A Comprehensive Guide to Salesforce Data Mapping for Seamless CRM Integration

A Big Player in the CRM Market Today Salesforce is one of the strongest CRM platforms available today and utilized by companies large or small whether they are managing customer relationships, building sales pipelines etc.

But to effectively leverage Salesforce, enabling data from numerous data source integration is pivotal. Enter Salesforce Data Mapping Well, this is where we will be using it.

Data mapping: The process of linking data from one system (ex. Salesforce) to another to have the proper data moving between the two systems and ensuring that cross-platform information transfers are in alignment. Let me explain the basics of data mapping and why it is very important in solidifying flawless Salesforce CRM integration.

What is Salesforce Data Mapping?

Salesforce data mapping is the process of determining what data will be sent from one thing to Salesforce.
This will likely require both knowing the format of source data and what that looks like within Salesforce.
Customer data from either an outside database or another CRM generally includes such types of fields: “First Name,” “Email Address,” Phone Number.
For example, the corresponding fields in Salesforce would be mapped to their equivalent fields with Name, Email and Phone Number of Contact object.
This technique of mapping provides “a roadmap” for the data to travel, aligns all data from one system correctly with the fields and set (structure) in Salesforce.
To avoid issues: Data loss, duplicate data or incorrect data

Why Data Mapping is Important for CRM Integration

CRM systems are not working on their own, they must communicate with another business systems to help speed up workflow.
For example, a company uses both Salesforce and sales automation platform ERP or even a different customer service.
Data mapping supports this interaction, such that info can flow freely from the outside world into these systems with relevance wise.
Lack of data mapping puts the organization high on errors, inefficiency and unsaved opportunities for automation.
CRM data integration provides businesses with a clear view of their customers and improves the customer experience which translates into very effective sales & marketing.

Advantages of Effective Data Mapping

Data mapping strategies can deliver many benefits your business can realize

Data Enforce: Mapping of data enables businesses to send data between systems in a way where everything is accurately passed between systems which makes the mistake rate close to zero.
Operational Efficiency: When data moves smoothly between systems employees will waste less time dealing with manual data transfer and correction and it allows an increase in productivity.
Enhanced Reporting and Analytics: Improved your data, report and analysis which ultimately makes informed better business decisions easier.
Compliance: Best practices for data mapping enable businesses to assure they are handling the customer information in accordance with data privacy legislation (example: GDPR).

Salesforce Data Mapping Main Key Concepts

If you want to map data into Salesforce, there are some fundamental concepts in the Salesforce platform to remember. Salesforce has multiple parts and data how it crosses these parts will decide what data mapping is done?

Salesforce Objects and Fields

In Salesforce, the store of data is either in object or in field. A Salesforce object is essentially a database table for a business process (Leads, Contacts, Opportunities).
A Field is the smallest unit of data making up a record in the objects table. For example, there could be fields in the Contact object as First Name, Last Name, Email and Phone No.
During mapping data, you will associate the source system fields with corresponding fields in the salesforce object. So, with this approach data gets mapped properly and there are reduced errors.

Hierarchy of Data in Salesforce

Salesforce stores different types of data with

Built-in data: The standard fields that come with Salesforce (the Account, Contact and Opportunity object, etc.)
Custom Data: Salesforce allows the user to add custom fields as well as to store data which is relevant to business. Example: because of example, a real estate company can create a custom field Property Type in the Account object
It is important to map these data types correctly as the source system might use a different terminology or structure than Salesforce.

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Standard fields vs Custom

Some of the main differences between standard fields and custom fields during mapping of data are;

Salesforce Standard Fields: These are the fields you will find built into Salesforce (e.g. Name, Email and Phone number etc.) as part of every standard object like Account, Contact or Opportunity.
Custom Fields: What these are, is that these custom fields get created from users, in order that they can gather data which is related specifically targeted to their organization. For example, we may add a custom field for Customer Satisfaction Rating and add it to the Account object.
Knowledge of standard and custom field mapping is of utmost importance to make sure all the necessary information is correctly delivered to Salesforce.

Salesforce Relationship Fields

Salesforce has some different relationships which includes object to object relationship (like one-to-many or many-to-many relationship).
Objects and Relationships between them Object level relationships are what you use to bind different types of data: an Object to an Opportunity or Cases connected to a customer.
If you ever go to mapping data, remain aware of these relationships as the data should be linked over related objects correctly.
If I want to map a Contact to an Account let’s say, you need to know what I mean by parent child something where Account is parent and Contact is child. And that allows data to have structure in Salesforce.

Initial Data Mapping

Now that you have completed the steps of your prep, it is time to undertake the actual mapping. This is where you convert the data from your pre-existing object and field into the equivalent Salesforce object/fields.

Mapping data fields

Salesforce data mapping step of importance is identifying fields in Salesforce to your source system for every field.
Good examples include, if a Customer ID field exists on the source system you will need to match this to an appropriate field on the Salesforce Account object whether that be something like a Custom Field you named Customer ID.

This step requires:

Field compatibility: Source system field type should match field type in Salesforce (ex-field,text,number,date etc.)
Make the fields mandatory: As many objects being managed by Salesforce have mandatory fields like Account Name or Phone #. You have to make sure that these fields are compulsory and have a meaningful fallback.
Understand relationships: If you’re doing relationship mapping (e.g. Contacts to an Account) make sure the relationship is appropriately defined and the correct lookup field in the Account object has been set.
Field matching is the building block of a good data transfer, it should ensure all the data lands in respective Salesforce object.

Salesforce Data Loader: Using the Salesforce Tools

Salesforce itself provides tools like the Data Loader to enable batch importing of data from external systems. This tool manages simple as well complex data mappings and offers support for easy and smooth data transfer.

To operate the Salesforce Data Loader, please follow these steps:

Choose your data operation: (Insert, Update, or Delete based on requirements)
Select your data source: Hit to your source file in CSV.
Field Mapping: Select the interface and map the field within your Source file to the respective Salesforce field.
Import: Once mapping is done, run the import and verify results.
Data Loader is a wonderful tool to deal with huge amounts of data, especially useful for bulk migration or third-party systems integration.

Data Transformation and Clean-Up

Mapping data is not the whole cake. There will be data coming into Salesforce that might not map perfectly to the data requirements or quality standards of Salesforce. You should clean and transform the data before completing the data import as it is critical to have a smooth integration.

Data Normalization Techniques

Data normalization is the conversion of data to a specific format. This will help to keep all data consistent with itself and make sure that the salesforce can understand (correctly use). Some frequent methods for data normalization include:
Standardize the Dates: Different system use different formats for dates so standardize them to single format Ex MM/DD/YYYY
Consolidate multiple entries: If there are multiple entries in a source system for the same record (for e.g. Contact’s having multiple phone numbers), ensure that all of them match in one single entry to revamp any potential duplicates.
Field length adaptation: sometimes data will be greater than what Salesforce field allows through character limits. This action may load incorrect data unless you’re adjusting the data to comply with these limits.
Normalizing your data means giving the right shape to it hence Salesforce will be able to process and render it correctly without any glitches or mistakes.

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Dups and inconsistencies handling

Duplication Early on encountered during integration check duplicate records is one of the top 3 data quality issues. So perhaps a customer is captured more than once in different systems, for instance, one customer in Sales Opps and multiple contacts from this customer record.
Adjusting Field lengths: At times the data can be larger than field allowed character limits of Salesforce fields. This way you have adjusted the data to be able to adhere to these limits for it load correctly.
Normalizing your data means that you are giving a proper shape to it therefore Salesforce can read and show it properly without errors or misfortune.
Solving same problems again but in another name
For Mapping, data inconsistency arises from different naming conventions for the same field names, address formats or even typos while mapping. Before loading the data, make sure that you are standardizing and cleansing your data without any concern for these types of issues.

Salesforce data mapping tools and software

There are tools for data mapping available in native Salesforce, and several third-party tools to assist you as well.

Tool of the Salesforce Growth

Native tools for data mapping and integration; Salesforce provide a lot of tools:

Salesforce Data Loader: Workhorse for importing & exporting massive amounts of data between Salesforce and other systems
Salesforce Import Wizard: Straight-forward, for small data import and automatically mapping standard fields.
Salesforce Integration Platform: Salesforce provides some integration tools out-of-the-box, for example Salesforce Connect and MuleSoft to map and exchange data from third party apps.
For many organizations these tools are often more than enough (especially for those that are a big whale on the Salesforce ecosystem.

Third party solutions for Data Mapping

There are also third-party data mapping tools that work with Salesforce just fine by design:

Jitterbit: Highly regarded open integration platform for mapping data between Salesforce and other systems along with transformation, automation
Kingsway soft: The home page For Salesforce users to map and sync data from Source-Salesforce.
Dell Boomi: Extensive integration platform with features to map, transform & automate Salesforce data.
The third-party tools are designed for complex integration requirements or when an additional layer of sophistication is planned.

The power of Data Mapping to COP with Seamless CRM Integration

A successful mapping of Salesforce data does not just mean a seamless CRM integration process, but also those which follow the import of the data. Although, the ongoing integration and after mapping processes of performing tasks are just as crucial to make sure that the data is kept in a proper form, accurate.

Continuing: Integrating to Other CRMs and external systems

With most businesses using a few separate software platforms, integrating Salesforce into these systems may be part of your data mapping. Whatever the system, whether an external ERP or marketing automation platform or CRM — data should move effortlessly between all systems on your team’s behalf to stay organized.

For example, you can pull Salesforce into HubSpot – allowing sales to see the marketing history of the people leads are meant for. Likewise, if you are syncing Salesforce with an ERP ensure that order and inventory data are aligned in both systems.

How to Seamlessly Integrate Salesforce with Some Other External Systems

Implement Salesforce APIs for real-time synchronization of data on both platforms.
Use MuleSoft (middleware platform) to properly lend, monitor and ensure that the integrations are across Salesforce and low-level third-party systems.
Sync Data so that both systems have the latest and greatest records updated

Post-mapping Activities

Once the data mapping and integration are done, do all the post-mapping activities to validate that it works and maintain the system smoothly.

Confirm data migration

Once data has been mapped and transferred to Salesforce, validate the results that the entire data has moved correctly cross-check records against their source system. Here we go:

Extract data validation: Cross confirm the Salesforce data and the source system to make sure all missing or corrupt records were not missed during map.
Error detection: Check logs for errors or discrepancies in the data mapping/migration process.
User Acceptance Testing (UAT): Quiz end-users and validate that the mapped data serves their end-use requirements.
After migration the verification of the data is very important to know whether it is right and good or not.

Ongoing Data Synchronization

Years after the transition data synchronization is something that can’t be missed. Performing regular synchronization between Salesforce and external systems guarantees that both systems are up to date with all the latest information.
Salesforce Tigers Hide Any Rigorous Synchronization Process Use built-in Salesforce Integration tools or popular 3rd party tools such as Zapier and Integrate to automate it. This will make the synchronization consistent and stop future data mismatches.

Conclusion

Integration of Salesforce Data Mapping plays an important role in linking Salesforce with the rest of business systems, so that data flow can be clear and help organizations gain more insights into their customer relationships. The degree to which your data mapping is prepared and tested and the right tools used in the right use cases determines the success rate of your Salesforce implementation and more especially the accuracy of your data.

Sticking to best practices, overcoming challenges and using the right tools to the best of its abilities can move your Salesforce CR into complete integration with other systems enabling more efficient operations, and therefore better decisions.