Pro Tips Archives - Page 4 of 45

Data Management, Marketing Automations, Pro Tips
July 29, 2025

Using Agentforce, Data Cloud, and Marketing Cloud Advanced to Improve Student Retention

Angelica Cabral

Student retention is one of the most pressing challenges in higher education—and it’s not just about keeping enrollment numbers up. It’s about making sure students feel supported, connected, and confident in their ability to succeed, and engaging them before it’s too late.

Almost a quarter, 22.3%, of first-time, full-time undergraduate freshmen drop out within the first 12 months, while 39% don’t complete their degree within eight years (Education Data Initiative).

Which is why it is imperative for institutions to be taking action to improve student retention. One of the ways they can is by maximizing the technology they have and tapping into the latest solutions available to gain a better view of their students’ journeys and take action to engage when it matters most.

In Sercante’s latest demo, we explored how Salesforce’s connected tech stack—featuring Data Cloud, Marketing Cloud Advanced, and Agentforce can empower institutions to identify and support at-risk students before they fall through the cracks.

In the demo, we followed the journey of Jason Smith, a sophomore whose profile revealed a 77% attrition risk. What followed is a case study in how smarter tech, working harder behind the scenes, can drive real results for both teams and students.

Unifying Student Data for Smarter Insights

Everything begins with data. Using Salesforce Data Cloud, we created a Unified Student Profile by integrating key data sources across systems: academic performance, course engagement, attendance patterns, and more.

This holistic view powered a propensity model that flagged Jason’s risk level at 77%. Instead of relying on gut instinct or outdated reports, the team now had real-time, actionable insight—and a clear signal that it was time to act.

From Insight to Action with Marketing Cloud Advanced

That’s where Marketing Cloud Advanced comes in. Once a student is identified as at-risk, every minute matters. This tool enabled us to build automated, personalized communication journeys, so students like Jason could receive the right message at the right time.

Jason’s message came from Sercante University: a friendly, timely nudge to connect with an advisor. And because it was based on real-time data from his unified profile, it felt relevant, not random.

A Seamless Path to Support with Agentforce

The magic moment? When Jason clicked the link and landed on a scheduling page powered by Agentforce.

Here’s where tech meets empathy. Agentforce’s AI assistant recognized Jason’s concerns about unavailable classes and provided instant, personalized guidance—helping him book an appointment with an advisor in just three clicks or less.

No back-and-forth emails. No waiting. No frustration. Just a frictionless experience that made Jason feel seen, supported, and empowered to move forward.

A Multi-Cloud Solution that Improves Student Retention

What made this work wasn’t just the data or automation—it was how these tools worked together to create a better experience for both students and staff.

For teams: The heavy lifting was handled behind the scenes. With Data Cloud pulling real-time insights, MC Advanced automating outreach, and Agentforce handling the scheduling, advisors could spend less time triaging and more time supporting.
For students: It felt easy, human, and personalized. Jason didn’t need to fight for support—it found him, right when he needed it. He got help fast, with minimal effort and instant gratification.

This Agentforce, Data Cloud, and Marketing Cloud Advanced, multi-cloud solution, is an example of when teams use the power of data and AI to engage their students when it matters most, before it’s too late. Intercepting more students like Jason can help institutions improve student retention while creating real connections that last to drive growth for the institution and in Jason’s educational journey.

Final Takeaway

When schools bring together data, automation, and AI, they unlock a more connected, proactive, and student-centered approach to retention.

Students feel seen, supported, and confident in what to do next
Teams get relief from manual processes and can focus on what matters most
Institutions see better outcomes—without burning out their staff

It’s not just about reducing attrition—it’s about building trust, creating moments that matter, and delivering an experience that helps every student thrive.

Want to see the full journey? Watch the demo here.

Looking to implement something similar at your institution? Reach out to the Sercante team.

Getting Started, Pro Tips, Technology
July 25, 2025

How to Overcome the 6 Biggest Obstacles to AI Adoption

Angelica Cabral

AI has the potential to fundamentally change the way we work—not just in theory, but in the day-to-day rhythms of marketing, sales ops, RevOps, and customer experience teams. At its best, AI can help us scale what works, automate what drains us, and create seamless customer journeys that feel personal, not robotic.

Every organization wants to implement AI, because they know the value, but teams are navigating real challenges: unclear use cases, disconnected data, limited internal expertise, and a natural hesitation that comes with change.

A recent Gartner survey found that 77% of executives believe AI will give them a competitive edge—but only 44%, meaning less than half, feel confident in their roadmap to get there.

To help teams navigate AI adoption, the experts at Sercante put together an AI Starter Kit filled with demos, real-life examples, expert recommendations, and insightful how-tos for overcoming the most common AI adoption obstacles, which is what inspired this article.

Here are the six most common AI adoption roadblocks the team has seen firsthand—and some practical, no-nonsense ways to work through them.

Obstacle #1 Data silos are stalling progress

You might be feeling this if…

Your team is using multiple tools that don’t talk to each other, reporting feels unreliable and takes forever, and you’re not quite sure where all your customer data even lives.

How to move forward:

AI can’t do its job if it doesn’t have access to clean, connected data. Start with a simple audit: where is your data, and who owns each piece? From there, focus on one high-impact use case and use integration tools (like a customer data platform or middleware) to bring data together. Keep it focused—you don’t have to solve the whole thing in one go.

Obstacle #2 Lack of trust in accurate results

You might be feeling this if…

There’s skepticism around AI recommendations, hesitation to take action on outputs, or concerns about compliance, bias, or lack of transparency.

How to move forward:

This isn’t just about proving that AI “works”—it’s about making people feel safe using it. Prioritize tools that show their work (think explainable outputs). Run small pilots to validate results and let the data do the convincing. Also appoint internal champions who can model responsible, thoughtful AI use.

If you’re just getting started, this article offers helpful grounding: 7 tips for how to get started with AI.

Obstacle #3 Skill gaps

You might be feeling this if…
AI feels too technical or intimidating for the team, and you’re relying on one or two people to drive all the innovation.

How to move forward:
You don’t need a team of data scientists to start using AI. Launch basic AI literacy training by role—what should a CX leader know about AI vs. someone in RevOps? Create safe spaces for learning and experimentation. And if there are areas where you need deeper expertise, don’t be afraid to lean on partners while your team ramps up.

Obstacle #4 No clear use cases

You might be feeling this if…

Your team has a shiny new AI tool, but no one knows what it’s for—or conversations are stuck at the “someday” level. Or conversations around AI remain at the hypothetical level, but no one is actually taking the plunge to use it daily and point to how it is helping them scale and be more efficient.

How to move forward:

Bring AI down to earth. Host simple workshops by function and explore high-impact, low-effort use cases: AI-generated email copy or campaign briefs, summarization, agentic lead qualification and routing, FAQ case deflection through knowledge article references. Document small wins and share them internally—that success story from the marketing team might inspire the sales org to try something next.

Obstacle #5 Resistance to change

You might be feeling this if…

There’s pushback from users or leaders who feel uneasy, or concerns that AI might replace jobs or change the nature of their work. Or you’re hearing team members say “But we’ve always done it this way.”

How to move forward:

There’s no way around it, change will always evoke emotions—discomfort, worry, anger, excitement—you get it. However, how we choose to respond is what is in our control, and we can either choose to keep our shields up with AI or we can see it as an opportunity to innovate, scale what we do best, and create even better experiences for customers.

For conversations with your team, consider reframing AI as a co-pilot that takes on the repetitive tasks, not a replacement for human expertise. Involve employees early and let them help shape how AI gets used. Highlight wins that make daily work easier and more efficient.

Obstacle #6 ROI concerns

You might be feeling this if…

Budget holders want to see results before approving spend, or it’s unclear how success will even be measured.

How to move forward:

In the beginning, when you’re identifying use cases, consider the metrics that will be used for each one to evaluate success and tie these to clear business outcomes.

Lauren Noonan, VP of Growth and Alliances at Sercante, quote: "What are you doing to do with the time you get back from using AI, and how will it impact the organization?"

In the beginning, it may be as small as time saved during campaign building, but when you multiply that time saved over the course of the year, and the amount of team members it affects, that will add up to big results. Then, as Sercante VP of Growth & Alliances, Lauren Noonan, shared on the Connections Recap session, answer the bigger question, “What are you going to do with the time you get back and how will it impact the organization?” When you answer that question, it will show leadership the existing gap between where you are now and the level of growth that could be reached if your team was using AI.

When you’re building your AI roadmap, include the expected short-term wins that will come with your initial low-level of effort use cases and the long-term goals the team is after to give your team a big picture that everyone can align on.

Overcoming to get started with AI

The road to AI adoption isn’t about flipping a switch. It’s about taking deliberate, doable steps—ones that meet your team where they are and build toward where you want to go.

Start by acknowledging what obstacles you and your organization align with the most and then work through the steps above to start to overcome. And if you’d like a third-party expert’s insight, the Sercante team can help. We’ve partnered with dozens of teams to move past the blockers and build AI strategies that actually work in the real world, and have guided them on the path toward driving growth with AI at their organization.

Getting Started, Industry News, Pro Tips, Real Talk, Technology
July 23, 2025

7 Tips for How to Get Started with AI

Christina Anderson

It’s not a secret, so many growth teams, marketing, sales, and customer success, want to be using AI to streamline processes and elevate customer experiences, but when it comes to adoption, they’re a little stuck on how to get started with AI.

After hearing a few of the experts at Sercante share their insights and having conversations with marketing leaders who have taken the plunge on applying AI to their initiatives, plus some first-hand experience with our own marketing, I was able to create this collection of tips for how to get started with AI.

For those thinking, TLDR, let’s cut to the chase, I recommend downloading Sercante’s AI Starter Kit.

Tip 1: Pinpoint the pain

After attending a Connections 2025 Recap Webinar, Sercante’s Salesforce Product Director, Heather Rinke, advised the audience to get started with AI by writing down the biggest pain points they have today.

What is a manual, repetitive, and mundane task, sucking up your bandwidth?

Then consider, of those pain points, which is the lowest barrier to entry? What might have dependencies that might need a little more technology configuration, data setup, or the involvement of multiple departments?

Focus on the low lift, but quick-win initiatives first. Often, this would be an internal process that you could see how it performs, measure impact, and then scale from there.

[Watch On-Demand 2025 Connections Recap]

Tip 2: Do your research

As Laura Curtis, Senior CRM & Marketing Automation Strategist at Sercante said on the Connections Recap, “You don’t know what you don’t know.”

In fact, 71.7% of non-adopters say “lack of understanding” is their biggest barrier to AI adoption (Influencer Marketing Hub AI in Marketing Benchmark Report). So if you’re feeling overwhelmed, you’re not alone. But it’s also fixable.

One way to start doing your research: Download the Sercante AI Starter Kit. It’s full of:

Real use case examples
Tips you can steal
Customer stories
Common pitfalls to avoid

Also, check out Rinke’s article, Five Tips for Getting Started with Agentforce.

Tip 3: Try out-of-the-box tools first

Don’t build the Death Star on day one.

There’s zero need to spin up a complex custom solution to get started. Many platforms—especially Salesforce Agentforce—already have out-of-the-box agents and AI functionality you can activate right now.

Use them.

Start small. Test how it works. See how it helps. Then decide if you want to scale or customize.

Tip 4: Get your data house in order (but don’t wait for perfect)

As Sercante VP of Growth & Alliances, Lauren Noonan, shared on the Connections Recap, “Very few people buy a home and it’s perfect.”

You can start with AI even if your data isn’t a 10/10. But the better your data hygiene, the better your AI output.

Start by asking:

What data is critical for our first use case?
Where does it live?
What’s messy that could block us?

Then clean it as you go. Consider what other data optimizations you can make along the way to support the future AI initiatives on your roadmap. Like updating the kitchen before you renovate the whole house, and then mapping out what renovations make sense to do next.

Tip 5: Measure what matters

But what metrics are worth tracking to measure the impact of AI?

It depends on your use case, but as an example, Noonan shared the idea of using AI to generate a campaign brief instead doing it manually.

How long does it take you to do it manually versus using AI?

Before getting started with using AI internally, get benchmarks for how long it typically takes your team do the processes you’ll be using AI for and then measure how long it takes after.

Now, the bigger question that Noonan posed is “What are you going to do with the time you get back and how will it impact the organization?”

If you’re trying to champion AI in your organization and get your leaders on board to support the initiative, answering questions like these can be a huge part of the business case—other than the increased efficiency, maximized output, and better customer experiences that’ll lead to growth.

Tip 6: Taking a crawl, walk, run approach to AI

As the CMO of Mogli, Christina Scarmeas, shared on my recent conversation with her on the Innovator Series about her team’s approach to using AI and Agentforce:

“One of the biggest things we learned was, it’s okay to slow down and take a crawl, walk, run, approach to AI. Take a step back, look at the infrastructure that we need to deploy, and what we’re trying to do with these agents. Be okay with having a phased approach with expectations of how it’s going to be implemented, and if you put that infrastructure together and have a team that is dedicated to the strategy behind it, the results come fast.”

[Watch the Innovator Series]

This aligns with Rinke’s advice of starting with an initiative that is low-barrier-to-entry, perhaps something internal where you can point to productivity gains.

A customer in the healthcare industry’s story of getting started with AI

For example, one of Sercante’s customers in the healthcare industry serving multiple practices implemented Service Agents with Salesforce Agentforce.

The Service Agents were set up to help the human agents query knowledge faster to support them in their calls to better serve patients and providers.

The solution has been rolled out to one practice area first, so the team can continue to learn and adapt the solution as needed before scaling to their other practice areas.

This is a great instance of a team starting small, with rolling out an AI-powered solution in one area of their business to then evaluate and see how it can be applied to the other areas of their business..

Tip 7: Build your AI roadmap

Once you’ve dipped your toe in, it’s time to zoom out.

As the Director of Marketing at Mogli, Evan Thomas shared on the Innovator Series:

“AI is the next evolution of technology and like all the tools that came before it, you have to have a plan. Just getting AI into your org isn’t going to fix it. You have to have a plan for that AI. What is it going to do for you? What is the process it is going to supplement or help your team focus on? What is the reason you’re doing it?”

Creating your AI Roadmap for quick wins and long-term success

Therefore, the next step is creating your plan or your AI roadmap. Identifying your pain points and use cases is the first step of this. The other piece of this is evaluating the customer lifecycle through the lens of the customer and identifying points of friction that could benefit from a solution to help your team scale and make the engagement seamless. However, as this can be overwhelming for teams to do, experts have started collaborating to put together resources for this.

Sercante’s session, AI Roadmap: The Strategy for Driving Growth with AI, is a great resource that includes insights from experts on how to approach creating a plan that:

identifies high-impact use cases
considers dependencies and how to address roadblocks
outlines key metrics to track for measuring success
clearly defines your path for quick wins and long-term success

Take advantage of training opportunities for creating your AI plan

Another option for getting started with creating your AI Roadmap is to get training. According to SurveyMonkey, 70% of employers don’t provide training on AI, even though 70% of marketers say it’s essential. Therefore, any time you can get training and advance your skills on how to approach AI or how to use it, take advantage!

One training offered is Sercante’s AI Workshop: Building your roadmap for real impact. This is the deep dive where the experts will guide you through creating your 30-60-90 day plan to help your organization get started with AI and scale for the future.

One last thing: Pick yourself in this era

CEO of Sercante, Andrea Tarrell, shared this sentiment during her opening keynote at MarDreamin’ Summit, encouraging the community to take action asking, “If not you, then who?”

This technology is at our fingertips, and it’s up to us to decide how we’re going to use it to streamline processes, meet customers where they are at scale, and create a truly seamless experience.

It’s time to get started with AI.

Data Management, Pro Tips
July 11, 2025

3 Tips for Optimizing Your Data Cloud Credit Usage

Mike Morris

Product Note: Marketing Cloud Growth and Advanced are editions of Marketing Cloud Next and have also been referred to as Agentforce Marketing.

Marketing Cloud Growth/Advanced (aka Next Gen Marketing Cloud) is built to leverage the power of Data Cloud, giving marketers key benefits like unified customer profiles, enhanced segmentation, cross-object personalization, and calculated insights. However, these capabilities come with a cost in the form of Data Cloud credit consumption. In this post, we’ll review several tips to help you maximize the benefits of Data Cloud without breaking the bank.

Introduction to Data Cloud Credits

Before we start talking about conserving credits, let’s take a look at what they are and what actions use them.

What Are Data Cloud Credits?

Salesforce defines Data Cloud Credits as “digital currency that you use to pay for Data Cloud services.” These credits are consumption-based, meaning you only pay for what you use. Use a little, pay a little. Use a lot, pay a lot.

Credit use is calculated by multiplying the number of units consumed for each usage type by the corresponding multiplier from the rate card. Usage types include Data Services, Data Storage, Einstein Requests, and Segment Activations. Usage can be monitored in the Digital Wallet included in your Salesforce org.

The key takeaway is that credits are a valuable resource, and every action comes with a related cost. The goal is not to scare marketers or discourage credit usage. It’s to encourage smart, intentional use to ensure that each credit delivers value.

Here are some great resources if you would like to learn more about these topics.

Tips for Optimizing Your Data Cloud Credit Usage

Tip #1 – Apply Filters to Data Streams

Identity resolution rules are one of the largest consumers of Data Cloud credits. They use Data Service credits to create the unified individual records required for Marketing Cloud Growth/Advanced. This process is essential and must be activated. But it can be optimized.

Save Credits with Filters

Identity resolution rules link data from multiple data sources into unified individual records. Credit consumption is based on the total number of records that Data Cloud reviews when unifying the records. Credits can be conserved by applying filters to the data streams to limit the number of records being used in the identity resolution process.

Example:

If your lead data stream contains 1M records and your contact data stream includes 500K records, 1.5M records will be used in the creation of the unified individual records. Data filters can be applied to limit the number of records used in the identity resolution process by focusing on only records that should be included in your marketing activities.

Applying Data Filters

Data filters can be applied in two ways:

When Ingesting: By adding a filter to the data streams
After Ingestion: By applying a filter to the data lake object (DLO) in the data space (Marketing Cloud uses the default data space)

The filters will impact the system processes like unification, segmentation, and CI, but will not impact the total number in the data stream.

Example:
There are 6,088 total records in the lead data stream (and let’s say that 2,500 are from the USA). If you apply a filter for Country = USA, the total record count in the data stream stays the same (6,088), but only the 2,500 records from the USA will be used in system processes (including identity resolution). This reduces the data being evaluated to only leads in the USA and will reduce credit consumption.

A screenshot of recently viewed data streams in Data Cloud.

A screenshot in Data Cloud showing how to edit the filter in a data stream to only include records whose country equals USA.

The great thing about filters is that they help save credits across multiple areas. They reduce credit usage in identity resolution and also limit the number of records evaluated in processes like segmentation and calculated insights. This saves you even more.

Tip #2 – Audit Refresh Schedules

Credits are consumed when data is refreshed in Data Cloud. This includes data streams, data graphs, calculated insights, identity resolution rules, and segments.

Data Streams
Data streams based on Salesforce data refresh every 15 minutes by default and upsert with new or changed records. Manual updates can also be triggered if needed. Data ingested from other sources can be scheduled to run hourly or daily, so it’s worth taking a look at their schedules.

If you find the data is being refreshed hourly, consider the frequency that the data is actually updating (in the data source being ingested) and the “freshness” that’s needed in your marketing activities. Hourly refreshes make sense for data that changes frequently and is used in time-sensitive communications. In other cases, daily refreshes might meet your business needs and they would save credits.

Data Graphs
Data graphs are used for personalization and dynamic content, and refresh daily by default. The refresh interval can be updated by navigating to the data graph in Data Cloud and selecting the “Schedule” option from the dropdown (under the ▼icon).

More frequent refresh intervals mean “fresher” data, but will use more credits. I recommend sticking with the daily refresh option and adjusting based on your needs. Remember, manual refreshes can also be triggered if needed.

A screenshot of the Refresh Interval drop down setting to set your Data Graph's refresh schedule.

Identity Resolution
Identity Resolution rules run daily and the schedule can’t be changed. The rules will run once every 24 hours and the time of day might vary based on your org and the amount of data being processed. Manual refreshes can be triggered by navigating to the rule and clicking the “Run Ruleset” button.

The only real optimization for identity resolution is limiting the number of records processed (by applying filters) as discussed in the first tip.

Segments
Segment refresh schedules are the primary way that marketing teams can reduce Data Cloud credit consumption. When creating a segment, the Standard Publish option offers the following refresh schedules:

Don’t refresh
12 hours
24 hours

I recommend choosing “Don’t refresh” unless there’s a defined need to refresh more frequently. This ensures segments aren’t needlessly refreshing—and burning credits unnecessarily.

Make sure your segments are still up to date before sending emails by selecting the “Immediately before running this flow” refresh option in your segment-triggered flow. This guarantees your email targets the most current segment population, without incurring extra credit usage from scheduled refreshes.

A screenshot showing toggling on "Immediately before running this flow" for the setting for "When do you want to republish this segment?"

Tip #3 – Be Selective

Data storage is another factor to consider when evaluating credit consumption. When ingesting data into Data Cloud, start with a minimalist mindset. Ask yourself the following questions when deciding which fields to include:

Is this field needed for identity resolution?
Is this field needed to support marketing efforts (ex. dynamic content, personalization, segmentation)?
Is this field used in calculated insights?

If the answer to these questions is “no,” hold off on ingesting the field to reduce unnecessary data storage. If a new use case arises later, the field can always be added to the data stream.

How to add a field to an existing data stream

Confirm the Data Cloud Salesforce Connector has read access to the field.
- Permission Sets > Data Cloud Salesforce Connector > Object Settings
  - Navigate to the object that contains the field and verify the “Read Access” box is checked
In Data Cloud, select the Data Streams tab and the data stream related to the object where the field is located.
Click the “Add Source Fields” button from the selected data stream.
Select the field (or fields) from the table and save.
Click the “Review” button in the Data Mapping section and map the fields from the data lake object to the data model object (you might need to create new custom fields).

Make the Most of Your Credits

Data Cloud credits are a valuable resource and should be managed accordingly. With a little bit of planning and some regular audits, you can make the most of your credits and take full advantage of the AI, calculated insights, personalization, and segmentation capabilities of Marketing Cloud Growth/Advanced.

If you have questions about Data Cloud or Marketing Cloud Growth/Advanced reach out to the Sercante team or leave us a comment.

Events, Pro Tips
July 10, 2025

Design Meets Agentforce: A Designer’s POV from the World Tour

Daniela Donato

I just got back from the Agentforce World Tour in Boston and my brain is full of ideas. I wasn’t totally sure what to expect, but I ended up walking away with a lot of thoughts on how this new wave of Salesforce tools is going to affect the way we design—and honestly, it’s already starting.

Here’s what stood out to me, what’s changing in marketing design, and what I think we need to start doing differently.

What Salesforce tech I learned about—and why designers should care

A picture of a slide from Agentforce World Tour that says Agents are the new primary UI...navigating apps is now a thing of the past and CX will never be static again.

The big thing right now is Agents. These are digital agents built into Salesforce that help you build campaigns, write copy, pass tasks between teams, and do all the repetitive stuff we usually get stuck with.

Here’s what stuck with me:

A Marketing Agent that helps write emails, build landing page briefs, and generate campaign ideas
Agents that pass work from marketing to sales to success without everything falling apart
A combo of Einstein and Data Cloud that makes personalization actually doable—not just a buzzword

The whole point is: this tech works in the background, which means the assets we make (emails, landing pages, chat flows) need to be flexible and fast to keep up. If the backend is getting smarter, the frontend has to match.

Why designers should be paying attention:

With marketers using agents to streamline content and campaign creation, we need to make sure that the designs on the frontend are just as easy to be flexible and scale. How can you templatize designs so they can be used for multiple variations and make assets a rinse and repeat process, so that marketing can continue to flow seamlessly to engage customers where they are?
As AI functionality + Data Cloud is making it easier to tailor campaigns on a 1:1 level, designers need to prep for modular, dynamic design solutions that can easily adapt to be used in tandem with these personalized experiences.

How design can make bots, emails, and landing pages better

A picture of a slide from Agentforce World Tour showing a web page from Fisher & Paykel.

A lot of chatbot flows feel like someone gave up halfway through. This tech is finally making them better, and as designers, we should be helping that along.

Things that stood out:

Keep bot messages short. Break things up.
Add little visual moments such as spacing, structure, and simple hierarchy

Same goes for emails and landing pages. If AI is helping create content, our layouts should be:

Modular and adaptable. Not every headline is going to be the same length
Built with personalization blocks in mind
Designed to include stuff like product recs, timers, or variations depending on the audience

It’s less about making something perfect once, and more about making something that works in a bunch of different ways.

Marketing tracking and data = smarter creative decisions

A picture of a slide from Agentforce World Tour showing dynamic blocks being used to personalize the email for recipients in two different locations, one in Boston and one in Brooklyn

I used to skip over the data talk. But now that I see how it connects to the creative side, I’m paying more attention.

Salesforce showed how live audience data helps trigger different campaign paths. And if we know who we’re designing for, we can make better choices.

Things I’m going to start doing:

Ask who we’re designing for before opening Figma
Build layouts that make A/B testing easy
Stop hanging onto designs that don’t perform, even if they look good

Key takeaways for fellow designers working in Salesforce-powered marketing

Design for flexibility. AI needs space to breathe, your layouts should anticipate variability.
Think like a builder. Modular, testable, scalable.
Keep it human. No matter how smart Agentforce gets, people still connect with thoughtful visuals, clear flows, and real emotion.
Ask for data early. It’s not just for reporting, it can inform design choices from the start.

If you’re a designer in the Salesforce space, this is your sign to get used to automation tools, AI agents, and your marketing team’s strategy. It’s not about being replaced, it’s about being empowered.

Marketing Cloud, Pro Tips, Strategy
July 10, 2025

Marketing Cloud Account Engagement (Pardot) & Person Accounts

Cate Godley

Person Accounts, an organizational feature of Salesforce, can be a powerful way to differentiate between a business contact (think Cate Godley who works at Sercante) and an individual you do business with that is not associated with a company (think Yuki Godley, shown below).

The reality is that Person Accounts are actually not that scary, but the fact that once they have been enabled they cannot be disabled is likely what causes a lot of that trepidation. This permanent enablement is also present when deciding to sync Marketing Cloud Account Engagement (Pardot) Prospects with Person Accounts in Salesforce, and there are definitely a few things that should be considered before enabling this option in your (or your clients’) Account Engagement organization. Read on to learn more about how to prepare for this setup.

Okay, but what’s a Person Account anyway?

Before we get into the things you’ll want to consider before enabling Person Accounts with ~~Pardot~~ Marketing Cloud Account Engagement (I’m a sucker for alliteration, always) let’s talk about what a Person Account in Salesforce actually is.

Person Accounts allow for a business to accurately track and manage relationships with customers if they’re in a B2C driven space, like education, health care, or non-profits. There are several considerations for Person Accounts inside the Salesforce platform, but here’s a quick summary:

Store information about individuals instead of businesses
Combines Account fields and Contact fields into one record and page layout – the Person Account
Takes up twice the Salesforce storage space due to having a backend Account and Contact record

Once Person Accounts are enabled, you’ll have the option to create a Business Account or a Person Account when creating a new Account from scratch in Salesforce. If you’re converting a lead using the standard Salesforce conversion process, you can create a Person Account by ensuring that the Company field on the lead is blank. No Company? Person Account. Company? Business Account.

The important thing to note here is that a Person Account is like two kids in a trenchcoat, Account & Contact, wearing a sign that says Person Account. In the backend of Salesforce, there is a Contact record and an Account record that are combined to show you the single Person Account record.

Great, but what about Marketing Cloud Account Engagement?

Now that we’ve got the initial details out of the way, it’s time to talk Person Accounts with Marketing Cloud Account Engagement. Just like in Salesforce, once you enable syncing with Person Accounts in Account Engagement you are not able to disable it. Additionally, when you sync a Person Account record with Account Engagement you’ll get a Prospect record and a Prospect Account record which will remain separate in Account Engagement (more on that later). The Prospect record will impact your mailable database number, but there are not any Prospect Account data limitations that you need to keep in mind.

Account Engagement Setup Options

When I first started out as a consultant, syncing Person Accounts with ~~Pardot~~ Account Engagement required reaching out to Salesforce Support to have the feature enabled. With recent updates to the Account Engagement Settings options, Admins are now able to turn on “Sync Prospects with Person Accounts” from within the setup menu.

Create Person Accounts on Assignment (instead of Leads)

In addition to enabling the option to sync Prospects with Person Accounts, you’re also able to tell the system to “Create Person Accounts Instead of Leads”. Turning this functionality on will tell the system to never create a lead when sending a Prospect to Salesforce and is irreversible. This is a good option if you never use leads, however if your organization does use leads or you are using both Business Accounts and Person Accounts you should leave this setting turned off.

Syncing Records Between Salesforce and Account Engagement

One of the biggest considerations with Person Accounts is how you set up your fields in Salesforce and in Account Engagement. Most of the Salesforce literature will tell you to create new custom fields on the Account record to have them added to the Person Account record and page layout. There’s nothing wrong with this setup, however if you’re going to be syncing Person Accounts with ~~Pardot~~ Account Engagement you should keep the Salesforce Connector sync directions in mind.

The Salesforce Connector for Account Engagement has Read & Write permissions for the Lead and Contact objects in Salesforce, and Read Only permissions for the Account object.

If you’re just starting out with Person Accounts in Salesforce, my recommendation is that you create any custom fields that you’ll want Account Engagement to be able to change on the Contact object in Salesforce. This will mean that when creating your custom field in Account Engagement, you’ll be able to do so on the Prospect object and use the standard Salesforce Connector sync options. If you have custom fields for the Person Account already created on the Account object in Salesforce, check out the section on automations below for how to keep these fields in sync.

In the Account Engagement system, the Prospect record that is synced with a Person Account will show the Prospect Name and Prospect Account as the same name. The Prospect record will have any Contact level fields you have added to Account Engagement showing, as well as a Record Type ID of a Person Account. The Prospect Account page will show you any Account level fields you have added to Account Engagement (remember, these are Read Only fields). Both the Prospect and Prospect Account records will show the owner as the Account Owner from Salesforce.

Other Gotchas to Know About

Person Accounts do not support scoring categories in Account Engagement, so if that’s a major player in your marketing strategy, you may need to think about other ways to achieve your goals. In addition to this, the Person Account will only sync to a single record type (the Person Account record type).

Finally, the Prospect Owner will always be the Account Owner in Salesforce. Crucially, this owner cannot be assigned from Account Engagement as we do not have write permissions to the Account record via the Salesforce connector.

Automations for Data Integrity

My earlier recommendation of creating any custom fields that you’d like to be updated by Account Engagement should be created on the Contact record in Salesforce. But what if you’ve already created custom fields on the Account level that you need to update and keep in sync in the Account Engagement system?

The best practice here is to create custom fields on the Prospect record in Account Engagement to hold this information, then create Automation Rules to keep it in sync with Salesforce. This will ensure that custom field information appears at the Account and Prospect levels and keeps bi-directional sync on the Prospect records active.

Enable Person Accounts without Fear

Did I write this entire blog post to get my dog’s photo online? Maybe, maybe not. But I did write this post after helping to answer questions about implementing Person Accounts in ~~Pardot~~ Marketing Cloud Account Engagement many, many times. I, too, used to be filled with trepidation at the idea of using Person Accounts both in Salesforce and in Account Engagement.

Once I understood the fundamentals of how this functionality works in both systems, I felt a lot more confident about getting this set up for clients in multiple business types. I hope this blog post helps you to feel more comfortable with this setup yourself! If you’ve still got questions, comment below or reach out to the team at Sercante and we’ll see how we can help.