Autonomous AI is transforming the way organizations operate, and Salesforce’s Agentforce is at the forefront of this revolution. The product was made generally available by Salesforce in October 2024. Whether you want to streamline case management, enhance lead nurturing, or delight customers, Agentforce empowers businesses to accomplish more with fewer resources. In this post, we’ll share five practical tips to help you successfully implement and use Agentforce. 

Feeling anxious about diving all in with Agentforce? Contact the Sercante team for an Agentforce readiness assessment. That way, you can be sure you’re getting set up for success before you implement Agentforce in your org.

Understanding Agentforce

Before diving into the tips, let’s take a closer look at what Agentforce is.

Agentforce enables autonomous AI agents to perform tasks without human intervention, acting as digital workers within Salesforce or external customer channels. These agents enhance productivity by automating routine tasks and assisting with complex ones. With tools like Agent Builder, you can customize agents using pre-built topics and actions or create entirely new ones tailored to your organization’s needs.

Agentforce integrates seamlessly across the Salesforce platform, leveraging Data Cloud for reasoning and learning. Out-of-the-box agents include Service Agents for case deflection, with more capabilities to be released in December 2024, such as SDR and sales coaching agents.

Unleashing the Power of Agentforce: Five Steps to Get Started

Follow these five steps to get started on the right foot when you dive into Agentforce.

Tip 1: Identify Use Cases

Start by identifying where Agentforce can deliver the most value in your organization. Ask yourself:

• How are you using your CRM today?
• What are the current pain points in your processes?
• Are there routine tasks that could be automated to free up team capacity?
• Are there new processes you’ve avoided due to resource constraints?

Examples of use cases include automating FAQ responses for service teams, generating campaign briefs for marketing, or assisting sales reps with lead prioritization and moving deals faster.

Then for each use case, think about what would be needed to transition to an agent:

• What job should they do?
• What actions will they need to take?
• What actions should they NOT take?  (This is just as if not more important to make sure you have defined the lane where an agent should operate within that use case)

Your responses to those questions are going to help you to understand the level of effort involved in use case. This in turn is going to help you to prioritize based on the level of effort and potential value

Tip 2: Define Success Metrics

To gauge the success of your Agentforce implementation, establish clear goals and KPIs. 

Questions you can ask:

• What does success mean? How will we know we have addressed our problem? 
• What metrics are we tracking today that we want to see improvement on?
• Are there additional metrics that will let us know we are seeing success?

For example:

• Reducing average case handling time by 20%
• Improving lead response times
• Increasing campaign ROI by automating content creation

Ensure you have baseline data for comparison and that the necessary measurement tools are in place to help you track success.

Tip 3: Assess Your Data

Your AI agents are only as good as the data they access. For the use cases identified, evaluate your data readiness:

• What data do need? 
• Where is it located? Is it in your CRM, Data Cloud, or other external systems?
• Is it accessible from your CRM? If it’s stored in an external system, do you have APIs in place to get that information?
• Is the data clean, accurate, and up-to-date?
  • Follow this blog post for tips on how to keep your imported Pardot prospect data clean.
• Do you have a single view of the customer across systems?
  • Get tips for creating that single source of truth in this blog post that covers marketing asset reporting, and this blog post that covers customer data platform reporting.
• Lastly, are knowledge bases and metadata structured for easy access? 
  • Agents need knowledge to inform how they will operate and answer questions. This is all of the background configurations your agents actions will rely on — flows, prompts, and Apex for example — they need to also be clearly identifiable and accessible. 
  • When you add actions to your topics, it uses the descriptions to help fuel the instructions. The naming conventions of your resources will also make it easier to determine what the inputs and outputs need to be.

Data and metadata are the backbone of AI performance, so this is an important area to pay attention to.

Tip 4: Start Small

After completing the previous steps, you may have more than one great use case to start with. Here’s where you ask yourself: What are the quick wins that we can get started on that can move the needle and that we can expand on as we mature?

It’s really easy to get caught up on how this can solve ALL the things. There are many challenges to starting a complex process all at once. If a lot of effort is required to get the data in place or to get the actions set up, it will be more difficult to roll out, not to mention making it potentially disruptive and prone to issues 

Avoid the temptation to tackle complex processes right away. Instead, focus on a simple, high-impact use case to pilot Agentforce. There are many out-of-the-box topics and actions that make getting started easier. For example, automating a single FAQ response or generating summaries for sales reps.

Starting small helps build confidence, momentum, and organizational buy-in, and it also reduces the risk of missteps.

Tip 5: Nail Down Clear Instructions

When designing agents, clarity is key. Use the Agent Builder to create and test well-defined topics and actions:

• Topics – Include precise instructions for classifying user requests, setting guardrails, and outlining scope.
• Actions – Clearly define what the agent should do, including required inputs and expected outputs.

Salesforce Agentforce Topic Instruction Best Practices

Instructions are the foundation for grounding how agents perform. They set the guardrails for how the agent should behave and give the agent the context it needs to do its job. 

Here are a few best practices for writing Agentforce topic instructions:

• Start simple
  • Start with the main use case first to ensure the agent is performing as expected. Then, add in more detail to address edge cases. Be sure to test existing instructions for any conflict. You don’t want to confuse the agent! 
• Use plain language
  • Use concise natural language to describe what your action does. Keep it to 1-3 sentences, and it can include the goal of the action, any use cases, and the objects or records it uses or modifies. 
  • In general, the more relevant detail you include in your instructions, the easier it is for the agent to differentiate between actions. Also, be sure to vary the words you use. For example, use a mix of “Get,” “Find,” “Retrieve,” or “Identify” for actions that will query records.
• Avoid industry or company jargon
  • Write like you are instructing someone who doesn’t know your business. Even terms like ‘qualified lead’ could mean something different from one organization to another. Give context where necessary, and reference clear criteria using the data it will have access to. 
  • For example, instead of vague terms like “qualify lead,” specify conditions such as “lead status equals MQL.” 
  • The agent isn’t not going to know your business processes either, so be explicit about the sequence of instructions or any conditions a conversation must meet for an agent to apply an action.
• Think of all the paths
  • You want to go through every possible permutation to determine the actions required. For example: a customer reaches out because they didn’t receive their order. 
  • First think about the order status ( Order Shipped, Delayed, Not Found, Processing). If the status is Shipped then there could be different tracking statuses (In Transit or Delivered for example). If the order is showing as Delivered, was it delivered to the customer’s correct address? Was it stolen? …and so on.
• Remember the Guardrails
  • Keep the Agent in its lane by providing clear instructions on what the agent should not do to prevent unwanted responses. In cases where the agent is customer-facing, be sure to also give clear direction on when an interaction should be routed to a human.

Test these instructions thoroughly in the Agent Builder’s testing environment to ensure your agents behave as expected.

Ready to Explore Agentforce?

Agentforce offers an exciting opportunity to enhance productivity and streamline operations. By identifying the right use cases, preparing your data, and starting with manageable projects, you can set your organization up for success.

Want to learn more? Check out Salesforce’s Agentforce Trailhead and virtual workshops to get hands-on experience. Need expert guidance? Contact the Sercante team for an Agentforce readiness assessment.

Original article: Five Tips for Getting Started with Salesforce Agentforce

©2025 The Spot. All Rights Reserved.

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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.

Original article: Using Data Cloud Credits in Marketing Cloud Growth Edition: A Guide for Account Engagement Users

©2025 The Spot. All Rights Reserved.

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Student expectations today are vastly different than they were a decade ago. It’s causing technology leaders at the most successful educational institutions to rethink their data infrastructure and student journeys through real-time interaction management strategies.

Today’s students want a personalized, seamless, engaging journey that keeps pace with their brand experiences outside of higher education. At the same time, more and more individuals are bypassing the traditional college education routes altogether. That means higher education institutions (HEIs) need to exceed student expectations to reach enrollment and retention goals and ultimately deliver successful student outcomes.

Combating Headwinds in Higher Ed: A three-part series

Throughout this three-part blog series, you will learn about using your institutional data to create personalized student experiences at scale and in real-time within your college or university. 

1. Part one: Real-time interaction management and real-time interaction for student success  
2. Part two: Overview of Salesforce Data Cloud for higher education professionals, potential use cases, and best practices for successfully using Data Cloud
3. Part three: Building a unified data vision and then activating your data to build a CRM + AI + data strategy for your institution

This series was co-authored by Kirsten Schlau, VP of Technology at Sercante, and Dr. Bradley Beecher (email), Director, Student Experience at Salesforce.

Harnessing data to navigate and overcome challenges in higher education

To help combat higher ed headwinds, there’s a tremendous untapped opportunity for HEIs to use their data by improving organization-wide data infrastructure.

Yes, you’re probably reading this and thinking things like:

We do use data — we analyze our data to maximize the value of resources and stay ahead of constituent needs.

Or even…

We use our data to create strategic plans, execute them efficiently, and analyze their results to differentiate our institution, proactively improve student outcomes, and report outcomes to government agencies and ranking organizations. 

Oftentimes though, that data is trapped inside campus systems that don’t easily integrate with each other. It’s time-consuming to piece together a cohesive and accurate story when the data is trapped, but there’s a better way. It involves creating a fully integrated single source of truth to manage student data.

Unifying student data can help your institution to:

• Generate real-time institutional reporting
• Create a unified student record
• Take action from the data
• Personalize the student experience to reinforce a sense of belonging 

Taking cues from non-HEIs to use data for growth and retention

What if we told you there’s an opportunity more specifically to use that data on an individual basis, at a 1:1 scale to personalize the student experience in real-time?

This is happening in other industries. In fact, you might have experienced personalization like this as an online shopper. Here are a few examples.

What is real-time interaction management (RTIM)?

Real-time interaction management, also known as RTIM, uses customer interactions, predictive modeling, and machine learning to deliver consistent, personalized customer experiences across channels in real-time.  

“Forrester Research analyst Rob Brosman originated the term Real-Time Interaction Management in 2012, and three years later Rusty Warner, another Forrester analyst, offered the formal definition of, “Enterprise marketing technology that delivers contextually relevant experiences, value, and utility at the appropriate moment in the customer life cycle via preferred customer touchpoints.” – Source

RTIM equips marketers to gain immediate visibility into critical moments within the shopping or user experience, which can deliver better consumer experiences and outcomes. This includes generating relevant offers and product suggestions on the right devices at the right time to drive customer engagement, satisfaction, and, in turn, revenue growth. 

Impact of real-time interaction management in the real world

As an everyday consumer, you’ve likely already experienced the effects of RTIM (or you’ve experienced a scenario where you wish RTIM was in place).

Example scenario illustrating RTIM in e-commerce:

Let’s say a customer, Maria, visits an online fashion retailer’s website:

1. Browsing Products: Maria lands on the retailer’s homepage and starts browsing through summer dresses.
2. Real-Time Data Capture: As Maria navigates through the website, her behavior is captured in real-time. This includes the pages she visits, the products she clicks on, her past purchase history, demographic information, and any other relevant data.
3. Real-Time Analysis: The e-commerce platform analyzes Maria’s behavior and data in real-time. It identifies her preferences based on her browsing history, past purchases, items in her shopping cart, and any other available data points.
4. Personalized Recommendations: Using RTIM, the e-commerce platform dynamically generates personalized recommendations for Maria. It might suggest summer dresses similar to the ones she’s viewing based on her style preferences and past purchases. These recommendations are displayed prominently on the website in real-time.
5. Real-Time Engagement: While Maria is still browsing, a pop-up notification appears offering her a limited-time discount on a dress she had previously shown interest in. This real-time engagement aims to incentivize Maria to make a purchase.
6. Adaptive Pricing: As Maria continues to browse, she adds a couple of dresses to her cart but hesitates to complete the purchase. In response, the e-commerce platform dynamically adjusts the prices of the items in her cart, offering her personalized discounts or free shipping to encourage her to proceed to checkout.
7. Abandoned Cart Recovery: If Maria leaves the website without completing her purchase, the e-commerce platform sends her a personalized email reminder within minutes to remind her about the items in her cart. These reminders offer her an additional discount or incentive to complete the purchase.
8. Cross-Channel Consistency: Whether Maria interacts with the retailer’s website or mobile app, or when she receives an email, the messaging and recommendations remain consistent across all channels for a seamless and personalized shopping experience.

In this example, RTIM enables the e-commerce retailer to engage with Mary in real time, providing her with personalized recommendations, discounts, and reminders tailored to her preferences and behavior. This ultimately increases the likelihood of conversion and enhances customer satisfaction.

Additionally, some online retailers are now using RTIM not only in their marketing efforts but also as a way to offer seamless customer experiences. 

Harnessing RTIM at colleges, universities, and other post-secondary education institutions

In the e-commerce example above, the experiences were grounded in segmentation and, of course, made up of various data points. 

It’s no different for HEIs. The ability to segment and provide greater personalized content and experiences leads to a great student experience.

We’ll share a few examples of how other professionals in higher education are doing this today.

Real-time interaction for student success

Imagine a world where student advisors can gain a full 360° picture of their students in a single view. This could include:

• Past class enrollment records and performance indicators
• Required courses that support their designated degree path
• Intelligence to recommend courses based on individual interests and passions outside of their degree path
• Automatic insights into things such as on target to graduate, at risk, potential for drop-out, and any other insights unique to your institution.

Oh! And one more thing to add: this is all done at scale with minimal manual effort put on the advisor.

Step 1 to building an RTIM strategy: Unify data to create a single source of truth

This vision can become a reality when your data is not trapped in siloed campus systems. 

You might say, “How is that possible?”

Here’s how you can start building a student-centric RTIM strategy.

All of this data aggregation and related insights are powered by Salesforce Data Cloud and Einstein 1 Platform. They are the building blocks to creating personalized student experiences with real-time capabilities. And they can also help advisors to gain more time to focus on making meaningful connections with their advisees and ensuring their long-term success. 

How does the Einstein 1 Platform support RTIM strategy for HEIs?

The Salesforce Einstein 1 Platform (A.K.A. “Salesforce core”) unifies your data, AI, CRM, development, and security into a single platform. It’s an extensible AI platform (meaning, it easily connects with other Salesforce platform products and third-party integrations), and it can facilitate the fast development of generative apps and automations.

Through Einstein 1, your institution can appropriately address students’ most common, basic, or foundational questions through alerts and automated workflows. Then your advisors’ interactions with students can center on deeper and more meaningful advising conversations.

Creating unified student profiles with connected data

A unified student profile, aggregating student data into a single student record allows advisors to meet with more students and encourage those meaningful conversations. For example, instead of talking through the required courses advisees need for their program, they get automated alerts listing which courses to take next. Then, the advisee’s open office hours can become career exploration sessions or deep dives to help students better understand complex concepts.

At institutions with siloed data, creating alerts like those in the example requires a ton of manual effort and time. And let’s face it — advisors don’t have time to spare. 

How Data Cloud solves the RTIM puzzle

With Salesforce Data Cloud, advisors can provide more proactive and holistic support for students. That’s because campus data for each student is unified in a single record — something that benefits both students and the institution.

In turn, students make more informed and thoughtful decisions with this proper support from academic advisors. Getting automated alerts supports students as they navigate the university/academic program policies and procedures, and, more importantly, offers an exceptional college experience.

Ultimately, Data Cloud will help build better staff experiences with a unified student record and a seamless student experience that meets their modern expectations.

In the next post in this series, we will provide an overview of Data Cloud for Higher Education, examples of potential use cases, and best practices for using Data Cloud.  

Ready to transform your student experience through real-time interaction management?

Discover how real-time interaction management can elevate the way you engage with students, and enhance their experiences with personalized, timely interactions that make a real difference.

Learn more about Salesforce Education Cloud here to understand the platform and how it compares and relates to your current technology stack.

Then, send a message to Sercante to learn about our Salesforce consulting services for higher education institutions, including Salesforce implementations & migrations, design & architecture services, reporting & analytics, custom integrations, and everything in between.

Original article: Combating Headwinds in Higher Ed: Part 1 – Real-Time Interaction Management

©2025 The Spot. All Rights Reserved.

The post Combating Headwinds in Higher Ed: Part 1 – Real-Time Interaction Management appeared first on The Spot.

I recently ran into a situation where a client needed to exclude select campaign types from being populated as the Primary Campaign Source field on opportunities. While this might sound unusual on the surface, the use case was very logical and likely impacts other organizations too. Read on to learn how we solved it to customize primary sources on opportunities using Salesforce flow.

Use Case

Before getting too deep into the solution, let’s first review the use case for relevancy in your organization. In this particular situation, the sales teams were leveraging Salesforce campaigns as a way to group records for outreach. Some of the outreach campaigns became quite large over time and began skewing data in the Primary Campaign Source field on opportunities.

Many reports in the organization were based on the Primary Campaign Source field and the outreach campaigns were undermining the impact of true marketing campaigns. It was determined that reporting would be more accurate if outreach campaigns were excluded and the Primary Campaign Source field was populated using the last “responded” campaign (based on the responded checkbox).

Primary Campaign Source Field Review

Before we get into the solution, let’s do a quick recap of the Primary Campaign Source field on opportunities. Campaign attribution can be a confusing topic, so it never hurts to review.

How is the Primary Campaign Source Populated?

• Lead Conversion (with Opportunity) – The Primary Campaign Source field will be populated with the campaign that was most recently associated with the lead.
• Opportunity Creation (from Contact) – The campaign that the contact was most recently associated with will populate the Primary Campaign Source field when a new opportunity is being created from a contact record. Users have the ability to change the value before saving the record. 
• Manually – Users can manually update the Primary Campaign Source field on the opportunity using the picklist of active campaigns.
• Automation – The Primary Campaign Source field can also be updated based on an automated process in Salesforce (generally a Flow).

Do Auto-Association Rules Apply?

Great question! Auto-association rules are part of campaign influence in Salesforce and are used to create campaign influence records. They are not factored into the population of the Primary Campaign Source field on opportunities.

Primary Campaign Source Field (on Opportunities) vs. Primary Source Campaign Influence Model

• Primary Campaign Source Field (on Opportunities) – Lookup field on the opportunity that links it to a single campaign.
• Primary Source Campaign Influence Model – Campaign influence model that attributes 100% of the influence to the campaign noted in the Primary Campaign Source field on an opportunity.  

Solution Review

Now that we’ve laid the foundation, let’s address the solution.

Step 1 – Determine Exclusions & Actions

The first question to answer is “What campaigns should be excluded from the Primary Campaign Source field?”. Depending on your organization, this could be a campaign type, a campaign record type, or a combination of both. 

Step 2 – Determine Actions

Now that we know what campaigns we would like to exclude, what should we do when we run across an opportunity with an excluded value? The default Salesforce behavior is to use the last associated campaign. We could go that route and use the last “valid” campaign that a lead or contact was associated with or we could go a step further and use the last campaign that has the “responded” box checked.

I prefer prioritizing my “valid” campaigns based on the “responded” checkbox. Similar to how I configure auto-association rules, I just don’t like giving credit to a campaign if the lead/contact has not actually engaged with it.

We also need to consider how the Primary Campaign Source will be populated if no valid campaigns are found. You can choose to keep the excluded value (as a reference point), clear the value, or populate with a default value. I elected to retain the excluded value (prefer data to no data), but you have options!

Step 3 – Build it in Flow (Sandbox)

For illustrative purposes, I created a flow in my dev org to show you how this solution could work for you. Here are the assumptions that were used.

• Campaigns with the type of “Sales Prospecting” should be excluded.
• When updating the Primary Campaign Source field, the most recent responded campaign (checkbox checked) should be used.
• If a valid campaign is not found (or the only campaign has a non-responded member status), the Primary Campaign Source field should be populated with the most recent campaign (basically defer to the default Salesforce behavior).
• Since this data is used for reporting purposes, real-time updates are not needed. 

Flow Summary 

• This solution uses a scheduled flow based on the opportunity object. The flow runs nightly and processes all opportunities that were created or updated that day.
  • Note: Relative dates can’t be used in the filter conditions of scheduled flows. To address this, create a custom checkbox field on the opportunity object that will evaluate TRUE if the opportunity was created or updated today and use it in your criteria.
  • Below is my filter. It’s selecting opportunities that have contact roles and were created or updated today.

• Get campaign members for contact roles
  • In this step, we get all the responded campaign member records (for the contact role) and sort them so the most recent is first.

• Loop through campaign members
  • Next, we loop through each of the campaign member records related to the contact role, find the first valid campaign (responded), and save it to the assignment variable.

• Update the opportunity record
  • Finally, we update the Primary Campaign Source field on the opportunity with the campaign ID stored in the assignment variable.
  • Note: If you decide to keep the most recent campaign as the Primary Campaign Source (if a valid campaign is not found), you will need to add a final assignment element prior to updating the record. The element uses a formula to ensure that the variable has been populated with a valid value and updates to the original campaign ID (even if it’s an excluded value) if blank. This prevents the Primary Campaign Source from being updated to a null value by the flow.

Complete Flow 

Here’s a look at my final flow.

Step 4 – Test & Validate

As with any flow, test, test, and test again before deploying to production. Below are some test scenarios to use for validation.

Create a new opportunity at lead conversion 

• Lead with a single valid campaign
• Lead with multiple valid campaigns 
• Lead with an excluded campaign (most recent) and a valid campaign 
• Lead with a single excluded campaign 
• Lead with a single non-responded campaign membership

Create a new opportunity from a contact 

• Contact with a single valid campaign 
• Contact with multiple valid campaigns 
• Contact with an excluded campaign (most recent) and a valid campaign 
• Contact with a single excluded campaign
• Contact with a single non-responded campaign membership

Update Primary Campaign Source on an existing opportunity

• Update to an excluded value (make sure that there’s a contact role who has a valid campaign) 

Test Table

When testing and validating flows, I like creating tables to record results for review. This helps me organize my thoughts and ensure that everything is working as intended.

Is the Primary Campaign Source field meeting your needs?

If you are using the Primary Campaign Source field in your reporting I encourage you to take a closer look at your campaigns to see if your data is being skewed. If so, this solution is a great way to prioritize valid campaigns and put more emphasis on engagement. You can even completely filter out specific types of campaigns if you choose. Don’t sell your marketing efforts short!

More Salesforce Flow resources

• An Introductory Guide to Salesforce Flow for Marketers
• Getting Started with Einstein for Flow
• How to Update Marketing Personas Using Salesforce Flow
• Creating Custom Object Records with Account Engagement and Flow
• Salesforce Automation Game-Changer: Einstein GPT and Data Cloud Capabilities for Flow

Original article: How to Customize Primary Source on Opportunities with Salesforce Flow

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Uh-oh. You just received an email from Salesforce saying you have exceeded your Marketing Cloud Account Engagement (Pardot) mailable database limit. That means if you don’t reduce the amount of mailable prospects in your database quickly, it’s going to cost you. 

Or maybe you were “just checking” one day & noticed that your Mailable Database limit was getting close to that 100% mark, and you need to do something quickly to prevent it from going over.

While the default Account Engagement instance allows for 10,000 mailable contacts, some companies purchase additional contact blocks of 10K prospects each based on their anticipated marketing/subscriber audience size. If you capture more mailable prospects than you’re limited to, Salesforce will allow you to capture those additional prospects in Account Engagement, but they will also invoice you for them.

At the end of the day, we’re all trying to grow our businesses and our audience size. So, hopefully, a time will come when we need to purchase another block of contacts to increase our mailable database limit. But if today isn’t that day, here are ways we can clean up our mailable database quickly and keep it tidy for the long haul.

How to check your mailable database numbers

If you get an email notice from Salesforce, the email will tell you how many mailable prospects are in your Account Engagement database compared to your database limit. Let’s log in to verify those numbers. 

There are two ways to check your mailable database numbers if you haven’t received an email from Salesforce for exceeding your mailable database limit or aren’t sure how many mailable prospects are in your database compared to your limit. 

Check your Prospects Table with the Mailable Prospects list view

In Account Engagement (Lightning) go to your Prospects tab > List View: Mailable Prospect. This represents your total number of mailable prospects, but it doesn’t tell you what your mailable prospect limit is.

Use the Usage and Limits Tab to see your mailable prospect utilization

In Account Engagement (Lightning) go to your Account Settings > Usage and Limits Tab. It’s important to know that there can be up to a 24-hour delay in the total number of mailable prospects represented in this table. 

However, this table shows you your mailable prospect database limit and percent of utilization in addition to the total number of mailable prospects — just check that total number to the prospect table we just noted above.

Also – one VERY important reminder!

Mailable prospect limits are shared across Account Engagement Business Units!

This means that if you have a limit of 10,000 mailable prospects, 9000 are in business unit A and 1941 are business unit B, your total database is actually at 10,941 mailable prospects! You are over your limit. This requires a little math and also an admin who is either monitoring both business units, or two Account Engagement admins who are, at the very least, communicating with one another. 

Wait, who is a mailable prospect again?

Before we can start determining who to keep in our database and who to purge, we need to understand who counts against our database limits. Mailable prospects count against your limit, but non-mailable prospects do not. 

Here are some quick bullet points to help you know which prospects are mailable and which ones aren’t.

Mailable prospects

• Any prospect who is eligible to receive marketing and operational emails

Non-mailable prospects

• Any prospect who has opted out
• Any prospect who is marked as “Do Not Email”
• Any prospect who has 1 hard bounce or 5 soft bounces
• Any prospect who has been deleted and now lives in your Recycle Bin
• Any prospect whose mailable status is “Operational Emails Only”

To reduce our mailable database, we need to turn our attention to mailable prospects.

Quick Wins: How to reduce your total number of mailable prospects quickly

Who should I keep in my mailable database and who is okay to purge? Here are three quick wins you can apply today.

1. Get rid of “junk” prospects

Their mailability status may say they are mailable, but it’s probably unlikely that test@123.com is a real prospect. Run a dynamic list, or multiple dynamic lists for that matter, that look for junk prospects.

This blog post is FULL of amazing Dynamic List options to run on the four fields most often filled with spam content: First Name, Last Name, Job Title, and Email.

Once you have created your dynamic list(s), select the prospects to delete and use a Table Action to send these prospects off to the Recycle Bin.

2. Delete old, unengaged prospects

Another quick win option at quickly reducing your mailable database size: delete the mailable prospects who aren’t engaging with your emails and marketing materials, and instead keep your focus on the prospects who are interested in what you are sharing with them.

• Create a dynamic list that looks at prospects who were created 18 months ago and haven’t engaged in the last 12 months.
• Tweak this according to your unique business model — how you want to measure age of prospect and how you want to define engagement.
• Run the list, select the prospects to delete, use a Table Action to delete the prospects.
• Now, those Prospects live in the Recycle Bin — they do not count against your mailable database. However, Account Engagement will resurrect them out of the Recycle Bin, along with their historical activity information (before deletion), if they fill out a form again in the future.
• FYI – When you delete a prospect from Account Engagement, it does not delete their Salesforce lead or contact records. 

Dynamic List Criteria Example

This type of list criteria could look something like this:

3. Filter out your competitors

If you are prioritizing your marketing spend on prospects who are most likely to purchase at some point in the future, competitors might not be on that list. 

Create a dynamic list and then utilize an automation rule to mark these prospects as ‘Do Not Email.’

• Step 1 – Write a list of all of your competitors email sending domains (or what follows the @ in their email address). 
• Step 2 – Create a dynamic list that looks at the Prospect Default Field Email Contains, and then insert your list of competitor email domains separated by a semi-colon (;). This allows you to use one line of criteria instead of each email domain requiring separate criteria entries.
  • Example: @competitor1.com;@competitor2.com;@competitor3.com
  • Note: If your list is long and you run up against character limits, utilize this sweet tool called Creuz Your Data to split your list of values into appropriate data chunk sizes with semi-colons already in place.
    • And then I recommend to bookmark that tool – you’ll thank me later

• Step 3 – Create a repeatable automation rule to check if a prospect is a member of your Competitor List to update the prospect’s field ‘Do Not Email’ to True.
  • By setting the rule as repeatable you ensure that if the ‘Do Not Email’ field is ever cleared, it will re-update to True.

Long-Term Success: Maintain a tidy mailable database

Okay, so now you have taken quick actions to weed out clutter from your mailable database and are within your utilization limits again. Phew! Now let’s consider how we maintain this clean and tidy house. 

Use the confirmed opt-in approach

Start on the right foot when your prospects opt-in to marketing emails. Let them know what they can expect to receive from you by signing up for your mailing list and have them confirm their email address and subscription preferences from the start. This helps eliminate invalid email addresses and uninterested prospects before they fill up your mailable database. 

Want to know more about confirmed opt-in? Check out this blog post.

Set up a regular timeblock to check your lists so you can delete junk and unengaged prospects

Remember that the lists you created to weed out “junk” prospects and older, unengaged prospects are just lists. You still need to go in to delete prospects and send them to the Recycle Bin. Depending on the size of your lists, you may want to monitor this weekly, monthly, or quarterly. Create a repeating calendar event, and you’ll never have to remember not to forget about it. Easy peasy.

Create an Engagement Studio program to re-engage prospects before they make it to the unengaged list

How do you get prospects to engage with your marketing materials? Email them! 

Give prospects a chance to re-engage before they make it onto the unengaged prospect list. Create an Engagement Studio program that encourages your prospects to engage with compelling content and calls to action. Warm them up by reminding them of how great your product or service is.

Run a Permission Pass

A Permission Pass is an opportunity to reach out to your unengaged prospects and ask if they still want to give you permission to keep emailing them. Simply put, ask them if they still want to hear from you. This can be done at any time, or even better, at the end of a re-engagement program after you have tried to reconnect with them. If they do not respond to the email within the given timeframe communicated in the email, it’s time to let them go and send them to your Recycle Bin. 

It can be scary letting “real prospects” go, but remember — in the long run it is better for your bottom line and for your reputation. Spend marketing dollars and invest time and effort in prospects who are interested in your product. Also, you are less likely to have spam complaints from prospects who are just annoyed with what they perceive to be junk in their inbox.

Plan for growth

I love this part. If you are still pretty close to your mailable database limit after all these tips and tricks, start budgeting conversations now with leadership. 

Show them numbers before and after tidying up the mailable database. That way, they’ll understand the need to start planning to market to more mailable prospects and budgeting in the next 10K or 20K prospects. 

Even better, back up your numbers with reporting data on how your marketing efforts are producing great leads and increased revenue!

Bring in the experts to reach radical impact

Have you checked your Pardot mailable database usage and limits? Have you tried the suggested quick wins, but still need more help? Or do all of these tips and tricks sound good, but you need some help with the execution? Sercante is here for you! We have a great team of experts who can help audit your system and provide you with personalized recommendations.

Or… This might have just started with a need to reduce your mailable database to stay within limits, but now you’re excited about the opportunity of setting a laser focus on your mailable prospects and how you can serve them in greater ways!

Let us help you.

We have the best of the best when it comes to planning amazing nurture programs to re-engage unengaged prospects. We also have the best of the best when it comes to using analytics to support your marketing campaign ROI. 

Reach out to Sercante as you plan for growth by radically impacting your business with your mailable prospects today!

Original article: I Exceeded My Account Engagement Mailable Database Limit. Now What?

©2025 The Spot. All Rights Reserved.

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In the age of big data, effective audience segmentation strategies are the key to unlocking the full potential of vast datasets available to enterprise-level companies. Join me on a journey from data overload to impactful insights as we explore how enterprise segmentation strategy drives meaningful results. 

From demographic segmentation to behavioral analysis, we’ll delve into the various segmentation approaches that empower enterprise companies like yours to understand their audiences on a deeper level.

Segmentation strategies for enterprise marketers

Businesses today face a monumental challenge: how do they effectively harness and analyze the customer information that’s at their disposal? 

One powerful solution is audience segmentation. By dividing large datasets into smaller, more manageable subsets based on common characteristics or behaviors, segmentation enables enterprises to unlock the hidden value within their data and make informed decisions that significantly impact their bottom line.

 In this blog, we’ll examine the fundamental principles of segmentation, discuss its various applications, and provide practical insights into implementing segmentation strategies that deliver measurable results for marketers at enterprise companies. 

Demystifying Segmentation

At its core, segmentation is a strategy marketers use to divide their broad customer base into smaller groups based on shared characteristics, behaviors, or preferences. The end goal is that marketing has specifically targeted lists to tailor their efforts. With their extensive reach and scale, enterprise businesses typically have large target audiences spanning across different demographics, geographies, and industries. 

These audiences can encompass millions of consumers, making effective targeting and engagement a significant challenge. However, by having the marketing team segment its audience into smaller, more manageable groups, your business can tailor their marketing efforts, products, and services to meet customer needs.

Data Distilled

Identifying segmentation criteria determines the variables that will be used to divide target audiences into distinct segments. The choice of segmentation criteria depends on the specific goals of the business, the nature of the product or service being offered, and the available data. 

Standard segmentation criteria include geographic, behavioral, product interest, or demographic factors. Businesses can create meaningful segments that enable more targeted and effective marketing strategies by carefully selecting segmentation criteria that are relevant, actionable, and aligned with business objectives.

Geography

Geographic segmentation focuses on location or region. This is most often used when there is great variation between consumers based on their locale. 

One well-known enterprise to use this strategy is McDonald’s. In a recent article written by Two Teachers, they share that “By tailoring its products, services, and marketing messages to meet the unique preferences and needs of consumers in different regions, McDonald’s has been able to create a powerful global brand that resonates with people from all walks of life.” 

McDonald’s successfully uses geographic segmentation daily by tailoring their advertising and their menu items, to fit the local preferences. For example, here in the United States, we may seek the Big Mac, whereas in Japan, their HiruMac Teriyaki McBurger. Yum!

Behavioral

Behavioral segmentation includes purchase history, loyalty, and social engagement. This strategy focuses on consumer preferences and patterns, and Netflix is one of many enterprises using this method daily. 

According to Scientific American, “users discover around 80 percent of shows through algorithmic recommendations.” For Netflix, this is highly dependent on users sharing their ratings along with watching preferences and saves. With AI at our disposal, behavioral targeting is becoming even more popular and easier.

Psychological

Pscychographic segmentation prioritizes attitudes, values, lifestyles, and interests. This method targets a customer’s motivations and preferences. This is a broader method, as it can be challenging to target someone based on feelings, but some brands do it successfully. 

Let’s take a look at Nike. According to PDF Agile, Nike has very specific personalities they are targeting – men who go to the gym and love sports, women who exercise or prefer sportswear, and children who are also athletes. 

According to that article, “Nike focuses on the people who enjoy engaging in sports. The company is passionate about sports, and it makes products suitable for sports lovers.” As a result, all of their campaigns are focused on that type of individual.

Demographic

Demographic segmentation assesses age, gender, income, education, job role/title, etc. This strategy allows business to tailor their marketing efforts to meet the needs of a specific demographic. This is the easiest of the segmentation strategies as it is the easiest data to collect, and it’s also inexpensive while effective. 

Let’s look into the financial sector, which offers “different tiers of products and services based on income levels,” according to Faster Capital. Affluent customers are targeted and sold premium credit cards with high fees and exclusive perks, while a college student would be offered a credit card with low fees and a rewards program. 

Navigating the Data Maze: Enterprise Segmentation Strategy

So, how do I get from point A to point Z? Let me walk you through it.

1. Perform Market Research: Know your market and collect ALL of the data!
2. Create the Personas: Who is your ideal customer and what do they want?
3. Analyze and Segment: Analyze the data, examine segmentation opportunities, and go for it!
4. Build a Targeted Campaign: Build a robust multifaceted campaign with that persona at its center.
5. Continuously Monitor and Evolve: Once you’re done, keep going. Be on the lookout for new ways to segment or reach your target audience in new and creative ways.

Get help with segmentation strategies for your enterprise team

Segmentation strategies are invaluable assets for enterprises seeking to navigate the complexities of modern markets and effectively engage with diverse customer bases. 

Enterprises can gain deeper insights into customer preferences, behaviors, and needs by segmenting their audiences based on demographic, geographic, psychographic, and behavioral criteria. Moreover, the continuous refinement and optimization of segmentation strategies enable businesses to adapt to evolving market dynamics and stay ahead of competitors. 

As enterprise companies continue to embrace the power of segmentation, they will unlock new opportunities for growth, innovation, and customer satisfaction.

We’ve helped countless enterprise teams figure out the best approach to audience segmentation, and would love to solve your segmentation challenges, too. Reach out the the team at Sercante to get help with your team’s segmentation strategies.

Original article: Big Data to Big Impact: Enterprise Segmentation Strategy

©2025 The Spot. All Rights Reserved.

The post Big Data to Big Impact: Enterprise Segmentation Strategy appeared first on The Spot.

Before we dive into the details of finding success with your Salesforce Data Cloud implementation, let’s set the stage. Whether you’re a seasoned Salesforce admin or just stepping into the realm of cloud-powered data solutions, Data Cloud is a game-changer, and here’s why you should care.

Navigating the Data Cloud Landscape

Salesforce Data Cloud is a platform that takes all of your data and turns it into actionable insights. It’s for anyone eager to supercharge their Salesforce experience. Whether you’re a department manager or an admin serving sales, marketing, customer service, or any other department, Data Cloud is your ticket to streamlined processes, informed decision-making, and ultimately, success.

The key to success is covering your bases early — before and during implementation. That means asking the right questions, collaborating with the right people, and establishing processes that keep everything running smoothly. 

Why Data Cloud Matters

Imagine having a centralized hub where diverse data streams — from identity platforms and purchase history to website interactions — seamlessly come together. Data Cloud does just that, offering a unified space to make sense of the data chaos. You may also be wondering what to do with the free Data Cloud license that you got as part of another cloud package.

You might wonder, “Why should I care?” Well, the answer is simple — efficiency, effectiveness, and exponential growth.

How to Ensure a Successful Salesforce Data Cloud Implementation

Now that we’ve set the groundwork, let’s delve into five practical tips you can use to guide your Data Cloud implementation with the ultimate goal of unlocking the platform’s full potential. We’ll explore how to propel your Salesforce Data Cloud implementation to new heights. You can also check out this post for a few ‘gotchas’ you may encounter during your Data Cloud implementation.

5 Tips for a Successful Data Cloud Implementation:

1. Reach for organizational alignment
2. Choose impactful use cases
3. Measure success effectively
4. Use out-of-the-box data models
5. Be intentional with your data

Tip#1: Reach for organizational alignment

Now, let’s talk tactics. Aligning your organization before embarking on a Data Cloud implementation is paramount. Here are a few specific tactics to ensure everyone is on the same page:

Establish a Clear Owner

Designate a dedicated owner for the Data Cloud implementation. This individual should be someone with a comprehensive understanding of your organization’s goals and processes. Having a clear owner ensures accountability and a streamlined decision-making process.

Conduct Cross-Functional Workshops

Bring together representatives from various departments for workshops. Discuss the potential impact of Data Cloud on each team and encourage open communication. These sessions not only educate team members but also foster a collaborative spirit.

Define Roles and Responsibilities

Clearly outline the roles and responsibilities of each team involved in the implementation. From data management teams to end-users, everyone should know their part in the process. This clarity prevents confusion and sets the stage for a smoother implementation.

Communicate the Benefits

Emphasize the benefits of Data Cloud to every stakeholder. Whether it’s time savings, improved insights, or enhanced customer experiences, make sure everyone understands how Data Cloud aligns with the organization’s overarching goals.

Address Concerns Proactively

Open the floor for questions and concerns. Addressing potential roadblocks early on builds confidence among team members. Proactively seeking and resolving concerns sets the tone for a collaborative and supportive implementation journey.

Tip#2: Choose impactful use cases

Now, let’s talk about choosing the right use case — the cornerstone of a successful Data Cloud implementation. We urge you to start with the end goal in mind (instead of a technology-first approach, which many of us are so tempted to do). Focus on one or two initial use cases that drive team optimization and deliver tangible results within a reasonable timeframe. Whether it’s streamlining contact behaviors or enhancing customer segmentation, these impactful use cases showcase the value of the platform and generate positive buy-in across the organization.

Start with end goals in mind

Begin by identifying the desired outcomes of your Data Cloud implementation. What specific business objectives are you aiming to achieve? Whether it’s improving sales efficiency, enhancing marketing targeting, or optimizing customer service, starting with clear end goals ensures alignment and focus.

Evaluate business processes

Conduct a thorough assessment of your organization’s existing business processes. Identify pain points, inefficiencies, and areas for improvement. Look for processes that rely heavily on data and could benefit from the insights provided by Data Cloud. Consider areas where you’ve got trapped data and manual flows/processes.

Prioritize use cases with high impact and feasibility

Once you’ve identified potential use cases, prioritize them based on their potential impact and feasibility. Focus on use cases that offer significant benefits with manageable implementation efforts. Consider factors such as resource availability, data availability, and technical complexity.

Involve stakeholders in use case selection

Engage stakeholders from relevant departments in the use case selection process. Gather input from sales, marketing, customer service, and other teams to ensure alignment with their needs and priorities. Collaborative decision-making increases buy-in and promotes cross-functional synergy.

Prototype and validate use cases

Before committing to a full-scale implementation, consider prototyping and validating selected use cases. Build prototypes to test the feasibility and effectiveness of the proposed solutions. Use feedback from stakeholders and pilot tests to refine and iterate on use case designs. This is a great use case of taking advantage of the $0 Data Cloud SKU as well.

Data Cloud Use Case Examples

Examples of how customers across Salesforce Clouds are using Data Cloud

Improve Forecasting and Sales Collaboration 

Admin Type: Sales Cloud

• Provide executives a full view of the sales forecast across multiple business units and orgs
• Pass leads from one Sales Cloud org to another to facilitate cross-selling
• Allow sales reps to collaborate with their broader account team on opportunities in separate orgs

Provide Proactive Customer Service

Admin Type: Service Cloud

• Anticipate and deflect cases by sharing info proactively
  • Examples:  warranty extension notifications, product recalls 
• Monitor events and devices to identify service actions
  • Examples: proactively avoid usage or entitlement overcharges or schedule proactive maintenance based on device data
• Predict behavior to offer assistance and recommendations
  • Examples: provide agents with customer’s propensity to buy and next-best action

Personalize Marketing and Drive Engagement 

Admin Type: Marketing Cloud

• Create and automate intelligent audiences fast
• Act on real-time data to personalize every moment 
• Gain insights into high-value segments and campaigns
• Segment more precisely 
•  Activate across the Customer Journey

Tip#3: Measure success effectively

Now, let’s discuss how to measure the success of your Data Cloud implementation effectively. Here are a few specific tactics to guide you.

Define key performance indicators (KPIs)

Identify measurable metrics that align with your organization’s goals. Whether it’s increased revenue, improved customer satisfaction, or enhanced operational efficiency, define KPIs that reflect the impact of Data Cloud on your business outcomes. And don’t forget to keep them SMART (specific, measurable, attainable, realistic, and timely)

Establish baseline metrics

Before implementing Data Cloud, establish baseline metrics to benchmark your current performance. This allows you to track progress over time and quantify the impact of the implementation.

Monitor data quality

Ensure that the data ingested into Data Cloud is of high quality and accuracy. Implement data quality checks and validation processes to maintain data integrity throughout the implementation. This is where taking advantage of our Data Cloud Readiness Assessment is key.

Track user adoption and engagement

Monitor user adoption and engagement with Data Cloud tools and features. Track user logins, usage patterns, and feedback to gauge the effectiveness of training and support initiatives.

Iterate and improve

Once you’ve successfully implemented, continuously review and iterate on your measurement approach. Get feedback from stakeholders, analyze performance data, and identify areas for improvement. Adjust your measurement strategy accordingly to ensure ongoing success.

Tip#4: Use out-of-the-box data models

You have to walk before you can run. Let’s delve into using the out-of-the-box data models during your Data Cloud implementation.

Explore standard data models

Familiarize yourself with the standard data models offered by Data Cloud. These pre-built models cover common data structures and relationships, saving you time and effort in designing custom solutions. Take advantage of these models wherever possible to accelerate your implementation.

Align with Salesforce Einstein 1 (Core) data model

Ensure alignment between the Data Cloud data models and the Salesforce core data model. By aligning these models, you facilitate seamless integration and interoperability between Data Cloud and other Salesforce products. This alignment simplifies data management and enhances overall system efficiency.

Customize only when necessary

While out-of-the-box data models provide a solid foundation, don’t hesitate to customize them to meet your specific requirements. However, exercise caution and prioritize customization only when absolutely necessary. Striking the right balance between standardization and customization ensures long-term scalability and maintainability.

Tip#5: Be intentional with your data

Now, let’s take a look at how you can be intentional with your data. Careful planning on how to use it within Data Cloud is crucial. Whether it’s analytics, segmentation, or real-time data actions, understanding the tools available and selecting the right ones for your use case is key. From calculated insights to data segmentation and AI capabilities with Einstein Studio, being intentional with data ensures effective utilization and actionability.

Data governance framework

Establish a robust data governance framework to govern the lifecycle of data within your organization. Define policies, procedures, and standards for data collection, usage, and management. Ensure compliance with regulatory requirements and industry best practices to maintain data integrity and security.

Data quality management

Implement data quality management processes to ensure the accuracy, completeness, and consistency of your data. Utilize data cleansing tools and techniques to identify and rectify errors, duplicates, and inconsistencies. Regularly monitor data quality metrics and address any issues promptly to maintain the reliability of your data.

Data privacy and security measures

Prioritize data privacy and security by implementing robust measures to protect sensitive information. Encrypt data in transit and at rest, restrict access to authorized users, and implement multi-factor authentication. Stay informed about data privacy regulations such as GDPR and CCPA, and ensure compliance to safeguard customer data.

It’s crucial to promote ethical data practices and mitigate bias in data analysis and decision-making. Educate stakeholders about the ethical implications of data usage and the potential impact on individuals and communities. Implement fairness, accountability, and transparency principles to ensure equitable outcomes and build trust in your data-driven initiatives.

Data lifecycle management

Develop a data lifecycle management strategy to govern the flow of data from creation to archival or deletion. Define retention policies based on regulatory requirements and business needs, and automate data archival and deletion processes where possible. Regularly review and update data lifecycle policies to adapt to evolving business and regulatory requirements.

Data-driven decision-making culture

Foster a data-driven decision-making culture within your organization by promoting data literacy and empowering employees to leverage data in their day-to-day activities. Provide training and resources to enhance data skills across departments, and encourage collaboration and knowledge sharing around data insights and best practices.

Bonus: Tap into expert guidance

Salesforce Data Cloud implementation requires strategic planning, thoughtful execution, and continuous refinement. By aligning your organization, selecting impactful use cases, leveraging out-of-the-box data models, measuring success effectively, and being intentional with data, you can unlock the full potential of Data Cloud and drive transformative outcomes for your business. 

As a bonus tip, we suggested looking toward expertise available in the Salesforce community. Seeking guidance from those who have navigated Data Cloud’s complexities can be invaluable. Whether through expert coaching sessions, community groups, or support office hours, connecting with experienced professionals can enhance your success with Data Cloud.

However, if you find yourself in need of expert guidance or support along the way, don’t hesitate to reach out to the Sercante team. Our experienced consultants are equipped with the knowledge and expertise to help you navigate every step of your Data Cloud journey and ensure success. Contact us today to learn more about our Data Cloud readiness assessment so you can embark on your Data Cloud implementation with confidence.

Related Resources:

• Six Reasons Why You’d Want to Implement a Customer Data Platform
• Should You Buy or Build a Customer Data Platform?
• The Five Major Components of a Customer Data Platform
• Salesforce Automation Game-Changer: Einstein GPT and Data Cloud Capabilities for Flow
• Lessons Learned During Salesforce Data Cloud Implementation

Original article: 5 Tips to Accelerate Your Salesforce Data Cloud Implementation

©2025 The Spot. All Rights Reserved.

The post 5 Tips to Accelerate Your Salesforce Data Cloud Implementation appeared first on The Spot.

You may be aware that when it comes to improving user experience on a record page,  Dynamic Forms have become more and more powerful over the last few Salesforce releases. A good example is the ‘Add Fields from Related Objects to Dynamic Forms-Enabled Pages’ feature from the Spring ‘24 release, which came from a  Salesforce IdeaExchange request.

Dynamic forms are a huge win for making more customizable and engaging user experiences, at least for custom objects and most standard objects. There are still a few that don’t have this feature yet. (I’m looking at you, Campaigns) 

Here’s a handy workaround that may help where dynamic forms in Salesforce aren’t supported.

Check out the latest Spring ‘24 Release updates here, including where you can display related record fields on a record. 

The Use Case: A “Dynamic” Campaign Page

You want to collect certain information for your campaigns, but the data differs depending on the type of campaign. 

Examples may include:

• Events
  • Location
  • Venue Address
  • Venue Contact Info
  • # of Days
• Webinar
  • Webinar platform
  • Presenter details
• Partnerships
  • Partner Information
  • Type of Partnership
  • Partner Contact Info

All of this different data living on the record page can be cluttered and noisy, and forcing the user to scroll through the page to get to the data they need to fill in. It’s not a great user experience and not a great recipe for capturing quality data. 

Wouldn’t it be nice if we could bump up specific fields to more prominent areas of the page based on the type?

Unfortunately, Dynamic Forms can’t help us here (at least not yet — you can upvote the idea here). Some may choose to use record types and page layouts, but that may not be ideal for all companies. 

An Alternative Solution for Salesforce Dynamic Forms

While we may not be able to use Dynamic forms, there are some other Lightning features that can give us a potential workable solution: 

• First we create a Quick Action, which allows us to build a mini page layout of the fields we want to highlight.
• Then we use Lightning Page builder features to display this mini-layout above the fold so it’s easy for the user to find and update:
  • Related Record component
  • Set Component Visibility 

Here’s how.

Create an Action for Partner fields

1. From Object Manager > Campaign > Buttons, Links, and Actions
2. Click New Action
3. For Object Name, select Campaign
4. For Action Type select Update a Record
5. For Label, enter a label that is appropriate for this purpose. It’s a good idea to make it relevant and easy to idenity what it’s for.
   • For example ‘Update Campaign – Event Details’
6. Enter a Description outlining the purpose of this action
7. Click Save

Edit the Action Layout

Once you have saved, you will be looking at the Action Layout page. Here is where you can choose what Campaign fields to display and the arrangement. 

1. Just like you would for a page layout, drag and drop the fields that you want to be visible. 
2. Click Save
3. If you see this message, go ahead and select Yes. We won’t need the Campaign Name on this layout for our use case.
   
4. You can edit this later from the Edit Layout button at the top of the page.

Now we can add our new layout to the Campaign record page

1. From Object Manager > Campaign > Lightning Record Pages
2. Select the Lighting Record Page you want to update and click Edit.
3. Drag the ‘Related Record‘ component where you want it on the page
4. In the Related Record settings panel on the right, update the following:
   • Header Label = the heading that should appear at the top of that layout on the page
   • Lookup Field = Use this Campaign
   • Update Action = the action that you created in Step 1
   • Click Save
5. Select ‘Set Component Visibility’ for the Related Record component. 
6. In the filter area, select Type = ‘Conference’

Voila! Now when working on a Campaign record, the Event Details will appear in their own “section” when the Campaign Type = Conference.  You can repeat this for other fields you want to appear on the page in specific circumstances.

To edit these fields, click the pencil icon next to the field you want to edit. All of the fields in that section will become editable, and notice that the other fields are not. These fields are edited separately because they are part of another component. When done, click the Save button to save the fields in that section. 

Build better experiences with this alternative to Dynamic Forms

While Dynamic Forms in Salesforce are fantastic for jazzing up user experiences, there are times when you need alternatives. Diving into Lightning features such as Quick Actions and Lightning Page Builder can help you to cook up custom solutions that do the job,  like the workaround we’ve explored here for displaying those crucial record fields based on different scenarios.

As you tinker around with ways to supercharge your Salesforce setup, remember, we’re in your corner. Want to chat about how to make your Salesforce dreams a reality? Reach out to the Sercante team today. Let’s brainstorm together and unlock the full potential of your Salesforce journey.

Original article: An Alternative to Salesforce Dynamic Forms When You Need It

©2025 The Spot. All Rights Reserved.

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Salesforce Starter was unveiled in August 2023 as an easy way for small-medium businesses (SMBs) to get started with Salesforce CRM. Historically, SMBs have found CRM systems to be overly complex and difficult to implement, but Salesforce Starter was built with this struggle in mind, allowing customers to get up and running in a matter of minutes while making future growth of the CRM easy.

What is Salesforce Starter? 

Salesforce Starter focuses on sales, service, and marketing and provides guided onboarding to ease users into Salesforce CRM. It’s an easy-to-use platform that’s aimed at getting teams at small businesses up and running with a CRM that can grow as the company scales.

The best part is that getting up and running with Salesforce Starter brings your data into the platform. You’ll avoid some migration expenses later on if you outgrow Salesforce starter and decide to implement other Salesforce clouds to replace it.

What marketing functionality is included in Salesforce Starter?

Salesforce Starter’s marketing features focus on emails, segmentation, and, with Pro Suite, process automation. The marketing features work a bit differently than what we’re used to with Marketing Cloud Account Engagement and Marketing Cloud Engagement. But if you’re familiar with the Lightning Email Builder and Salesforce Flows, you’ll be able to pick up Salesforce Starter’s marketing functionality pretty easily. 

Campaign-Centric Workflow

Marketing in Salesforce Starter revolves around the Campaign. Once you’ve created a campaign, you’re guided to choose between creating a single email (similar to a List Email for Account Engagement users, or a single email send for MC Engagement users) or a Message Series (similar to a “Engagement Studio Program” for Account Engagement users, or a “Email Journey” for MC Engagement users).

Segmentation

Segmentation in Salesforce Starter is handled with Data Cloud, which allows you to create a unified customer profile and harness data from all interactions your Lead/Contact has with your company. If you’re new to Data Cloud segmentation, I highly recommend working through the Segmentation and Activation Trailhead module to get a feel for creating and editing Segments in Salesforce Starter. This help article also provides several Segment examples to help you get started. 

Before we start building our first email, we’ll want to set up an Audience Segment. A Segment is required to preview and test your email, so we’ll want the Segment running while we’re building the email. Click Select Audience from your Campaign page to begin, then select New Segment. 

Building Emails in Salesforce Starter

Building emails in Salesforce Starter feels familiar to the Lightning Email Builder. You’ll start off with a pre-built email template that can be edited by dragging and dropping components from the left side menu. Custom styling can be configured on the right side menu and will change depending on the component you have selected. 

Merge tags can be inserted to personalize the email for each recipient. These merge tags rely on the Data Cloud unified individual rather than having to choose a specific Marketing Platform or Lead Object field. 

Salesforce Starter also supports sending transactional, also known as operational, emails by toggling the Message Purpose field.

Once you are done building your email, make sure you select Publish before previewing and testing your email. Publishing the email will ensure all the associated images are published and won’t be broken during testing. 

The Preview option allows you to toggle between Desktop and Mobile views to ensure your email is responsive. You can also send your team a test email for review, but note that test sends count towards Salesforce Starter’s base credits of 2,000 emails per org/month.

Sending Single Emails with Salesforce Starter

If you’re sending a single email, navigate back to the Campaign Overview page and select Schedule or Send Now.

When scheduling, Einstein Send Time Optimization is available to help select the best time for each recipient on your Audience Segment. Check out our blog post, Pardot Einstein Send Time Optimization: A How-To Guide, for more information on how Einstein Send Time Optimization works.

If you’ve selected Send Now your Email Campaign Flow will automatically be activated. However, if you are scheduling the email in advance, you’ll need to manually select the Activate button to ensure the Flow is ready for this email send. 

Sending a Message Series in Salesforce Starter

If you’re sending a message series, you will have to first edit your Flow so you can configure the schedule, segment, and wait steps between each email send. By default, the Message Series Flow will be built with a 1 day wait step between each email, Einstein Send Time Optimization is disabled, and Track Clicks and Track Opens is enabled. All of these settings can be reconfigured by clicking each element within the flow. 

Make sure you select the Start element to configure your segment and schedule. 

Once you’ve finished configuring your Message Series Flow, make sure you Save and Activate the flow before navigating back to the Campaign overview page. 

Now, if you are new to Flow and the steps above are causing a bit of existential dread, don’t worry! Flows seem a little intimidating at first, but I promise they are pretty easy to use and you can do some really neat things with them. Check out our blog post, An Introductory Guide to Salesforce Flow for Marketers, or the Flow Builder Basics Trailhead Module to get more familiar with Flows. 

Salesforce Starter Reporting and Performance

Salesforce Starter automatically collects and displays aggregate engagement data about your campaign on the Performance page. Common metrics, such as opens, clicks, unsubscribes, bounces, etc. can all be viewed in this prebuilt dashboard. 

To view the Performance of multiple Campaigns, navigate to the Performance tab. In this view you can filter your dashboard by date range, campaign(s), individual sends, send type, and even segments.

Salesforce Starter — easing small business marketers into CRM life

And there you have it! In summary, Salesforce Starter is a great way for SMBs to get started with CRM and Marketing Automation. As your company and familiarity with CRMs expands, you may outgrow this edition. But the great thing about Salesforce Starter is that you can avoid migration costs because your data is already in the Salesforce platform if you outgrow the product at any point. 

Reach out to the team at Sercante if you have any questions or need help figuring out if Salesforce Starter is the right tool for your team.

Original article: Salesforce Starter: Easing Small Business Marketers into a CRM

©2025 The Spot. All Rights Reserved.

The post Salesforce Starter: Easing Small Business Marketers into a CRM appeared first on The Spot.

The beginning of the year is an ideal time to have a reset on your Marketing Cloud contact strategy. That way, you can get your Marketing Cloud contacts in order, have an org cleanup, and create a future-proof strategy that will ensure those contacts within your org are serving a purpose (and you stay within your Marketing Cloud contact limit).

So where do you begin when it comes to developing a Marketing Cloud contact strategy? 

A Marketing Cloud contact is an individual added to any contact database within your Marketing Cloud instance. So, your Marketing Cloud contact strategy is the process you’ll create to make the most of your marketing efforts by focusing on promising contacts and letting go of contacts that aren’t helping your team reach its goals.

Step 1. Find out how many Marketing Cloud contacts you have purchased.

Every Marketing Cloud contract will have a contact limit. You can expect communication from your Salesforce Account Executive if you breach this limit, which can result in you needing to pay for more contacts. So it’s important to know what you’re working with. 

Refer to your Marketing Cloud contract to find how many contacts your license includes, or reach out to your Salesforce Account Executive to find out. 

Step 2. Find out how many contacts you currently have in Marketing Cloud.

Once you know the number of contacts you have purchased, you’ll want to find out how many contacts you currently have in Marketing Cloud. This will help you identify if a review or a cleanup is needed. 

Follow these steps to find out how many contacts you have in Marketing Cloud:

1. Go to Contact Builder > ‘All Contacts’ tab
2. From there, click ‘All Contacts’ for the total number to show up.

Alternatively, you can run a report that will show you how many contacts you have from each audience, such as Sales and Service Cloud leads, and contacts, per channel.

Keep your Marketing Cloud contact numbers handy

At this point you should have two numbers:

1. The number of contacts you are contracted to
2. The number of contacts currently in Marketing Cloud 

Review your Marketing Cloud contacts

The next step is to review your contacts. Think about:

• What they are doing
• Who they are
• If they should even be in Marketing Cloud (after all each contact comes at a cost)

From there, decide which ones you can remove from your org. 

Ask Yourself: Do all your contacts provide value to your business?

If you’re not sure how to make that decision, then check out this blog post where Sarah Smith explores the reasons why deleting your marketing contacts regularly is a good thing when you delete the right ones.

Step 3. Review Marketing Cloud contacts and complete your cleanup tasks.

A key part of a good contact strategy is ensuring you only have the contacts that are needed in Marketing Cloud. As part of your contact strategy, it’s important to evaluate your current contacts and perhaps have a clean-out. 

Check for Duplicate Records

One of the biggest reasons Marketing Cloud users go over their contacts limit is due to duplicate records. 

First, identify how many duplicates you have using SQL queries in Automation Studio. 

1. Identify how many duplicate records you have by following the instructions in this trailhead: Evaluate Your Contacts Unit 
2. Delete your duplicates – follow this Salesforce help article: Contact Delete Best Practices in Contact Builder

Bonus Duplicate Contact Tips

Identify the source of the duplicates: 

• Do you import contacts directly into Marketing Cloud?
  • This can sometimes cause an issue, particularly if you are also syncing records from Salesforce
  • You’ll end up with the “Salesforce version synced down” + the Marketing Cloud version you imported!  
• Review your Salesforce lead-sync approach
  • Syncing both leads and contacts can often cause duplicates in Marketing Cloud when a lead is converted into a contact, particularly if you’re using Salesforce Record ID as the unique identifier
  • Your lead record will have a lead ID and this lead will sync with a Marketing Cloud contact but when you convert that lead it will have a different ID, a contact ID thus creating a duplicate record in Marketing Cloud 
  • It is however best practice to use the Salesforce ID as  the unique identifier rather than email 
• Review your Salesforce records 
  • Are there duplicates here? If so then this could be causing duplicates in Marketing Cloud as well 
• Do you import records into Salesforce (manually or via a third party)? 
  • This could cause duplicate records in Salesforce and therefore Marketing Cloud

Review contacts that do not have an assigned channel address

Assigned channels are things like email, mobile, ad studio, and any channel within Marketing Cloud that uses your contacts to target. If you have contacts that do not have a channel address, then these are likely to be a good candidate for removal. These types of contacts often get into Marketing Cloud because of the Marketing Cloud Connector [Keep reading to implement a solution that minimizes the “wrong” records being synced into Marketing Cloud from Salesforce!]

Identify if your contacts do not have an “assigned channel.” Why? If they don’t have an assigned channel then you haven’t “used them” in your marketing campaigns:

1. In Marketing Cloud, navigate to Automation Studio.
2. Click the Activities tab, then click Create Activity.
3. Select Data Extract and click Next.
4. Add a name, external key value, and a file naming pattern. The file naming pattern value doesn’t actually affect anything, because all results go into a Contacts Without Channels data extension in the root folder of the account.

Remove contacts that are not right for your business

If you have been letting everyone into your Marketing Cloud org, then chances are some folks just shouldn’t be there (for example, competitors or spam submissions). As part of your contact strategy, it’s important to define the purpose of Marketing Cloud for your business. If it’s only to engage with leads and customers, then you could remove staff, partner, and competitor contacts.

Use SQL and Automation Studio to identify any contacts that do not meet your criteria (for example, if they do not have a “client” or “lead status” or if they have your business email address). Add these contacts into a non-sendable data extension and then delete them. 

Step 4. Implement the right processes to keep a clean Marketing Cloud contact database moving forward.

Below are some suggestions to help when creating your Marketing Cloud contact strategy so it’s an easy lift for your team and you avoid over-limit surprises.

Think about the ways Marketing Cloud fits into your overall business goals

Start with the right foundation. Evaluate the ways your marketing and business goals align with your team’s use of Marketing Cloud.

Who are your audience personas? And who are you connecting with through Marketing Cloud? Your list may include:

• Leads
• Customers
• Partners

Putting this on paper may help you prioritize your contact usage and determine the ‘nice to haves’ versus the ‘need to haves.’

Determine how you’ll segment your Marketing Cloud contacts

From there, create segments for each group of contacts:

• Those who are highly engaged and likely to purchase
• Those who may need a little more encouragement 
• Those at the start of their journey who need a lot more nurturing 

You can follow Cara Weese’s blog post Audience Segmentation Strategies for Salesforce Marketers for guidance on segmenting your contacts in Marketing Cloud.

Once you have your segments, create a Content Strategy for each. Then, you can develop messaging strategies for each of your audience segments.

Control how Marketing Cloud syncs contacts with Salesforce

This one is for Marketing Cloud Connect users. If you use Marketing Cloud Connect with Salesforce, create a ‘Sync to Marketing Cloud’ field in Salesforce.

• Develop a list of criteria for who should be in Marketing Cloud. For example, everyone should at least have an email address or mobile number, and everyone should be mailable and be opted into emails and/or texts.
• Use a Salesforce flow to check the Sync to Marketing Cloud field
• Select the field in Marketing Cloud as the sync criteria. 

You can also use a single unique identifier, such as Salesforce ID, to match Marketing Cloud records to Salesforce records. 

Other contact strategy tips

• Create contact count reports and build a process to ensure your team is monitoring them regularly. This can be as simple as setting a monthly calendar reminder to check the contact report.
• Build a process in Automation Studio via a script to remove contacts. This avoids manual deletion in the future.

Future-Proof Your Marketing Cloud Contact Strategy 

Remember, there’s no one-size-fits-all when it comes to creating a Contact Strategy, it needs to be specific to your business and your goals. However, there are steps you can follow to create a future-proof plan that will ensure all your contacts serve a purpose in Marketing Cloud:

• Know your limits.
• Keep your data clean.
• Implement automation to manage your contacts.
• Review and reiterate continuously — your plan needs to grow as your business does!

Need help with creating a contact strategy for your marketing automation platform? Get in touch with the team at Sercante to get the ball rolling.

Original article: 4 Steps to Create a Marketing Cloud Contact Strategy

©2025 The Spot. All Rights Reserved.

The post 4 Steps to Create a Marketing Cloud Contact Strategy appeared first on The Spot.