK or TextBlob:

from textblob import TextBlob
import pandas as pd

# Load Excel file
df = pd.read_excel("customer_feedback.xlsx")

# Apply sentiment analysis
df["Sentiment Score"] = df["Feedback"].apply(lambda x: TextBlob(str(x)).sentiment.polarity)

# Save back to Excel
df.to_excel("customer_feedback_updated.xlsx", index=False)

This script:
✅ Reads customer feedback from an Excel file.
✅ Analyzes sentiment (positive, neutral, negative).
✅ Saves the updated file with sentiment scores.

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Step 4: Generating AI-Based Customer Service Reports

1. Average Response & Resolution Time

Use AVERAGEIF to calculate key metrics:

=AVERAGEIF(G:G, ">0")

• Calculates average resolution time for closed tickets.

=AVERAGEIF(F:F, ">0")

• Calculates average response time.

2. Number of Open Tickets

Use this formula to count unresolved issues:

=COUNTIF(I:I, "Open")

3. Customer Satisfaction Score (CSAT)

To calculate the CSAT Score (% of positive reviews):

=COUNTIF(H:H, ">0.7")/COUNT(H:H)

• H:H (Sentiment Score)
• 0.7+ considered positive feedback.

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Step 5: Automating Reports with VBA

To generate weekly reports, use this VBA script:

Sub GenerateCustomerServiceReport()
    Dim ws As Worksheet
    Dim lastRow As Integer
    Dim responseAvg As Double
    Dim resolutionAvg As Double
    Dim openTickets As Integer
    Dim csatScore As Double

    Set ws = ThisWorkbook.Sheets("CustomerService")
    lastRow = ws.Cells(Rows.Count, 1).End(xlUp).Row

    ' Calculate Averages
    responseAvg = Application.WorksheetFunction.AverageIf(ws.Range("F2:F" & lastRow), ">0")
    resolutionAvg = Application.WorksheetFunction.AverageIf(ws.Range("G2:G" & lastRow), ">0")
    openTickets = Application.WorksheetFunction.CountIf(ws.Range("I2:I" & lastRow), "Open")
    csatScore = Application.WorksheetFunction.CountIf(ws.Range("H2:H" & lastRow), ">0.7") / lastRow

    ' Display Results
    MsgBox "Customer Service Report" & vbCrLf & _
           "------------------------------" & vbCrLf & _
           "Average Response Time: " & Round(responseAvg, 2) & " hours" & vbCrLf & _
           "Average Resolution Time: " & Round(resolutionAvg, 2) & " hours" & vbCrLf & _
           "Open Tickets: " & openTickets & vbCrLf & _
           "Customer Satisfaction Score: " & Round(csatScore * 100, 2) & "%", vbInformation, "Report"
End Sub

How It Works

✅ Calculates key metrics (response time, resolution time, CSAT).
✅ Summarizes results in a popup report.
✅ Can be scheduled to run weekly for automated insights.

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Step 6: Visualizing Customer Service Data

To create dynamic reports, use:
✔ Pivot Tables → Summarize response/resolution times per category.
✔ Conditional Formatting → Highlight overdue tickets in red.
✔ Charts → Visualize trends in ticket resolution over time.

Example: Customer Service Dashboard Layout

Metric

Value

Avg. Response Time

4.5 hrs

Avg. Resolution Time

24 hrs

Open Tickets

15

CSAT Score

85%

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Step 7: Automating Escalation for Unresolved Tickets

Use Conditional Formatting to flag tickets unresolved for 48+ hours:

=AND(I2="Open", G2>48)

• Applies a red highlight for tickets exceeding 48 hours.

For automated escalation via email, modify this VBA script:

Sub EscalateUnresolvedTickets()
    Dim ws As Worksheet
    Dim lastRow As Integer
    Dim i As Integer
    Dim clientEmail As String
    Dim ticketID As String
    Dim issue As String

    Set ws = ThisWorkbook.Sheets("CustomerService")
    lastRow = ws.Cells(Rows.Count, 1).End(xlUp).Row

    For i = 2 To lastRow
        If ws.Cells(i, 9).Value = "Open" And ws.Cells(i, 7).Value > 48 Then
            clientEmail = ws.Cells(i, 10).Value ' Assuming email is in column J
            ticketID = ws.Cells(i, 1).Value
            issue = ws.Cells(i, 3).Value

            MsgBox "Escalation Alert! Ticket " & ticketID & " (" & issue & ") has exceeded 48 hours.", vbCritical, "Unresolved Ticket"
        End If
    Next i
End Sub

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Key Benefits of AI-Based Customer Service Analytics in Excel

✅ Automates customer service reporting
✅ Improves response and resolution time tracking
✅ Uses AI for sentiment analysis on feedback
✅ Escalates overdue issues automatically

By integrating AI, Excel formulas, and VBA, businesses can improve service quality, retain customers, and enhance operational efficiency.