January 8, 2025

Table of Contents:

1. Scheduled Filters
2. Real-Time Filters
3. Using the Webservice API
4. Using the Import Wizard
5. DupeCatcher
6. Questions to consider for which method(s) is suitable for your organization

Data cleansing and deduplication often seem like a one-time task—dedupe the data, and you're done. But data is dynamic, changing, and growing daily. Changing data comes with the potential to get into a bad state again rapidly. So how do we prevent duplicates? Can we? Is real-time deduplication the answer?

That of course depends on your business needs, processes, and data.

Before you decide, here are some options and considerations…

Scheduled Filters

How it works:

Cloudingos automation jobs allow you to schedule predefined merge filters on specific intervals (e.g., daily, weekly, monthly) using custom-defined matching criteria and rules for selecting the right master record.

When this makes sense:

After completing an initial cleanse and bringing your data set to a baseline clean. Some filters are “no-brainers”, and it makes sense to compound the initial effort by setting up regular intervals for the filters to run automatically. Users are unencumbered in entering and editing new records in Salesforce, while the data itself is reviewed and cleaned on a regular interval.

Considerations:

Duplicates will remain in the org until the next scheduled filter and merge run. Not all filters are great candidates for merging automatically because of the sensitivity of the data or the intended loose nature of the filter.

Learn more here.

Real-Time Filters

How it works:

With up to 3 filters (one per object: leads, contacts, accounts), Cloudingo can have “actively listening” filters that will merge dupes based on the custom logic defined by the user.

When this makes sense:

When speed is needed! Real-time filters remove the delay between intervals of the filter run schedule.

Considerations:

You can only have a single filter per object set up to run in real-time. Education…you will likely need to alert your internal reps that this has been enabled, so that if a record is created and meets the criteria for a real-time merge there is no confusion.

Learn more here.

Using the Webservice API

How it works:

Cloudingos API allows integration with external applications to deduplicate data in real-time or on demand.

When this makes sense:

One or more external applications automatically create records in Salesforce.

Considerations:

This typically requires a development resource for the initial implementation and can be managed by the business user going forward.

Learn more here.

Using the Import Wizard

How it works:

The Cloudingo import wizard allows you to load a list into Salesforce but first check the list against existing Salesforce data for duplicates. When duplicate records are found, the existing Salesforce record can be updated. Unique records on the import file are inserted as new Salesforce records.

When this makes sense:

List imports are a regular occurrence for your team, and you want to prevent the creation of duplicates, update existing records with new information, and push in net new records.

Considerations:

Import jobs can be run as one-off jobs, or if an import process is regular and consistent, Cloudingo Import Templates can be created to ease and speed the process.

Learn more here.

DupeCatcher

How it works:

DupeCatcher looks for duplicates when new records are created manually in Salesforce, or when existing records are updated or converted. It enables users to identify, block and dedupe leads, accounts, contacts, and person accounts in real-time.

When this makes sense:

If youre looking to prevent users from creating duplicates before, this free tool can help. Please note that you cant clean up existing dirty data and as a free tool it has some limitations.

Considerations:

The tradeoff for preventing users from creating new duplicate records is that doing so can slow down the process of your users getting to work with their new data. Rules that are too strict can frustrate users and work against the goal of quality data as users find creative ways to circumvent those rules. Rules that are too loose fail to offer any real assistance to maintaining good data.

Learn more here.

Questions to consider for which method(s) is suitable for your organization:

• How critical is data accuracy in your day-to-day operations?
• What is the end user experience going to be like?
• What is the volume of new/old data?
• Where is the new data coming from?

Ultimately, the right choice depends on balancing your immediate needs with long-term scalability. Cloudingo provides a range of solutions tailored to different stages of data quality —ensuring theres an option that fits your goals and resources.

Want to learn more about what option works best for your set up? Speak with a data quality expert!