Salesforce System creates Marketing Cloud Data Views as user-defined tables. The data provides information with respect to email campaigns and email subscriber’s activities. Access to these data views can be done through SQL Query language.
Are you interested to know how email opens, clicks or bounces can be tracked? Or are you eager to find out how much subscribers are engaging or billing out campaigns? The following data views provide solutions for those kinds of questions.
These views provide the back-end yet effective means within the Salesforce platform. Their functions include measuring the performance of emails and the activities of the subscribers. They are central in enhancing the campaigns.
Access Data Views: SQL Query Example
To harness the power of Marketing Cloud Data Views, one must carry out SQL Query in Salesforce Automation Studio. This enables marketers to pull out information concerning the behavior of the subscribers, for instance, the rate of email clicks, bounce rates, and even the number of spam complaints filed. Setting up an SQL query is simple even a child can do it, but interpreting the data takes some level of skill.
Let’s say for example you wish to determine the subscribers who have not opened an email for the last two weeks, you would look up the Sent view in order to pull such information. One of the key distinguishing features between Data Views and Data Extensions is the use of the underscore as a prefix table. A few examples include combining these queries to analyze email campaigns, the activity of the subscribers over a period of time and to enhance users engagement.
Step 1: Create a Data Extension
The primary provision for utilizing Marketing Cloud Data Views is to create a Data Extension where one can store the output of their query. A Data Extension is a data structure that holds the harvested data for further use. To do this, add columns such as SubscriberKey, AccountID, JobID, and EventDate.
It is important to observe the correct labels for the various columns because these labels are specific to the metadata tables. You can adjust the extension according to the data you want, making sure it meets your particular objectives such as how many people opened the email or how many people clicked on the email.
Step 2: Create an SQL Activity in Automation Studio
Now, you will enable SQL activity in Automation Studio. This step provides you with an opportunity to create a query that aims at specific Data Views such as Open or Sent. To illustrate this if you want to find out which subscribers have emailed bounces, your SQL query would go for the data in the Bounce view.
This step is particularly important because this is where you limit your analysis. This means you can scan for opened emails or undeliverable SMS and then closely examine specific engagement or campaign performance metrics. After creating the activity, ensure you associate it with the Data Extension you created earlier.
Step 3: Run the Query
Once you configure the SQL task, the last activity is executing the statement and analyzing the output.The data pulled will fill up your Data Extension with information such as status of subscribers, the number of spa complaints and even people who opted out from your campaigns.
It’s important to remember that Data Views in Marketing Cloud have a data retention period of only six months. This means you need to run queries regularly to access past data. Without this, you may lose access to valuable historical information. The historical data is crucial for improving future email campaigns. It helps enhance the content and structure of your emails. It also keeps users engaged throughout the campaigns. This ultimately contributes to the overall success of your campaigns.
Common Marketing Cloud Data Views
There are some Marketing Cloud Data Views that marketers use extensively when looking into the performance of campaigns. These consist of tables such as Subscribers, Click, Bounce, Open, and Sent. Each of these views provides a unique understanding of your subscribers and the campaigns.
To illustrate, the Subscribers view shows you a profile of active subscribers along with their status and level of interaction. In the same vein, the Click view tracks when the audience clicks the email to help you understand the most engaging content for the subscribers. With these details combined, the marketers are able to create such strategies that will increase levels of engagement.
Uncommon Marketing Cloud Data Views
In addition to the typical perceptions, Salesforce has a number of Data Views that are less known but have more opportunities. These include BusinessUnitUnsubscribes, Journey, UndeliverableSms, FTAF, and Complaint. These tables are not widely applicable but can show a different side of user engagement.
The BusinessUnitUnsubscribes view helps you track unsubscribe rates in different business units. This allows you to focus on problem areas. The Journey view provides valuable data about your journeys. It includes information like completion and engagement levels. Utilising these views can help you polish up your strategies and enhance email marketing efficacy.
Frequently Asked Questions
What are Marketing Cloud Data Views?
Salesforce generates system tables that keep records of incoming email campaigns and their interactions with subscribers.
How do Data Views differ from Data Extensions?
How can I access Marketing Cloud Data Views?
Implement SQL commands in Automation Studio or use Ampscript functions for fetching data.
What does the “Bounce” Data View track?
It monitors sent emails which have not been delivered along with their bouncing reasons.
How long is data stored in Marketing Cloud Data Views?
Data is stored for six months.
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Conclusion
First of all, learn the core SQL Query skill and learn more about the Automation Studio in Salesforce.This approach helps you go beyond the limits of these metadata tables. It will take your email marketing business to the next level.
