Scenarios

Last published at: March 18th, 2025
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Plauti Deduplicate uses scenarios to identify duplicate records in Salesforce. In a scenario you decide which fields and which logic Plauti Deduplicate should use when comparing records to see if they are duplicates. Furthermore, you can define from which level of similarity two records should be considered duplicate.  

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You can create up to 5 scenarios per object with the Advanced license, and 10 scenarios per object with Premium or PDM.

Usually different scenarios are created for different duplicate search processes, but it is possible to use multiple scenarios for the same process.

Do note however, that in the case of scenarios "more" is not always "better". A larger number of scenarios will result in a larger Search Index‍, which can lead to lower quality search results. A smaller number of well-thought-through scenarios will lead to better performance and better search results.

Edit name

Edit a scenario name by clicking the pencil icon next to the name. The icon will become visible when you move your mouse over the scenario name.

Threshold

In the process of comparing records, Duplicate Check calculates a matching percentage: the matching score. That percentage is calculated by comparing the values of the fields that are defined in your scenario. The Threshold level decides from what percentage a match is defined as a potential duplicate record. The default setting is 75%: every score equal to or higher than 75% will be defined as a potential duplicate record. This means that a match between two (or more) records can deviate with a maximum of 25% in its values.

If you set the Threshold level at 100%, the scenario will only return results that have an exact match on all of the fields defined in it.

Fields

Your scenario is a strategy on how to compare records and find duplicates. The fields defined in the scenario are the fields used to compare records. The Lead Default scenario (standard configuration) uses the First Name, Last Name, Company Name, and Phone field. You can remove fields from your scenario by clicking the 'Delete' icon at the end of the table. Adding a new field is easy. Just click the 'Add new field' button.

Synonym Matching

At Synonym Matching, select a list of synonyms for the possible values of this field. Synonyms in this context are words that are different from each other, but that should be considered duplicates of each other. Applying a synonyms list will improve the accuracy of a duplicate score. Find out more about synonym matching in this article‍.

Frequent Words

At Frequent Words, select a list of frequent words for the possible values of this field. Frequent Words are common words that will not be taken into account when checking for duplicate values for this field. Applying a frequent words list will improve the accuracy of a duplicate score. Find out more about frequent words in this article‍.

Matching method

Matching Methods are algorithms used by Plauti Deduplicate to analyze field values of standard and custom fields. Based on this analysis it decides to what extent two records match: the matching score. 

Fields can have different value types (e.g. numeric or text, but also plain text or email addresses, etc.) In order to catch duplicate records it is important to apply a matching method that can properly analyze each value type.
With a matching method you also decide to apply an exact or fuzzy logic to evaluate field values. 

Select a matching method for each scenario field, based on the field type.
Find out more about matching methods in this article.

Empty fields

In most databases, not all fields of every record are populated. The 'Empty Fields' setting lets you configure how to handle empty fields in the comparison process. You can choose between three options. 

1. Disregard

"Disregard" will not take empty fields into account when calculating a matching percentage. It can still trigger a 100% score if there are one or more fields without value. Using this setting, we allow you to find duplicate records that are not filled out entirely. "Disregard" can, however, also trigger false positives. If so, please check out the other setting options. These example scores are calculated with an equal weighting for all fields.

First Name Last Name Company name Email Address Phone number     Score
Jennifer Blake Laoreet Corporation j.blake@loareet.com 1-817-297-7931     100% 
Jennifer Blake Laoreet Corporation Empty 1-817-297-7931

Or

First Name Last Name     Company Name Email Address Phone Number Score
Jennifer Blake Laoreet Corporation j.blake@laoreet.com 1-817-297-7931 100%
Jennifer Empty Empty Empty Empty

2. Score 50%

Instead of disregarding empty values, "Score 50%" will take empty fields into account for 50% in the calculation process. As a result, the matching percentage is lower.

First Name Last Name     Company name     Email Address Phone number Score
Jennifer Blake Laoreet Corporation j.blake@laoreet.com 1-817-297-7931 90% 
Jennifer Blake Laoreet Corporation Empty 1-817-297-7931

3. Score 0%

"Score 0%" will assign empty fields a matching score of 0%. As a result, the difference between the two field values is considered a non-match. The matching percentage will be lower.

First Name Last Name  Company Name     Email Address Phone number Score
Jennifer Blake Laoreet Corporation j.blake@laoreet.com 1-817-297-7931     80% 
Jennifer Blake Laoreet Corporation Empty 1-817-297-7931    

Depending on your 'Empty Fields' setting, your scenario could calculate a 100% score based on one field, even if there are more fields defined in your scenario.

Apply to

Decide to which feature of Duplicate Check for Salesforce you want to apply this search scenario. You can choose any number of features.

Manual Insert Prevention
Manual Update Prevention
DC Search
DC Convert
DC Check
DC Entry
DC Live
DC Job
Unique Import / API Bulk Insert
API Single Insert / Update
DC Apex API
Web to Lead
Data API

Weighting

Use the weighting setting to decide which fields matter the most when comparing records. A field with a higher weight impacts the matching percentage more than a field with a lower weight.

Example 1: Weighting equal to all fields

Field Matching Method Weighting
First Name Exact 10 (10/50 = 20%)
Last Name     Exact 10 (10/50 = 20%)
Company Exact 10 (10/50 = 20%)
Email Exact 10 (10/50 = 20%)
Phone Exact 10 (10/50 = 20%)


First Name Last Name     Company Name Email Address Phone Number Score
Jennifer Blake Loareet Corporation j.blake@loareet.com     1-817-297-7931     80% 
Jennifer Blake Loareet Corporation different@mail.com 1-817-297-7931    

Example 2: More weight on Email Address

Field

Matching Method Weighting
First Name Exact 10 (10/60 = 16.6%)
Last Name Exact 10 (10/60 = 16.6%)
Company Exact 10 (10/60 = 16.6%)
Email Exact 20 (20/60 = 33.3%)
Phone Exact 10 (10/60 = 16.6%)
First Name Last Name  Company Name Email Address Phone Number Score
Jennifer Blake Laoreet Corporation j.blake@laoreet.com 1-817-297-7931 67%
Jennifer Blake Laoreet Corporation different@email.com     1-817-297-7931
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Matching encrypted fields

You can use fields that are encrypted, e.g. with Shield Platform Encryption, in your scenario. The field values will not be displayed in duplicate search results.