Approach to Salesforce Data Cleansing

Successful implementations rely heavily on the cleanliness of data migrated into your Salesforce environment. Bad data will negatively affect user adoption, so adequate time and attention should be built into the project to cleanse the data before migration.

Below is a standard process to Salesforce data cleansing that Sikich recommends to partner with our clients to achieve duplicate cleansing and ongoing duplicate prevention, within your Salesforce environment.

Tool Selection

Discuss duplicate issue (Client/Sikich)

  • What is the nature of the duplicate problem?  Accounts, Contacts, Leads, Possibly Opportunities?
  • What is the client’s estimation as to the completeness and quality of their data?
  • In the client’s estimation, how many duplicates could there be

Based on this information Sikich will recommend a tool.

Data Analysis

Sikich performs data analysis using the tool and present the results to the client.

Sikich will apply both “Rigid” and “Fuzzy Logic” to generate reports to assess the magnitude of the duplicate issue, The reports will show results such as:

  • Exact Account Name and Email Address matches
  • Exact match on Account Name/Address combined
  • Fuzzy logic match on Account Name (e.g. Acme Inc., Acme Incorporate, Acme)
  • Data Completeness – Incomplete and inaccurate data is one of the biggest challenges with duplicate cleansing, To assess this issue, Sikich will provide reports showing the following:
    • Percentage of accounts without an Address or Phone.
    • Percentage of Contacts without an Email Address, etc.

Based on a review of the reports and feedback from the client, Sikich will develop a plan for cleansing.

Cleansing Process

There are two different options for data cleansing:

Auto Merge

  • Agree on “Rigid Logic” for auto merge, if possible, For example, duplicate Email Address Contact records will be automatically merged, Client will need to provide rules such as: which Contact record will govern the merge—the most recently created or changed? Who will be the record owner?  Because of the difficulty in defining firm rules, many clients do not choose the auto merge method.
  • Sikich or the Client will execute the Auto Merge

Subjective (Selective) Merge: This option requires HEAVY involvement from the client.

  • Sikich will use the tool to generate lists of “potential duplicates.”
  • The client will engage their Subject Matter Experts (SMEs) to review the potential duplicate records individually and decide whether or not to merge and if so, make final decisions on conflicting data (such as different phone numbers on Contact records that should be merged).
  • Sikich will either work side by side with the client and do the technical execution of the merge or Sikich can train the SMEs on the use of the tool, This will be decided when the plan is created in the prior step.

Ongoing Duplicate Prevention (Post Cleansing)

To prevent duplicate data issues in the future, Sikich will work with the Client SMEs to determine Duplicate Prevention rules to be applied after the cleansing is complete, Sikich will assist the client with the technical set up of the rules, either with the tool selected or native Salesforce Dupe prevention, The rules will be applied at the end of the cleansing process.

Duplicate prevention rules are generally applied in two ways:

  • Full Prevention – New records cannot be created if the rule is matched (i.e. identical email address already exists on another Contact record).
  • Flagging a Potential Duplicate – When a new record is created, the user will receive a warning message that they should investigate the potential duplicate before saving the record (i.e. identical First and Last Name at the same Account), The user is presented with a link to the potential duplicate record; however, the user has the option to Ignore and continue with creating the record.

Have any questions about Salesforce data cleansing or Salesforce itself? Please reach out to one of our Salesforce experts at any time.

This publication contains general information only and Sikich is not, by means of this publication, rendering accounting, business, financial, investment, legal, tax, or any other professional advice or services. This publication is not a substitute for such professional advice or services, nor should you use it as a basis for any decision, action or omission that may affect you or your business. Before making any decision, taking any action or omitting an action that may affect you or your business, you should consult a qualified professional advisor. In addition, this publication may contain certain content generated by an artificial intelligence (AI) language model. You acknowledge that Sikich shall not be responsible for any loss sustained by you or any person who relies on this publication.

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