Filter Best Practices

Introduction

Here is a best practices guide to help get you started with filter configuration inside Cloudingo.

Data is the backbone of any successful organization, but poor data quality, especially duplicates, can slow down operations and lead to missed opportunities. That’s where Cloudingo comes in. Configuring filters is one of the most important steps in deduplicating your data. With the right setup, you can automate data cleanup, reduce errors, and ensure your systems run efficiently.

Getting Started: The Basics of Deduping

The goal of deduping is simple: identify duplicate records by matching field values. With Cloudingo, you can configure filters to match any combination of fields and customize the degree of match with algorithms tailored to your needs.

Here is how to approach deduping strategically:

1. Start Small and Precise: Begin with tight filters using exact matches to catch obvious duplicates. These filters are reliable and can often be automated.

2. Gradually Loosen Filters: Once the obvious duplicates are handled, adjust matching algorithms to identify less obvious duplicates.

3. Automate, but Review: Automate what you trust, but always review the results as you loosen filters to ensure accuracy.

Core Fields for Duplicate Matching

When setting up filters, focus on fields that provide the most reliable matches.

Here are the key fields by object type:

Leads & Contacts

• Email

• Last Name

• First Name

• Phone

• Company/Account Name

Accounts

• Account Name

• Phone

• Address (billing or shipping)

• Website

Recommended Initial Filter Configurations

Here are configurations to start with for exact matching:

Leads & Contacts (Merge)

Email + Last Name + First Name

Email + Company/Account Name

Last Name + First Name + Company/Account Name (this may require manual review vs. automation)

Last Name + First Name + Phone

Email + Last Name

Accounts (Merge)

Account Name + Address (Street or City and State)

Account Name + Phone

Account Name + Website (or just Website if Account Names are not reliably similar)

Lead to Contact (Convert)

Email + Last Name + First Name

Email + Last Name

Email + Company/Account Name

Last Name + First Name + Company/Account (this may require manual review vs. automation)

Lead to Account (Convert)

Company/Account Name

Email/Website (Domain match)

Adjusting Matching Algorithms

After running initial exact matches, fine-tune your filters with these algorithms to uncover less obvious duplicates:

• Email: Keep set to Exact for consistent and reliable results.

• Last Name: Use First N Characters to match partial names. Test to ensure accuracy. Or use Letters Only to find names that may be a match with slight differences in spacing or apostrophes (ie: O’Brien vs OBrien).

• First Name: Add Synonym matching for variations (ie: Stephen vs Steve).

• Phone: Use Numeric Only to account for formatting differences. Or use one of the phone algorithms.

• Account Name: Use Company Clean to find variations (ie: Acme Inc. vs. Acme Co.).

• Website: Use the Domain algorithm to focus on the core URL.

• Street Address: Use Fuzzy (specialized for address variations- ie: 1st vs. First).

• State/Country: Use Synonym matching for abbreviations (ie: TX vs. Texas and US vs United States).

Best Practices for Filter Creation

1. Experiment Without Risk: Filters only generate reports until a merge request is submitted. Feel free to test different configurations.

2. Adapt to Your Data Model: Consider your unique data and operational needs. Use scope settings to isolate subsets (ie: Record types).

3. Review Before Merging: Always test filters and review results in the Cloudingo UI before running mass cleanup jobs.

4. Iterate and Improve: Use feedback from initial runs to adjust and refine your filters over time.

Quick Reference Checklist

1. Start with exact matches for key fields.

2. Gradually loosen filters using the recommended algorithms.

3. Focus on key fields by object type (ie: Email for Leads/Contacts).

4. Review filter results before merging data.

5. Always adapt configurations to suit your specific data and goals.

For more information, check out more on our help website.

www.cloudingo.com | contact@cloudingo.com