CRM DATA ENTRY & DATA CLEANING
📌 1. What is Data Entry in CRM?
Data Entry means adding and updating customer information inside the CRM accurately and consistently.
Correct data entry ensures:
✔ No missing information
✔ Correct follow-up
✔ Proper communication
✔ Better lead qualification
✔ Accurate reports
Incorrect data = lost customers.
📌 2. Why Data Entry Is Important for Udyamkart
Udyamkart deals with many clients from:
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Schools
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Colleges
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Businesses
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Startups
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Individuals
To serve them properly, CRM must have:
✔ Correct details
✔ Updated records
✔ Accurate pipeline
✔ Clean status
This avoids:
❌ Wrong calls
❌ Duplicate leads
❌ Missed follow-ups
❌ Bad customer experience
📌 3. What Data Must Be Entered in CRM?
Interns must fill these key fields:
A. Basic Details
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Full Name
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Phone Number
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Email Address
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Company/School Name
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Location
B. Lead Information
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Lead Source (Website, WhatsApp, Call, Ads)
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Lead Type (ERP, Website, Software)
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Requirement Description
C. Communication History
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Call notes
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WhatsApp updates
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Email shared
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Meeting summary
D. Follow-Up Details
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Follow-up date
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Follow-up time
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Follow-up purpose
E. Status Updates
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Lead stage
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Priority
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Ownership
📌 4. Rules for Correct Data Entry (Very Important)
✔ Always type full names
Not “RK” → Write “Ritesh Kumar”
✔ Use proper formatting
Phone: 10 digits
Email: professional format
Address: proper spelling
✔ Fill every field
No blanks unless necessary.
✔ Add clear notes
Example:
“Client needs school ERP, demo tomorrow at 4 PM.”
✔ Update immediately after communication
Do NOT wait till evening.
✔ Maintain consistency
Use uniform spelling, format, and words.
📌 5. What is Data Cleaning?
Data Cleaning means:
✔ Removing duplicate leads
✔ Fixing incorrect phone numbers
✔ Updating old leads
✔ Correcting spelling
✔ Completing missing fields
✔ Closing dead/invalid leads
Clean CRM = professional work.
📌 6. Types of Data Cleaning in CRM
A. Duplicate Lead Removal
When same person added twice:
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Merge leads
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Delete duplicate
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Keep clean record
B. Correcting Wrong Entries
Fix:
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Wrong phone number
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Misspelling
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Wrong lead status
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False priority
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Wrong email ID
C. Completing Missing Fields
Examples:
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Lead without name
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Lead without source
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No follow-up date
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No notes
Incomplete data reduces conversion.
D. Updating Lead Status
Change:
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Contacted → Qualified
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Demo Done → Proposal Sent
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Proposal Sent → Negotiation
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Lost Lead if no response
Never keep old status forever.
E. Cleaning Old Leads
Old leads inactivity = confusion.
You must:
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Recheck old leads
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Mark them converted/lost
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Update their comments
📌 7. Data Validation Techniques for Interns
Interns must verify:
✔ Phone number correct?
✔ Email format valid?
✔ Name spelled correctly?
✔ Lead status matches communication?
✔ Follow-up time is set?
✔ Notes added?
✔ Lead source identified?
📌 8. Why Data Cleaning Helps Udyamkart?
✔ Accurate reporting
Managers get correct numbers.
✔ Faster lead conversion
No confusion in communication.
✔ Better customer service
Right details → professional support.
✔ Efficient follow-up
No missing reminders.
✔ Better marketing decisions
Correct data shows which sources work best.
📌 9. Daily Data Entry Responsibilities of Interns
🔹 Enter new leads immediately
🔹 Update all communication in notes
🔹 Correct or complete missing fields
🔹 Check duplicates
🔹 Update pipeline regularly
🔹 Add follow-up details
🔹 Keep database clean daily
This must be done before logging out each day.
📌 10. Common Data Entry Mistakes Interns Must Avoid
❌ Leaving empty fields
❌ Wrong phone number
❌ Not updating lead status
❌ No follow-up date
❌ Wrong spelling of customer name
❌ Adding duplicate entries
❌ Not writing communication notes
❌ Using incomplete descriptions like “call done”
Always be specific:
“Call done, client wants demo tomorrow at 3 PM for ERP.”
📌 11. What Interns Must Learn in Module 7
By the end of Module 7, interns should be able to:
✔ Enter customer details correctly
✔ Maintain consistent data formatting
✔ Remove duplicates
✔ Validate information
✔ Update communication logs
✔ Clean old data
✔ Keep CRM database accurate
🎓 Module 7 – Practical Assignments
Task 1:
Clean 20 old leads (fix names, numbers, status).
Task 2:
Identify and remove 5 duplicate leads.
Task 3:
Fill missing fields for 10 leads.
Task 4:
Update the communication notes for 5 leads.
Task 5:
Write a 1-page document on why data cleaning is important.



