Salesforce Duplicate Management


Salesforce Duplicate Management

Data Duplicates is the biggest challenge and which is recurring for anyone who manages data between systems. It is always a significant concern to the company to clear the system of data duplication as its effect in all terms of business, such as resource efficiency, productivity, and the most important time consumed as a whole unwanted system involves the same set of work that has already been done.


Every Salesforce customer has an issue with the data duplication; this is something thing which depends on the process of the system, and ideally, it’s challenging to make the process to create data that will always be unique.

Maintain clean data, and accurate data is one of the most crucial challenges you can do to get the most out of Salesforce. It builds the trust of your sales team and Customer, helps you to work toward different data protection and privacy regulations.

Duplicate records cause sales teams to lose trust in their CRM system. You always want your team to question the validity of the data.

merge contacts salesforce

Merge Accounts, Merge Contacts and Merge Leads in Salesforce

To make more data accurate and maintain clean and accurate data in an organization, Salesforce introduced a new feature concept called Salesforce Duplicate Management. This feature provides an effective solution to control duplicate records and not to create a duplicate record in Salesforce.

The sales team needs to maintain excellent relationships with customers, and keep your leads, accounts, and contacts clutter-free. By activating duplicate rules and the Potential Duplicates component, you can control whether and when sales reps can create duplicate accounts, contacts, and leads. You can also permit them to merge duplicate leads, business and person accounts, and contacts.

Let’s take an Example


Data deduplication is a method to reduce storage by identifying redundant or duplicate data in your storage environment. Only one single unique copy of the data is retained on storage media, and unnecessary or duplicate data is replaced with unique data copy.

Salesforce provides some of the rules which will help to reduce the duplicate record in the system this as per requirement or business need. These are two things that are important for controlling duplicate records in Salesforce.

Matching Rule – Matching criteria to identify duplicate records. Salesforce comes with three standard matching rules.

  • Business accounts
  • Contacts
  • Leads

Salesforce Duplicate Rule- It will help on Salesforce matching rules and determines actions to take as it identifies duplicates and depending on how you configure Duplicate Management, Business User will see an alert that they are going to create a duplicate or cannot allow him to create the record which seems to be duplicate.
After Spring 15, Salesforce has given standard duplicate rules for business accounts, contacts, leads, and personal accounts.

  • An alert or report for the user creating a duplicate.
  • The blocking of the creation or editing of a duplicate record.

Check in Salesforce who it can be configured.


Matching rules and duplicate rules work together to ensure that your sales teams work with data that’s free of duplicates. Before saving or updating the record, matching rules and duplicate rules provide warnings for the duplicates based on Configured matching rules and duplicate rules.


Matching Rules

Salesforce provides some of the key features for the Matching rule which will help to protect your organization from duplicate records.

Name Variant- If the ecord contains a value for both First Name and Last Name fields, those values are transposed to consider possible data entry mistakes.

Acronym- It will consider acronyms and full titles. Let’s take will match if Rule is   VP and Vice President.

Address– Addresses are broken into different sections and compared those sections. Each section has its own matching method and match score.

Example- Duplicate Management compares these two addresses. 123 Market St, Ste 100 and 123 Market Dr, Ste 300.
Some of the contacts include phone numbers with country codes. Salesforce flags contacts with matching phone numbers as duplicates, even though one includes a country code and the other doesn’t. There are some limitations from duplication management.

Let’s create a Custom Matching Rule.

  • Go to Setup and Search Matching Rule.
  • Click New Rule.
  • Select the Object.
  • Provide name of the Rule.
  • Description of the rule what action it will perform.
  • Most Important provide the matching criteria. There can be multiple criteria condition with define operation.

Duplication Rules

A duplicate rule defines what happens when a user views a record with duplicates or starts creating a duplicate record, duplicate rules step in and determine what to do with them.

Let’s take an example.

  • Go to setup and Search Duplicate Rule.
  • Create New Rule and Select the Object.
  • Provide duplication record Name and description.
  • Define the action on Create and Edit record like Block or Allowed.

Error Logging

Error Logs save errors that will be helpful. There could be a chance where the matching mechanism is not available due to which the Duplicate check could not be performed, or the Duplicate record sets or the Duplicate record items could not be saved. The error log will help you solve this. The Error logs help the user to identify the records.



Salesforce defines the logic that determines whether two fields match. For the exact matching method, the exact matching algorithm is automatically used. For the fuzzy matching method, various unclear Matching Algorithm can be used. Each matching algorithm is scored based on how closely it matches the two fields. For example, if you select the exact matching and the two fields match, the match score is 100. If the two fields don’t match, the score is 0.

how to merge accounts in salesforce


Scoring method will be helpful where data duplication can be the same but not based on the exact match of the data, but it will based on set of matched. It uses the algorithm to calculate the score, generally 80% or the score considered as a make the record as duplicate which is call threshold. Threshold is basically the minimum score that needs to be satisfied for the match, for the record to be marked to be duplicate. Depending on the type of fuzzy method, you have to identify and duplicate management system would automatically set a threshold.

Matching Key

When a matching rule is activated, one or more match keys are applied to existing records. The matching rule looks only for duplicates among records with the same match key. If two records don’t share match keys, they aren’t considered duplicates and the matching algorithms aren’t applied to them. This indexing process improves performance and returns a better set of match candidates. Only standard matching rules use the scoring method.

  • Average: Uses the average match score.
  • Maximum: Uses the highest match score.
  • Minimum: Uses the lowest match score.
  • Weighted Average: Uses the weight of each matching method to determine the average match score.


It helps to determine the minimum match score needed for the field to be managing a match. The field is given a match score based on how closely it matches to the same field in an existing record.

Edit Distance Algorithm

Edit distance is a way of identifying way of dissimilar two strings are to one another by checking the minimum number of actions required to transform one string into the other. Determines the similarity between two strings based on the number of deletions, insertions and character replacements needed to transform one string into the other.


It helps to determine the similarity of two sets of personal names. Let’s take an example, the first name John and its initial J match and return a score of 100.

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01. Jaro Winkler Distance

Determines the similarity between two words based on the number of character replacements needed to transform one string into another. This method is best for shorting of the data string, such as personal names, Last Name or Title.

02. Keyboard Distance

Determines the similarity between two strings based on the number of deletions, insertions, and word replacements needed to transform one string into the other, this help to weighted by the position of the keys on the keyboard.

03. Kullback Liebler Distance

Determines the similarity between two strings based on the percentage of words in common.

04. Metaphone

Determines to identify between two strings based on their pronunciation. This algorithm attempts to account for the irregularities among languages and works well for first and last names.

05. Name Variant

Identify whether two names are a variation of each other. Let’s take an example. For example, Ravi is a variation of Ravindra and returns a match score of 100. Ravi is not a variation of hari and returns a score of 0.

06. Syllable Alignment

Determines the similarity between two strings based on their sounds. First, the character strings are converted into syllables strings and then the syllable strings are also compared and scored using the Edit Distance algorithm. This matching algorithm works well for company names.


When a matching rule runs, it applies one or more match key formulas before applying a comprehensive matching. Match keys will help to increase the performance of duplicate rules through a introductory comparison that narrows the matches to the 100 most likely duplicate records. The rule applies the matching equation only to those possible matches. In exceptional instances, match keys result in unobserved duplicates, but generally, match keys very much improve the performance of duplicate rules.

  • The matching equation that determines the understanding of the fields is rewritten into a standardized format that translates the OR statements into AND statements
  • Values for fields in the matching rule are normalized.
  • A matching key is generated using the field grouping specified in the identical field format. A matching rule can have multiple match keys. A custom matching rule can have up to 10 match keys. It can be prevented from saving a matching rule that requires more.
  • The matching key is used to combine normalized field values for all record.

How to merge Accounts in Salesforce

The standard person account matching rule identifies duplicate person accounts using match keys, a matching equation, and matching criteria. To use the rule, first enable person accounts, and then activate rule in Setup.

Match keys speed up matching by narrowing the potential matches to the most likely duplicates before the rule applies the comprehensive matching equation.



Let’s take an Example of Matching Equation– The threshold for the first three conditions in the equation is 85; the threshold for the fourth condition is 75.

(First Name AND Last Name AND Email) OR (First Name AND Last Name AND Billing Street AND (City OR ZIP)) OR (First Name AND Last Name AND Phone ) OR (First Name AND Last Name AND Phone AND (City OR ZIP) AND Mailing Street AND Phone)




Finding Duplicate Records

  • Large Volume– every person knows that working with Salesforce can be annoying when dealing with large data volumes. This is mainly true of jobs of any kind. Salesforce is well aware of this problem and warns:
  • Cross Object Duplication– The chances are beautiful that your new lead is already present in your Salesforce organization but as a Contact. To make sure you don’t work with carbon copy data, cross object matching is very important. Salesforce can do alerting on manual insert for all objects, but jobs are limited to finding duplicates within objects.
  • Job Limitation– Running duplicate jobs are necessary to combine duplicates in your existing database. Salesforce has limited this feature to the recital and Unlimited editions.
  • Matching Limitation- Finding duplicates is a responsive business. Nobody wants to miss any duplicates, but you can not want false positives either. To fine tune your matching, you need specific algorithms. Salesforce Duplicate Management offers correct and unclear matching algorithms. In addition to limited matching algorithms, Salesforce Duplicate Management also lacks a weighting method. A matching email address should count difficult than a matching first name.

Merging Duplicate Records

  • Create Restriction– It is vital to believe that the alerting and reporting of a duplicate ahead creation or edit only works for manual actions. 99% of all records are added in imports or through APIs. In these cases, Salesforce will block the creation of a new record. You will lose important information in this process.
  • Object Limitation– Duplicate Jobs do not allow the comparing and merging of records on custom objects, which is important to prevent data duplication.
  • Manual Marge- Salesforce enables you to merge record groups. The only way to go about this is to open and check each duplicate group manually. Duplicate Check for Salesforce allows you to fast merge groups without opening them and even to merge all groups in the list mechanically.
  • Max Record limitation– Chances are attractive and your job has provided in a list of duplicate groups that includes groups of four or more duplicates of the same record. Salesforce Duplicate Management has a limitation on merging a maximum of three records at a time. This will slow you down in processing the list.
  • Automatic process– Data Creation blocking is also a regular action but blocking is not attractive. If your marketing automation processes run all the time, you cannot wait for a manual review of duplicates. In such a scenario, automatic checking and merging of new duplicate records saves you time and do not delete valuable. These are the limitations to decide if Salesforce Duplicate Management suits your needs or if you require another solution.

Salesforce Duplicate Management Solution

Salesforce Duplicate Management fits your needs, but should you need more deduplication capabilities, the App Exchange offers many alternatives. Below is the process that needs to follow to implement the Duplication Management


Data Requirements:

First, set to identify the object where you are looking to implement the tool. Make a list of the object which should be unique, and data duplication should not be there. Based on that, the further process of the implementation will be drive.
Identify the Field, which should be the part of the data uniqueness, and will be play role as user key of the record.
Identify the Matching Rule, which will be applied and vary from object to object to make it more data quality.

Word ignorance as many of the word of the data does not play an important role in making it identical. This is the most important case in Account as many Companies have LLC and Pvt. Which is not relevant to identify duplication, and those words should be ignored.

merge accounts salesforce

Process requirement 

There is some key feature which should take care while processing the data as it could be important detail or unrelenting.

  • Data needs to remove or keep the backup.
  • GDPR and other compliance.
  • Data legal issue.

Tool Selection

Salesforce provides Duplication management tool, which has some challenges which we already discussed in the above bogs. Salesforce App Exchange offers many of the Duplication Tool. Best trusted one of the tools is Smart Duplicate Manager, which offers several features and its trusted product, which have been used many of the fortune customers.

It will provide full feature installation as a trial version without any cost. You can configure the tool in your organization free of cost, and it will provide all the features as license use has during the trial period.

You can connect with customer support before paying for the application. Before paying for an app, you need to make sure both the app and support meet your expectations.



Smart Duplicate Manager – the Salesforce Duplicate Manager – provides easy configuration wizard which help to configure the tool in just section the option. Application documents will help guide if any assistance required as Company has provided a high quality of the detail, which will help the user training.


Prevent of data duplication is not an onetime activity. Prevention and scheduled clean-ups are essential to keeping your Salesforce Clean. Salesforce has continued development and improvement strategy, which always means a new field and new costume object will be created. Make sure to update your deduplication settings to reflect these changes.

Salesforce provides basic duplication management functionality, which will help the initial setup business of where the system is not complicated. When you required organization data, quality should be high, and other objects, cross object matching, faster processing, or automatic processing should be work fine. Smart Duplicate Management will play an essential role in your organization to prevent this issue, and it will make the process smooth.

In the next blog, we will discuss Key Features of the Smart Duplicate Management, App Exchange Installation guide, and Apply duplication management process on real-time data.

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