The Salesforce Summer ’23 Release Notes are out and we’ve been combing through them to see how these changes will affect our clients and readers. This post includes what you’ll need to know as a Marketing Cloud Account Engagement (Pardot) admin or user.
Probably the new release feature I am most excited about, an Account Engagement Connector for Data Cloud! This connector will allow you to pull in Data Cloud segments via Account Engagement Dynamic Lists, allowing you to not only market directly to your Data Cloud customers, but also reap the benefits of Data Cloud’s unified view of customer data to help support your ABM initiatives.
If you have multiple Account Engagement Business Units (BUs), then you probably know the pain of keeping universal assets exactly the same across all of your BUs. The Summer ‘23 release is hoping to make that pain point a thing of the past by enabling Salesforce Flow to replicate assets across BUs. This new feature will allow for replication of custom fields, email templates, engagement studio programs, files, and custom redirects! Keep an eye out for a follow up post on this, I can’t wait to try it and share some tips and tricks with all of you.
Back in the Winter ‘23 release, Salesforce announced they were doing away with the “Most Recently Updated” sync behavior option for Account Engagement’s “Opt Out” field. However, after hearing from the community, this change is being rolled back. So, if you didn’t prepare for this change, your procrastination has paid off! Just keep in mind new business units created after October 18th, 2023 will have the Opt Out sync behavior set to “Use Account Engagement” by default.
External Actions, which allow Account Engagement to send data to 3rd Party Applications, will now be available in Completion Actions. Now you can easily register a prospect for an event in a 3rd Party system upon form fill, or even send them a text as a completion action.
Account Engagement Optimizer is moving from Beta to Generally Available! Optimizer provides easy ways to clean up your Account Engagement org but pinpointing potential issues. With the move to Generally Available, Optimizer has a couple of additional metrics, including:
Configuration Issues: diagnose problems that are blocking access to features
Performance Improvement Measures: display good measures so you can see what is working well in the Business Unit
Prospect Change Monitor: understand which features result in the most prospect changes for your Business Unit
Salesforce is upping their game in the race to incorporate the latest generative AI tools into their products. Announced during Salesforce Connections on June 7, Marketing GPT and Commerce GPT are coming to Salesforce customers using Marketing Cloud and Commerce Cloud.
The features are gonna make it easier for marketers to reach the right audiences and generate emails, and commerce teams will create better shopping experiences and customer journeys. But, the best part is that both Marketing GPT and Commerce GPT can be connected to Data Cloud — meaning the tools can do their thing using data from any source.
History of Salesforce in the GPT game
Both Marketing GPT and Commerce GPT are dependent on Einstein GPT, which is the generative AI version of Einstein.
For a little back story, Salesforce Einstein is the machine learning model the company rolled out in 2016 to analyze large sets of CRM data. So, Salesforce has been on the AI train for a while already.
You can get it in Marketing Cloud Engagement and Account Engagement, Sales Cloud, Commerce Cloud, Experience Cloud, and Service Cloud, along with other platform tools.
So, how are Marketing GPT and Commerce GPT related to Einstein GPT?
Both Marketing GPT and Commerce GPT are powered by Einstein GPT — the AI-powered set of solutions that marries Salesforce AI with OpenAI’s technology. They are both iterations of Einstein GPT that are tailored for the respective clouds. Stay tuned because we’re seeing GPT features getting infused across all Salesforce clouds in addition to these two.
What capabilities do Marketing GPT and Commerce GPT have?
Both of the sets of features combine generative AI capabilities, which use data from OpenAI, with Salesforce Data Cloud. That means you can use customer profiles in Data Cloud that include data from any source in real time. And while you don’t have to use Data Cloud to take advantage of the Salesforce GPT features, you’ll definitely be able to do more if you have it.
So, what exactly can you do with Marketing GPT and Commerce GPT?
Marketing GPT Capabilities
We’re really gonna be cooking now by giving the people super valuable experiences through email and content marketing. We already have Einstein features in our marketing back pocket, but now we’re throwing GPT into the overall mix. That means we can use conversational language prompts to get Marketing Cloud to do things for us.
I mean, it’s not going to organize all those random newsletter graphics you’ve been uploading to Account Engagement without using a naming convention (yet???). But it will do things like analyze the data you have and use that information to predict the best ways to improve your emails.
Segment Creation | generally available Oct. 2023 This is a whole new fancy way to build your audience segmentation strategy. You can tell Marketing Cloud to create audience segments for you using natural language prompts, and it will help you to improve your targeting using AI recommendations and audience data that’s in Data Cloud.
Email Content Creation | generally available Feb. 2024 Ok, so I’m gonna have to see this one in action, but Salesforce said this feature can “reduce writing workload” by creating auto-generated emails. It can potentially be a big one for marketing teams that have the content but stumble with their email marketing.
Segment Intelligence for Data Cloud | generally available Oct. 2023 This adds a fancier twist for tracking ROI. Segment intelligence combines first-party audience data, revenue data, and paid media data to show you exactly how your campaigns are doing in relation to your audience segments.
Rapid Identity Resolution, Segmentation, and Engagement | generally available Aug. – Oct. 2023 Salesforce is going heavy on the ‘transform at the speed of your customer’ theme. The mouthful that is this feature basically keeps Data Cloud segments updated in real time so messaging is always relevant and timely.
Typeface content platform | GA date not given yet Using a third-party content generator called Typeface, marketers can create branded visual assets (like email graphics or social cards) inside Salesforce. Stay tuned for this one cuz it could be huge.
These are the features that Salesforce outlined during the announcement, but we’re sure the list will grow with each Salesforce release.
Commerce GPT Capabilities
We’re also getting a bunch of generative AI features for B2C companies that use Salesforce tools for commerce. These are especially cool because ecommerce customers can be a fickle bunch. Getting them exactly what they want when they want it makes all the difference.
Goals-Based Commerce | generally available Feb. 2024 This is one of those a-ha tools for businesses with big growth goals. It unites Data Cloud, Einstein, and Flow to lay out everything commerce companies need to do to reach their goals. Users give it a goal, like increase average order value (AOV) by XX%, and it gives recommendations on how to get there.
Dynamic Product Descriptions | generally available July 2023 Okay, so we’ve seen how serving up product recommendations based on customer preferences has shaken things up for commerce companies. But now we’re gonna be taking it even further by introducing dynamic copy capabilities for product descriptions. It could be a serious game changer.
Commerce Concierge | generally available Feb. 2024 Not all of the Commerce GPT features are specifically for Salesforce users. Online shoppers can use Commerce Concierge to find what they need using language prompts across channels from online stores to SMS messaging.
Comments on generative AI + Salesforce from the peanut gallery
My two cents: My mind immediately goes to the content creation features of Marketing GPT. There is SO MUCH copywriting that goes into marketing. And we’ve seen a whole bunch of copywriting GPT tools pop up in the last year, like the free Stensul email toolkit or paid ones like GrammarlyGo. Some people are naysaying the tools in fear that they will replace copywriting jobs, but I don’t think that’s the case at all.
In my experience, leaner marketing teams rarely have dedicated copywriters. Those responsibilities are usually lumped into other marcom roles. I see the tools giving marketers the ability to edit copy instead of writing from scratch. Then, they can have bandwidth to dig deeper with their messaging and present higher quality work that hits their audience in the feels. And being able to do that inside Salesforce just sweetens the whole deal.
I opened the floor to my teammates about what they think about Marketing GPT and Commerce GPT, and here’s what they had to say.
Cate Godley
“I’m excited to see how Marketing GPT can help marketers to craft better subject lines and calls to action to increase engagement with content. There are so many ways to use generative AI to inspire creativity in our marketing efforts, and I can’t wait to see how people are using these tools in new and exciting ways.”
Courtney Cerniglia
“As marketers, we’re constantly asked what content is resonating most with customers, what action will increase likelihood to purchase, and how we identify our highest value leads. Marketing GPT is going to help prove our assumptions and give us the data in real-time, across platforms, so we can quickly pivot and personalize experiences for customers.”
Mike Creuzer
“There have been a few inflection points where human knowledge growth hockey sticked. Gutenberg press took centuries, computers took decades, the internet took years, and this generative AI appears to be taking… months?
According to the 2023 Connections Keynote, there were 1 million users in two months for ChatGPT (if I remember correctly).
We are at the start of the next great change in pace of human knowledge and communication.
2023 is the year where AI is no longer hidden away behind RFID badged doors and is widely available to EVERYBODY in a usable, general way.
In business, AI has been baked into the tools that we use for many years now. But it’s been a one trick pony. It’s now anything WE want it to be, not just what our vendors built.”
Continue the conversation
What are your thoughts on Salesforce and generative AI? Any hot takes? Tell us about it in the comments, or reach out to team Sercante to see how the tools fit into your overall marketing and operations strategy.
Salesforce is introducing something pretty exciting for orgs that have little wiggle room while assigning licenses to Salesforce users. A new type of license called “Salesforce Integration User” is available now, and it’ll help you to save your user licenses for actual humans.
The Salesforce Integration User was introduced to facilitate best practices of using a separate license for any integrations that require an integration license to integrate with Salesforce. That includes integrations like Docusign and MuleSoft.
This license is specifically designed for System-to-System Integration types and provides the user with API Access Only.
How many Salesforce Integration User Licenses Do We Get?
All orgs will have 5 free Salesforce Integration User Licenses available to them, and additional licenses are available to purchase for about $10 each (customers should speak to their AEs regarding the purchase of additional licenses).
Salesforce Integration User License Setup
You can verify the number of integration user licenses available to you under Company Information > Setup.
In addition to the new licenses, a new standard profile called ‘Salesforce API Only System Integrations‘.
NOTE: When creating a new user with the Salesforce Integration User License, this will be the only profile available.
Creating a Custom Profile for the API Only System Integration User (System Permissions)
Since the new ‘Salesforce API Only System Integrations’ profile is a standard profile and therefore can’t be updated, it is recommended that you create a new profile by cloning the Salesforce API Only System Integrations (not System Administrator) for integration users in order to customize the permissions:
Go to Setup > Profiles
Locate the ‘Salesforce API Only System Integrations’ profile and click Clone.
In the Permission set, go to System Permissions
Enable the following permissions:
Password never expires – doing this prevents the password from expiring while someone is out of the office with no one available to update it across integrations
API Enabled
Api Only User
Chatter Internal User (optional)
(Still under System Permissions) Make sure ‘Multi-Factor Authentication Login Requirements for API Access’ is not enabled
Create a Custom Permission Set for the Integration (Object Access)
Go to Setup > (Quickfind) Permission Sets
Create a new permission set
Name your permission set to reflect the permission for this integration. For example “Integration – ZoomInfo”
Leave the License Type empty “–None–”
Add the following to the Object Settings for each object the integration needs access to:
In particular, keep in mind custom record types that are deployed by integrations’ own packages
Creating an Integration User
To use one of these licenses, it is recommended to:
Create a new user for each specific integration (if there is not a dedicated license already)
Assign the Salesforce Integration license (or you can change the license or if you already have a dedicated user for the integration)
Give the user the Salesforce Integration API permission set license.
Add the custom permission set you created above.
Validate
Once your user is set up:
Add the new integration user credentials in the integration platform (the steps may vary based on the integration)
Test the integration to confirm the integration is working the way it should.
For example, are records being updated as expected?
Considerations
The Salesforce Integration user license is API Access Only, meaning that it is not suitable for non System to System integration uses. Users with this license will not have access to the direct user login or access the org through the UI.
With the new licenses, it is still recommended to use one integration user per integration to ensure traceability of the transactions that the integration has within Salesforce.
If you are moving an existing user to the integration user license, the new ‘Salesforce API Only System Integrations’ profile, may not have all the object permissions needed. Any specific permissions needed may need to be assigned using permission sets.
Pardot API users are usually better met with the Identity User License, but if there are reasons to use this license (Oath2 Client Credentials) the Integration Connector User permission set is what will need to be applied to grant Pardot record access. Users using this license may not appear in User Sync until after you manually create and connect a Pardot user.
A custom permission set granting object and field access is preferred over doing this in the profile as permissions in profiles is scheduled to be sunset Spring of ’26.
In a move that extends beyond the chatbots used to formulate interview questions or write email subject lines, Salesforce is expanding automation capabilities by integrating Einstein GPT and Data Cloud with Salesforce Flow.
Bringing Einstein GPT and Data Cloud capabilities into Salesforce Flow means marketers can use the automations to create impressive real-time experiences for customers. And they’ll accomplish that using clicks rather than coding skills.
It’s something that will make the tools easily scalable for Salesforce customers at every growth stage.
How and when can Salesforce customers access it?
The announcement actually involves two initiatives Salesforce is launching. The first is a tighter integration between Salesforce Data Cloud and Flow. And the second is the integration of Einstein GPT and Flow.
According to John Kucera, senior vice president of product management at Salesforce, customers can use Flow currently with Salesforce database data. The integration updates between Data Cloud and Salesforce Flow are opening up the possibilities, and incorporating Einstein GPT is adding an efficiency edge to the technology.
Kucera said the Einstein GPT capabilities will be available on an early adopter basis in early fall as part of the Salesforce Winter ‘24 release. He went on to say that the Data Cloud integration will probably be offered as part of a standard Salesforce subscription, and Einstein GPT for Flow may carry an additional charge once those details are worked out.
Einstein GPT and Data Cloud Capabilities
Salesforce introduced Einstein GPT in March 2023 as the world’s first generative AI CRM technology, which infuses proprietary Salesforce AI models with generative AI models from OpenAI and other large AI models. And Data Cloud takes customer data from any source inside or outside the Salesforce platform and harmonizes it in real time.
So what in the world does that mean for marketers?
That means marketers can use information from Data Cloud to generate content and build workflows via Einstein GPT. Since Data Cloud reacts to data changes in real time, marketers can serve content that adapts dynamically and creates personalized experiences every time.
For example, a marketer could use Einstein GPT to generate an email with dynamic content blocks that update in real time when a Data Cloud field updates based on customer activity.
John Kucera said to SiliconANGLE, “You can give it a prompt such as ‘I want to create a guided workflow for a new customer or create a rule to follow up with an email to customers who haven’t responded in five days.”
Infusing Einstein GPT and Data Cloud with Salesforce Flow
The new integrations are going to turn things up a notch for marketers. Here’s what happens when we incorporate Salesforce Flow into the Einstein GPT and Data Cloud mix.
What is Salesforce Flow?
Salesforce Flow is a declarative automation tool. It allows you to create complex automations inside the platform using clicks rather than code, so users can get in there without the need for developer skills.
Marketers use Salesforce Flow for things like managing campaign activations, automating customer onboarding steps, or creating a custom task series for sales teams.
How can marketers use Salesforce Flow with Einstein GPT and Data Cloud?
Using the Einstein GPT and Data Cloud integration alongside Salesforce Flow is changing the game for marketers who use the platform. That’s because marketers will be able to use conversational chatbots to automate complex workflows and trigger actions in real time.
Users and admins can describe the type of flow they want to build, and then they’ll sit back and watch the chatbot complete the tasks. Or, it can be used to build formulas or search for functions. It removes much of the manual and tedious work that goes into creating complex flows and automations.
For example, a field in Marketing Cloud Engagement detects that a customer added items to their shopping cart, but they left the page without completing the purchase. That triggers an immediate email notification, created via generative AI, that goes to the customer and offers a discount code for them to complete the purchase.
In summary, the three benefits to marketers include:
Reduced flow build time
Access to more options to automate with flow
Improved real-time personalization for customer interactions
Get ready for generative AI inside your Salesforce org
We’re on the edge of our seats with anticipation for combining Einstein GPT with Salesforce Flow and Data Cloud capabilities.
These technologies make us feel like we have a front row to the future of CRM and marketing automation. So, in the meantime, we’ll be thinking about all the ways we can use conversational AI to do all the things us busy marketers do.
Have any aha use cases you’d like to share? How do you think Einstein GPT, Data Cloud, and Flow are going to work together in your org? Let us know in the comments!
You can also drop us a line if you’re wondering how you can incorporate these tools into your marketing operations strategy.
Those of you who have been followers of The Spot for a few years now know that we have shared our favorite Marketing Cloud Account Engagement (Pardot) Ideas from the Salesforce IdeaExchange either in blog posts or the Pardashians Slack group.
This tradition started in 2017 with Andrea’s initial post highlighting 8 ideas on the IdeaExchange that Pardot admins should upvote. We’ve seen great features come to life in the most recent Salesforce releases (looking at Conditional Options for Completion Actions), and we’re hoping you can help prioritize ideas for future releases.
Salesforce has three releases throughout the year and uses their IdeaExchange to help drive which features are prioritized in future releases. As a marketer, you have most likely entered a situation where your team is requesting a solution that is currently not available in Marketing Cloud Engagement or Marketing Cloud Account Engagement as a feature.
Your first stop is to see if this feature/solution has been mentioned or resolved via the IdeaExchange. Checking there first is going to help you understand how others have solved it, and then you can add in your own vote to the idea.
What is the Salesforce IdeaExchange anyway?
Back in 2006, the Salesforce #Ideaexchange was born as a way to involve its customers (big and small) in a modern effort to crowdsource ideas for its product roadmap. This ensures the community gets a platform to contribute their ideas and wishes — you know, a place where the margods can go for inspiration if you will as they build the world of tomorrow.
How does one enter their idea into the Salesforce IdeaExchange?
Come up with an idea and submit it to the exchange
You then get trapped and spend 2-4 hours going through other people’s ideas (definitely optional, but highly encouraged).
If your idea gets enough votes (10+ points for you) then a product manager gets involved
The idea is developed and then delivered, and we all cheer!
As Salesforce continues to work on improving their marketing automation platforms, our team has put together a list of ideas that we recommend you upvoting and adding to your wish list in hopes of getting them added to the top of the prioritization list.
Here is our current list of Salesforce IdeaExchange items that marketers should check out and upvote.
Salesforce
Ability to Customize Campaign Member Status Values for all Campaigns
Track and Record Direct Replies to an Email Sent from Marketing Cloud Account Engagement
This feature would provide an additional, much needed KPI for marketers to be able to determine which CTAs are working for their emails that do not go directly to links or forms.
Allow or Operational Email Sending in Engagement Programs
This feature would bring the operational email checkbox to the entire Engagement Program or individual Email steps to ensure those who need to receive these emails still are even when in an Engagement Program.
Audit changes to Marketing Cloud Account Engagement Assets
This feature would bring a tool similar to what Salesforce Admins have available to them to be able to view all changes made to lists and assets throughout Marketing Cloud Account Engagement.
This feature would bring forth a notification system for your team to understand when there are Connector errors between Salesforce and Marketing Cloud Account Engagement.
This feature needs no explanation as many people are hoping we can reverse the name rebrand and move back to calling the tool “Pardot” at some point in the future.
While some Pardot admin recommendations get picked up and implemented faster than others, it all depends on community participation and perceived need from the Marketing Cloud product team. In fact, to help drive ideas, Salesforce created a prioritization system where you can see top feature suggestions across the ecosystem battle it out!
Are there any features or functionality you wish you could see? If so, let us know below. With a little bit of luck and support from your Salesforce Ohana, you might also uncover the secrets of the IdeaExchange and get your idea on the scoreboard.Don’t forget to vote for these ideas, submit your own and chat with us on Twitter, LinkedIn or simply subscribe to the blog.
Salesforce Marketing Cloud Personalization (Interaction Studio) is a fantastic platform to add to your marketing toolset. But starting a Marketing Cloud implementation can be daunting, especially when it is as complex as Personalization.
The following sections of this article will detail the implementation approaches available, provide indicative timelines and outline example use cases. However, if you’re wanting to understand a little more about what the tool can offer, you can check out my last article – Salesforce Marketing Cloud Personalization (Interaction Studio): A Beginner’s Guide.
SFMC Personalization Implementation Methods
With any platform like SFMC Personalization, which promises Real-Time Personalization and AI Recommendations, it’s easy to get carried away with what it can offer. However, the key takeaway from this article is that you should focus on what you and your company can achieve, which is particularly important given the tricky interdependencies you’ll face when implementing Personalization.
In a nutshell, the approaches vary from minimal viable product (MVP), where the goal is to implement a baseline as quickly as possible and then build upon it in future iterations, all the way to future-state implementation (FSI), where you depend on use cases to drive large-scale transformation. There is also a halfway house approach of implementing an As-Is, for those who may sit between the two methods above.
These helpful questions allow you to ascertain which method will best suit your needs, including:
How often does your company change its website?
Do you have easy access to developer resources?
Are you migrating from an existing tool?
Do other platforms need to be integrated?
What you’ll find is:
MVP is great for companies making constant changes to their website, have easy access to developers, and are not migrating from an existing personalization platform. In other words, it’s a viable method for those who are perhaps new to real-time personalization.
As-Is is great for companies that don’t have immediate access to developers, are looking to migrate from one tool to another and have a few live personalization campaigns ready to migrate.
FSI is the preferred option for companies that less frequently change their website, have limited access to developers, are looking to integrate Personalization with multiple clouds (Marketing, Sales or Service), and have external data sources that need to be integrated.
Obviously, the implementation roadmap will vary depending on the scope of your project and the implementation approach you’ve decided to use. However, there are some key milestones that will occur in all implementations, as shown in the diagram below, which is based on a typical net-new Personalization implementation with 2-3 use cases.
Roadmap Diagram
From the diagram above, the two key milestones I’d pay the most attention to are the Use Case Discovery and the Blueprint Development.
Regardless of the implementation method, defining a handful of clear and precise use cases before beginning the build is key to ensuring success. As mentioned, it’s easy to get caught up with the wide range of functionality Personalization offers. That’s why understanding the desired outcome is the most effective way of running a successful implementation and ensuring your company gets the most out of the platform. I’ll go on to share a few examples of good use cases later on.
The blueprint document goes hand-in-hand with the sitemap — which is debatably the most crucial part of Personalization. The blueprint helps define which page categories exist, which triggers exist on those pages, what data can be scraped and where it can be scraped from (i.e. DOM vs Data-Layer) for each visit.
Thankfully, to aid with your implementation, the Salesforce Partner Portal can provide a useful template that helps capture all of the information necessary to create your sitemap, and for implementing Personalization. The template covers everything from page types and content zones to events and attributes, and most importantly, where they can be found on your website to make it easier for the developers building the sitemap.
Use Cases
Without sounding like a broken record, use cases can make or break a Personalization implementation. During my first implementation of Personalization, the goal I was given was to deliver Real-Time Web Personalization aka Personalization.
There were no clear KPIs, the website was static and there was nothing to encourage returning visitors, and it made any experiences based on previous visits practically void. The end result was that our very expensive personalization engine sat on the shelf until we revisited the drawing board.
Defining Your Use Cases
In order to avoid making my mistake, don’t be afraid to get granular with your use cases. Once established, it’s easier to build on top of existing use cases with future iterations. So really think about the following aspects when defining your use cases:
Objective – What is it you’re trying to achieve with your personalization? Is it to increase the value per order? Or perhaps to encourage more users to download your app?
KPIs – How are you going to measure the success of your personalization? Is it based on the number of successful completions? What percentage increase in order value would be considered successful?
Approach – Once you know what you’re trying to achieve, you then need to consider the approach. Is it based on visitors from a particular source (Rule-Based) or is it based on trending products (Recipe-based)?
Measurement Approach – There’s no point in creating a personalized experience if there is no control to measure success. Consider what an adequate sample might look like and how long the campaign might last.
Channels – Is this going to be a web- or mobile-led campaign?
There’s no right or wrong answer for use cases and it completely depends on your company’s objectives. But for a typical net-new implementation, 2-3 concise use cases similar to the ones below is a good starting point.
Use Case Definition Example
Use Case
Approach
Channels
KPI
Measurement Approach
Encourage users to complete the onboarding application
Rules Based
Web, Email
No. clicks on CTA, no. applications started, no. applications completed
50% personalized, 50% control
Encourage mobile app downloads
Rules Based
Web, Mobile App, Email
No. clicks on CTA, no. app downloads
50% personalized, 50% control
Once you’ve defined your use cases, keep referring back to them throughout the implementation and when developing your blueprint. The use cases will help keep your implementation focused on the end goal, and help your developers build a sitemap that will be fit for purpose.
Planning is Key to a Successful SFMC Personalization Implementation
As you’ve probably gathered by now, successfully implementing Personalization is closely linked with planning. Defining clear and concise use cases as well as developing an accurate and detailed blueprint, both of which are milestones during the Discovery Phase, are imperative for a smooth implementation. This is true regardless of your chosen implementation method.
As final food for thought, don’t forget to consider your implementation team. Being the tool that it is, Personalization implementations often begin in the marketing department as it’s the marketers who want real-time personalization capabilities. However, even large marketing teams with wide-ranging skill sets will not be able to deliver Personalization alone.
The Personalization Sitemap will require JavaScript developers. Building ETLs will require support from data architects. CRM integration will require CRM administrators. And creating experiences, although there are ready-made templates, may also require HTML and CSS experts. So, consider including wider teams early on in the implementation.
Not only will this help to ensure that those resources are available to support and understand the ask, but it may also help to define use cases that are more relevant and that are also technically viable.
Need help filling the gaps on your team through your Salesforce Marketing Cloud Personalization implementation? Reach out to team Sercante to get their experts on the case.
