The functionality of Salesforce can be leveraged by integrating it with databases, servers, and third-party applications. Salesforce integration allows users to work on a centralized platform and bring data from multiple platforms together for ease of operation.

Through Salesforce integration, your team can operate on a single unified platform without having to switch platforms for performing specific business processes. You can integrate Salesforce according to your needs and preferences. Salesforce PayPal integration would help you streamline your payments. Salesforce QuickBooks integration would help you leverage your accounting practices. Salesforce integration allows you to expand the features provided to you by Salesforce and make work easy for your team.

However, the manner in which you undertake integration is extremely important. Your approach towards integration can be determined by the integration patterns you use. As the name suggests, a Salesforce integration pattern is the structure implemented and a unique set of steps followed by developers to integrate Salesforce with a suitable application.

Wherever you go ahead with Salesforce integration, always remember that an integration pattern should have a combination of at least two of the following elements:

• The transformation that your dataset will undergo
• The results comparing the original state of your database to the desired state
• The destination where your data will be inserted
• The source where your data is stored before integration
• The criteria determining the scope of your data to be copied, replicated or moved

Here are some of the major Salesforce integration patterns you can implement to integrate your CRM with a third-party application:

1. Data Migration

Simply put, data migration is the process of moving specific datasets from one location (system) to another. The migration pattern of integration allows developers to create automated and seamless migration solutions that create functionality that can be shared across different users within an organization.

This can be done by setting configuration parameters for passing into the API calls to migrate the concerned datasets in and out of the Salesforce org. The process can be carried out on command or on an “as needed” basis.

The migration pattern of Salesforce integration is an idea for moving data from a legacy system to Salesforce, backing up customer master dataset, consolidating a CRM system, and much more.

2. Data Broadcast

The data broadcast integration pattern involves moving datasets from a specific single-source system to different destination systems on a continuous real-time (or near real-time) basis. In simple words, it is a one-way synchronization method following the “one to many” approach.

As opposed to the migration pattern, the data broadcast pattern is transactional in nature. It is optimized to help you process records as quickly as possible. This pattern helps you in keeping data up-to-date between multiple systems across time. Whenever you are implementing this integration pattern, it is important to ensure that it is highly secure and reliable to prevent unwanted data loss in transit.

3. Data Aggregation

The aggregation pattern involves gathering data from multiple sources and moving it to a single destination system. This integration pattern helps developers to eliminate the need to run multiple data migrations regularly, getting rid of concerns about data accuracy, and ensure smooth data synchronization. This is one of the simplest Salesforce integration patterns to extract your data and process it into a single application.

The data aggregation pattern ensures that your data is always up to date, is not replicated, and can be processed effectively as per your requirements. The important considerations for implementing this pattern of integration are collecting data, merging multiple datasets, formatting data, ascertaining the scope of the data, and inserting data.

4. Bi-directional Data Sync

This Salesforce integration sync pattern involves integrating multiple datasets with multiple destination systems. This allows different datasets to behave like a single system and allows them to acknowledge the existence of different datasets.

The bi-directional data sync pattern of integration is ideal when you need different tools or systems to accomplish different functions within the same datasets. It enables both the systems involved to be used while maintaining a consistent and real-time view of your data across systems.

5. Data Correlation

The data correlation pattern is very similar to the bi-directional data sync pattern with one major difference between the two. Data correlation allows you to undertake a bi-directional synchronization of data across multiple systems only if the concerned item naturally occurs in both systems. On the other hand, the bi-directional data sync pattern would create new records if they are found only in one system and not the other.

This integration pattern is ideal when you want to share data between two systems having the same items or contacts. Here, the most important consideration to keep in mind is the definition of “same” when used for items across the two systems. This definition can differ from one industry to another and it is important to understand the context before going ahead with the integration.

6. Real-time Integration

Real-time integration is an approach where data between the integrated platforms is synced on a real-time basis. Any changes made to the data pertaining to one platform would immediately reflect on the other platform immediately. This prevents users from manually reconciling data and keeping both platforms in sync.

Real-time integration is most commonly used for integrating marketing and sales platforms, such as the Salesforce HubSpot integration. These integrations allow users to perform a range of different processes with utmost speed, efficiency, and accuracy.

7. Real-time Mashups

Here, the developers build a user interface in Visualforce. Just like a traditional HTML-based web application, real-time mashups allow custom branding, complex data flows, and callouts to retrieve data from systems external to Salesforce.

This approach is ideal when you need immediate access to datasets stored outside your Salesforce org, such as obtaining specific documents from external systems.

The Final Word

These were the major Salesforce integration patterns that can be used to extend the functionality of your Salesforce org. Always make sure that you choose the pattern that best suits your integration requirements.