Professional Data Quality, Cleaning & Deduplication for CRM / Excel Datasets
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1. Introduction
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I help businesses clean, standardize, and de-duplicate messy data so they can trust their customer, vendor, and master data.

Whether your dataset has duplicate names, inconsistent formats, or scattered records, I provide a structured and reliable solution using a combination of rule-based logic and smart matching techniques.

No generic tools — every solution is customized to your dataset.

If your data is messy, inconsistent, or full of duplicates — I can make it clean, structured, and ready for business use.

2. Why choose me
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- I don’t just clean your data — I make it reliable for business decisions
- Custom-built matching logic (not generic tools)
- Business-friendly outputs (easy to use, not just technical)
- Transparent match scoring (you always know why records match)
- Flexible approach based on your dataset

3. Services Included
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- Identification of duplicate records (exact, rule based & fuzzy matching)
- Name (Title, Suffix, Company Words etc.) standardization (individual & company names)
- Address cleaning and formatting
- Matching based on:
-- Name similarity (smart matching that identifies similar names even with spelling mistakes or variations)
-- Rule-based & Probabilistic Matching
-- Matching on Phone numbers
-- Matching on Email addresses
-- Matching on other identifiers, based on availability
-- Custom matching logic tailored to your dataset
- Consolidation of duplicate records
- Match Confidence Score (e.g. 85% similarity)

4. Output
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- Clean and standardized dataset
- Duplicate groups identified using Cluster IDs
- Match confidence score for each record
- “Golden Record” (best version of each entity)
- Includes clearly labeled columns so you can easily identify and use the results.
- Executive summary dashboard
- Delivered in a structured Excel file, ready for immediate use.

5. Process
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- Data assessment & profiling
- Standardization (names, addresses, formats)
- Matching (rule-based + fuzzy logic)
- Scoring & clustering
- Survivor selection (golden records)
- Final delivery + summary report

6. Use Cases
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- CRM data cleanup before migration (Salesforce, HubSpot, etc.)
- Removing duplicate customer or vendor records
- Cleaning marketing/email lists
- Master data consolidation across systems
- Matching applicant/customer names with external Compliance Lists for screening
- Preparing clean data for analytics or machine learning

7. Pricing Tiers
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Basic:

Data Structure -> Individual Name (or Company Name) + Address + Phone/Mobile + Email
Record Volume: <1000
Turn-around time: 6-8 working days
Price: USD 100

Standard:

Data Structure -> Individual Name (or Company Name) + Address + Phone/Mobile + Email
Record Volume: <5000
Turn-around time: 12 - 15 working days
Price: USD 300

Premium:

Data Structure -> Individual Name (or Company Name) + Address + Phone/Mobile + Email
Record Volume: <20000
Turn-around time: 18 - 22 working days
Price: USD 800

8. Add-on Services
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- If address components are included in matching, pricing and turnaround time will increase by 50%
- If both individual and company names are included in the scope for cleansing and deduplication then pricing and turnaround time will increase by 50%
- Extra volume of records - Will be mutually decided before the contract

9. FAQ
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Q: Can you handle messy/incomplete data?
Yes, I use fuzzy matching techniques to identify duplicates even with spelling variations.

Q: Will I lose any data?
No. Output will contain original data besides clean data and match information.

Q: What tools do you use?
Excel, R, Python, and custom scripts depending on complexity.

Q: What format should I provide the data in?
Excel (preferred), CSV, or database extract. I can guide you if needed.

Q: How accurate is this?
Typical matching accuracy: 85%–95% depending on data quality.
Manual review is recommended for edge cases to ensure maximum accuracy.

Q. Can I request revisions or additional logic after delivery?

Yes. Standard and Premium tiers include one revision cycle to refine matching logic based on your feedback.

10. Data Privacy
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- Your data is handled with strict confidentiality
- No data is shared or reused

* Feel free to message me before placing an order to discuss your dataset and requirements. *