Like many people in the Salesforce ecosystem, you may be intrigued by the announcement of Marketing Cloud Growth Edition — especially since access to the platform is available to current Marketing Cloud Account Engagement (Pardot) users on the “Growth Edition” tier. However, a key differentiator between the platforms is that Growth Edition gives marketers access to Data Cloud credits.
In this post, we’ll explain how Account Engagement users can tap into those Data Cloud credits through Growth Edition, the differences between both platforms’ billing models, and strategies for marketers to follow while using Data Cloud credits.
Understanding the Consumption-Based Billing Model
Whether you’re a marketer, an operations manager, an admin, or something in between, there’s a lot to look forward to as functionality moves into Salesforce core. For example, consider the flexibility of segmentation with Data Cloud and leveraging Einstein AI to supercharge your campaigns.
As you start to explore this toolset and feature set, however, there is an important mindset shift in the structure of the product to be aware of.
Like Data Cloud, Marketing Cloud Growth Edition is a consumption-based toolset. That means your team’s feature usage within the platform determines how many credits are used and what your organization will pay each billing cycle.
Back up a second — Account Engagement has usage limits, too?
Yes, Account Engagement has certain feature limits. If you’re an admin, you’re probably familiar with navigating to the usage tab and checking your mailable prospect database or how many repeating engagement studios you have in play (if you’re not, check out our blog post on monitoring your mailable database).
How does the Account Engagement billing model differ from Growth Edition’s?
Outside of total mailable database count and feature limits based on your edition, segmentation and email sending are generally open season for users. Dynamic lists can be run and emails can be sent to your heart’s content.
The Einstein toolsets available in the more premium editions of the platform also generally run for the whole database and have no specific consumption considerations.
In comparison, Marketing Cloud Growth Edition is structured so there are credits for many of the core actions taken. This aligns with the structure of Data Cloud, which serves as the segmentation engine for Growth campaigns.
Marketing Cloud Growth Edition Standard Credits
For new setups of Growth Edition, these are the standard credits provisioned:
- 10K Marketing Unified Profiles
- 240K Data Cloud Credits
- 10K Segment and Activation Credits
- 1TB Data Cloud Storage
- 180K Emails/year
- 20K Einstein Co-Create Requests for email content generation
These numbers may depend on your edition and specific agreement with Salesforce, and all of these areas can be extended with additional credits.
Other business segments may have Data Cloud
Also worth considering — Data Cloud is not solely a marketing tool, and Data Cloud may already be in use by other divisions of your organization. But don’t fret, that’s a good thing!
A key benefit of the toolset and moving to Growth is gaining the ability to align customer experience processes across all departments.
Is there an easy way to monitor my consumption-based credits?
Glad you asked! Yes, Salesforce released a feature called Digital Wallet to help admins keep track of consumption-based tools.
The Consumption Card tab can be accessed by users with appropriate permissions and provides an overview page to monitor credit usage.
This page also includes access to insights that help you understand how usage is trending over time and where you might need to plan for expansion.
How do I go about strategically using these? What is a “credit” worth, anyways?
Different considerations are at play for different consumption metrics within Marketing Cloud Growth. Email send credits and Einstein Co-Create credits are relatively straightforward — the total number of emails launched and uses of AI copy generation for the content, respectively.
Where complexity lies is the data harmonization and segmentation process in Data Cloud and credits needed there — calculated based on rows in your database used and processed for different actions.
You can see a more detailed breakdown of the calculations here.
Data Cloud Credit Usage Examples for Growth Edition Marketers
In practice, these areas are likely where a marketer will consume Data Cloud credits.
Data Harmonization and Unified Individuals
- Target Audience: As opposed to “prospects” within Account Engagement, users create segments in Data Cloud for Marketing Cloud Growth Edition campaigns via Unified Individual profiles.
Instead of 1:1 syncing with a lead or contact, these unified profiles can link multiple data sources to create a 360-degree view of the customer, with data from Salesforce and external data sources. - Identity Resolution: To make sure these unified profiles are accurate to your map of data, identity resolution rules are created in Data Cloud to join datasets by the relationships you define.
The harmonization process this executes does utilize Data Cloud credits, so data complexity here can affect the requirements for this process. Learn more about the process in this Trailhead! - Growth Edition also includes a set of features for incorporating consent per channel into this profile, determining whether the individual can be sent communications and helping you maintain privacy and compliance for your audience.
Pulling and Refreshing Segments
- Segment Creation: When you create a new segment or modify an existing one, Data Cloud Credits are used to execute the data queries that define the segment criteria. This process involves filtering and aggregating large volumes of data to isolate specific audiences.
- Segment Refresh: To keep your segments up-to-date, you’ll need to refresh them regularly. Each time you perform a refresh, credits are consumed as the system reprocesses the data to ensure the segment reflects the most current information.
Using Einstein’s AI Capabilities
Note: this refers to Einstein Features within Data Cloud, not Einstein Co-Create content generation within Marketing Cloud Growth. You can get more on the specific rate consumption for AI models with Data Cloud here.
- Predictive Scoring: Einstein AI can analyze historical data and predict future behaviors. Utilizing predictive models or scoring capabilities consumes Data Cloud Credits based on the complexity and volume of data processed.
- Recommendation Engines: Whether you want to personalize content or recommend products, Einstein’s recommendation engines leverage AI to analyze user behavior and preferences. This process also requires Data Cloud Credits, reflecting the computational resources needed for these advanced features.
- Automated Insights: Einstein provides actionable insights and analytics by examining trends and patterns within your data. Accessing these insights involves credit consumption, especially when dealing with extensive datasets or detailed analyses.
How to make the most of your Data Cloud credits
To make sure you’re using Data Cloud as efficiently as possible, keep the following considerations in mind.
- Efficient Querying: Optimize your segment queries to be as efficient as possible. Reducing the complexity of queries or breaking them into smaller, more manageable tasks can help conserve credits.
- Scheduled Refreshes: Instead of frequent manual refreshes, schedule them during off-peak times or based on data needs. This reduces unnecessary credit usage while ensuring segments remain accurate.
- Strategic AI Usage: Use Einstein’s AI capabilities strategically. Prioritize features that deliver the most value for your marketing goals and ensure that the credit expenditure aligns with your objectives.
- AI Models Management: Regularly review and refine AI models to maintain their accuracy and relevance. Properly trained models can yield better insights, maximizing the return on your credit investment.
Take advantage of the consumption-based model to understand what you’ll need as you scale
Hopefully, this gave you a good introduction to the concepts needed to monitor and understand credit usage as you consider using Marketing Cloud Growth Edition and Data Cloud alongside Account Engagement.
Don’t let this scare you off — while there are new concepts to learn, the toolset opens possibilities for marketers ready to use data to create the best possible customer experience and segmentation.
As the “Growth” name implies, it sets your business up for cost-efficiency in the short term and scalability in the long term. As you continue to scale and incorporate new data sources and channels, there’s a more defined method to ingest this data, improve your personalization, and predict the impact to your costs over time.
As you explore more, please check out our FAQ article on Marketing Cloud Growth or send us a message if you have any other questions.
