Introduction
CRM (customer relationship management) software is the lifeblood of any modern B2C company. By monitoring and storing all of your interactions with prospects and customers—from their first visit to your website to their most recent purchase—CRM software makes it dramatically easier to segment your customer base, identify hidden trends in the data, make smarter predictions, and forecasts, and much more.
However, CRM data doesn't always come in a nice, neat package ready for you to consume out of the box. In many cases, data in your CRM needs to go through processes such as data cleansing and data transformation before it's ready for use in business intelligence and analytics workloads.
Salesforce is the world's leading CRM platform, with nearly 20 percent market share. In other words, understanding the process of Salesforce customer data transformation is crucial for hundreds of thousands of organizations. In this article, we'll discuss how and why to transform your Salesforce customer data for use in BI and analytics.
What is Data Transformation?
Data transformation, broadly defined, is the process of converting data from one representation to another. Often, data transformation is performed as the intermediate stage in the ETL (extract, transform, load) process, which takes information from one or more data sources and collects it in a centralized data warehouse or data lake.
A few types of data transformation include:
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Aggregation: Combining multiple data values to form one or more new data points. For example, you can sum up the revenues generated by each of your sales representatives to calculate the total revenue of your sales team.
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Concatenation: Joining compatible data values into a single data value, such as combining a user's first and last names.
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Filtering: Applying filters to data records to remove irrelevant information. For example, data records for customers that contain personally identifiable information (PII) should be filtered to remove this PII before they're used for BI and analytics.
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Joining: Connecting two or more database tables that share matching columns. For example, you can combine a table containing students' contact information with another table containing their coursework, matching them with the shared "student ID" column.
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Standardization: Putting different data values that represent the same concept into a single, standardized format. Examples include converting state names to abbreviations (e.g., California to CA), converting miles to kilometers, and converting dates to MM/DD/YYYY format.
Related Reading: Data Transformation: Explained
Transforming Customer Data in Salesforce
With all that said, why should you want to transform your Salesforce customer data?
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Better analytics: Data transformations such as filtering, joining, standardization, and validation are must-haves for BI and data analytics workloads. Without performing data cleansing and consolidation, the outputs of your BI tool could be based on incorrect or out-of-date information. For example, if you don't standardize the date formats of records in your Salesforce CRM, your analytics software could miss many of these entries if it's only searching for records with dates in a specific format.
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CRM data decay: An estimated 30 percent of customer data in your CRM loses its accuracy every year, for a variety of reasons. People move, change jobs, and get new contact information while businesses undergo employee turnover and mergers or even shut down. Using data transformations, you can help eliminate old, inaccurate, and duplicate information so that you always enjoy the freshest CRM data.
However, the process of Salesforce customer data transformation is far too massive and time-consuming to be performed manually on any but the smallest CRM databases. Surveys estimate that data scientists already spend 60 percent of their time cleaning and preparing data, and just 20 percent on actual analysis—so how could you ask them to spare any more manual effort?
The good news is that with ETL tools such as Integrate.io, you don't have to. Integrate.io is a powerful, feature-rich ETL and data integration platform with more than 100 pre-built third-party integrations, including Salesforce.
With Integrate.io, it's easier than ever to create robust, fully automatic data pipelines from your data sources to your enterprise data warehouse in the cloud or to another destination such as Salesforce. Integrate.io's user-friendly, drag-and-drop interface lets you define a variety of transformations for your Salesforce customer data—joining, sorting, cloning, filtering, and many more.
You can get started by using your Salesforce CRM as the data source for your data integration workflow, thanks to Integrate.io's built-in Salesforce integrations. Once your Salesforce data is flowing through the pipeline, Integrate.io makes it simple to define many different data transformations of your choosing, as best fits your BI and analytics needs. Finally, you can then redirect your transformed customer data back into your Salesforce CRM, as well as load it into a centralized data warehouse—ensuring that the information is up-to-date in both locations.
Organizations of all sizes and industries have successfully used Integrate.io to transform their Salesforce customer data. As of writing, Integrate.io has an average rating of 4.4 out of 5 stars on the business software review website G2, based on 98 reviews. In a five-star Integrate.io review, cloud application architect manager Steve L. notes that "Integrate.io has been great for us," adding:
"Integrate.io has helped us connect several different databases, including Salesforce. The connections are fairly simple to build, and there is solid functionality to manipulate data where needed. We've been able to eliminate data silos and pull information from a finicky ERP that was previously a manual process to move data."
Another Integrate.io user, an IT administrator, writes that "Integrate.io saves time and increases data accuracy":
"I came from very minimal experience working with SQL, REST APIs, and Salesforce SOQL. In a few weeks, we were able to connect our Salesforce into a SQL database for reporting, storage, and analysis. The time we saved and the insights we gained were invaluable. With Integrate.io's support, documentation, and straightforward design, there were very few challenges I faced... I would recommend them to anyone looking to connect data in CRM systems like Salesforce to SQL databases, and anything in between."
Finally, a pharmaceuticals administrator notes that Integrate.io excels at Salesforce customer data transformation on a very large scale:
"Integrate.io was the primary tool used to migrate millions of records from one Salesforce org to another. Integrate.io was able to easily scale and meet the performance SLAs (service level agreements) for large-scale data migration."
How Integrate.io Can Help with Salesforce Data Transformation
Ready to learn more about using Integrate.io for Salesforce data transformation? Check out our article "Using components: Salesforce source" for a quick overview of what's possible with Salesforce and Integrate.io. You can also get in touch with our team of data experts today for a chat about your business needs and objectives, or to start your free trial of the Integrate.io platform.