Salesforce Business Analysts (BA) are changing how they write user stories, as new AI features and smarter tools take over tasks that used to need clicks and buttons. With new features that can suggest actions, answer questions, and make decisions based on past activity, many projects are becoming more dynamic and data-driven. As a result, BAs need to think beyond traditional requirements and learn how to design stories that support these smarter, automated actions.

This change affects how Salesforce Business Analysts work.

In the past, the main focus of Salesforce BA was on writing clear Salesforce user stories. These stories described what the user needed and helped admins and developers know exactly what to build. That approach still matters. But today, many Salesforce features rely on data to decide what to do. When that happens, the story needs to be more than just a request.

You may need to explain which records are involved, how the system should respond in different cases, and what success looks like. You may also need to check if the right data even exists yet.

As shown in the image, User Stories make up 18% of the questions on the Salesforce Business Analyst Certification exam. Learning how to write strong user stories is essential because they help teams understand what to build, ensure the solution meets business needs, and play a key role in successful project delivery.

Salesforce Business Analyst certification topics

Image from FocusOnForce

How Salesforce user stories are changing for BAs

Salesforce keeps growing, and with each release, more features respond to what is happening in real time. These features do not wait for a user to click a button. They act based on patterns, timing, or trends in the data.

Think about tools like:

• Case routing based on urgency or past activity
• Sales alerts when an Opportunity stalls
• Recommendations to update, escalate, or follow up

These are not simple requests. They are built on rules, signals, and models that look at data and decide what to do next. When writing user stories that support intelligent, automated, or data-driven features in Salesforce (like Flows or Agentforce), make sure to clearly define:

• Who: From whose perspective is this story written? Define the user persona inside Salesforce, such as a Sales Rep, Customer Care Agent, or Field Technician.
• What: What action, functionality, or automation should happen? Be specific about what the user wants to do or what should be implemented in the org.
• Why: What’s the business or user reason behind this request? This keeps the team focused on outcomes, not just systems.

For example (AI-Ready Story):

“As a Customer Care Representative,
I want to automatically take ownership of new cases and communicate with customers,
so that I can deliver high-touch customer experiences without delays.”

That is why the way we write stories is changing.
The user is still at the center. But now, you also write for the system that acts on their behalf.

If you are a Business Analyst, it is not enough to describe the button. You need to describe the logic behind the button. That is what makes today’s user stories Salesforce teams write differently from the ones you have written before.

When to write data-driven stories

Not every Salesforce user story needs data logic, but some features work only when the system reads and reacts to patterns. These are the cases where you need more than steps, you need to describe how the system should “think.” Below are common signs that your story should focus on data.

1. The action depends on timing, like “no update in 7 days”

When the system reacts based on time, not on clicks, the story needs to include how long to wait and what counts as an update. Without this detail, developers and admins will not know when to trigger the process.

2. The decision depends on a score, such as lead quality

If the system makes a choice using a rating or score, the story should explain what that score means and how it is used. Scores are not always self-explanatory and may be calculated elsewhere.

3. The records need filters, like “only open deals over 10,000”

When your feature applies to a subset of records, your story must list the exact filters. Teams cannot guess which records count. Be clear about values, ranges, and any exceptions.

4. The system acts without direct user input

If no one clicks a button, the system needs instructions on when to run and what to check. This is common in automated flows or alerts. Stories like this must describe the triggers clearly.

5. The data may be missing, unclear, or wrong

In real life, data is often incomplete. If your story relies on clean data, it must also say what to do when values are missing, dates are blank, or numbers look wrong. This prevents confusion later.

Writing clear data-based stories is a crucial part of creating a Salesforce business requirements document. It helps bridge the gap between what users expect and what the system will actually do.

How to write stories that support data-based features

For Business Analysts, writing data-based stories means thinking beyond the user’s action and focusing on how the system should respond. These stories should provide enough detail to help developers and admins build solutions that can work with changing data, handle exceptions, and deliver accurate results, aligning with the Salesforce business requirements. Here’s how to create clear and actionable data-based stories:

Focus on the data

Your story should clearly describe what data needs to be involved. This includes not just the records that will be used, but also how the data will be evaluated.

For example:

“Create a task if a lead has no contact activity for 30 days”
What does “activity” mean in this case? A phone call? An email? An opportunity update? Make sure these details are specified in the story.

Define triggers and rules

Clarify when the system should take action. Will it check data on a regular schedule or when a specific event happens? Will it act based on a rule, like a score or threshold?

For example:

“If the opportunity amount exceeds 10,000, send an alert.”
This story isn’t enough unless you define the exact condition and what the system should do when the amount is above the threshold.

Use examples and edge cases

Include real-world examples and potential edge cases in the story. What happens if data is missing, or records don’t fit the expected pattern? Be clear about the edge cases, so developers can handle them properly.

For example:

“If there’s no contact associated with the opportunity, do not send the alert.“
This is an edge case that needs to be addressed to avoid unexpected outcomes.

Stay focused on the user’s needs

Even though your story deals with data logic, it should still focus on the user’s needs. Don’t lose sight of the fact that these features exist to serve a purpose. Your job is to make sure that the purpose is clear and achievable through data.

For example:

“The system should prioritize sending follow-up tasks for high-value leads that have gone cold for 7 days”
This story shows the value of the feature in a way that’s easy for both the team and the user to understand.

Leverage Salesforce Agentforce 

These tools can assist in automating and optimizing the flow of data-driven stories. For instance, Salesforce Copilot Einstein (now part of Agentforce) uses AI to analyze historical data and predict the right course of action. It can help you define decision criteria and triggers, making it easier to write effective stories. Similarly, Salesforce Copilot AI can streamline data processing, offering recommendations based on past patterns and helping teams identify relevant trends or gaps.

Using templates and checklists for data-based stories

Creating data-based stories can become complex due to the many variables and conditions involved. To simplify the process and bring more consistency to your work as a BA, using templates and checklists can be incredibly helpful. They act as guides to ensure you don’t miss any critical elements, and they can streamline the handoff process between business analysts, developers, and admins.

Templates for data-based stories

Templates are useful because they provide a standardized structure, making it easier to focus on the details that matter. You can develop your own template or use an existing one from your team. Below is an example of a simple template you can adapt to your needs.

Story template example:

• Title: [Short descriptive name of the feature]
• User: [Who is the intended user? Example: Sales Representative, Customer Support Agent]
• Goal: [What is the user trying to accomplish? Example: Assign leads based on region.
• Data Input: [What data will the system use? Example: Lead region, Lead priority]
• Trigger Conditions: [When should the action happen? Example: If a lead has been in the system for more than 48 hours without being assigned]
• Data Rules: [Any specific rules or logic that must apply? Example: Assign leads in the North region to the ADR team, leads in the South to Sales reps.
• Edge Cases: [What should the system do if certain conditions are not met? Example: If the region is not specified, assign the lead to the default team.
• Outcome: [What should happen after the system processes the data? Example: The lead is assigned to the correct team.

By using templates, business analysts can ensure that every data-based story has all the necessary details.

Checklists for data-based stories

Checklists are equally important for ensuring that every element of a data-based story has been covered. They act as reminders of common data issues, edge cases, and possible conditions that should be considered. Below is an example checklist you can follow.

Checklist for data-based stories:

• Have I defined the specific data that the system will use?
• Are the trigger conditions clear? Does it specify what action will be taken and when?
• Have I considered edge cases and missing data?
• Is the story focused on the user’s goal?
• Is the outcome of the action clearly defined?
• Are the rules for filtering and processing data well understood?
• Have I used Salesforce Agentforce or Salesforce Copilot AI where necessary to enhance the process?

Best practices for reviewing and handoff

Image from FocusOnForce 

As a Business Analyst, it’s essential to review your data-based user stories and hand them off properly to development and admin teams, ensuring they align with Salesforce’s business requirements. Here’s how you can make the review and handoff process more efficient.

1. Review for completeness and clarity

When reviewing a data-based user story, ensure data definitions are clear, triggers and conditions are well explained, and edge cases are addressed. The outcome should be clearly stated so developers know what success looks like. Clear, detailed stories prevent errors and ensure the right solution is built.

2. Collaborate with developers and admins early

The earlier you bring in the developers and admins, the better. Having them involved during the story-writing phase can help prevent misunderstandings later. If possible, collaborate during the drafting stage and ask for feedback on the feasibility of the stories. You can also get their input on technical constraints and the way data should be handled, which can save time in the long run.

3. Leverage Salesforce Agentforce

Use Copilot tools to review your data-based stories more effectively. For example, you can ask Copilot Einstein to summarize trends from past Opportunities, identify which conditions typically trigger escalations, or suggest logic for Flow decisions. You can also prompt Copilot to check whether key data exists in the org for your story to work as expected. These tools won’t write or validate user stories for you, but they can help spot missing data, unclear triggers, or opportunities to automate.

4. Focus on clear communication

When handing off a user story, communication is key. Ensure that the development team has all the context they need to understand the story’s purpose. If there’s any ambiguity in the requirements, now is the time to clear it up. You may also want to organize a meeting with the team to walk them through the most important aspects of the story.

5. Use test cases and acceptance criteria

Test cases and acceptance criteria help ensure that the solution built will meet the original goals. These are the conditions that must be met for the story to be considered complete. Writing clear, testable acceptance criteria ensures that developers know exactly what is expected when they’re implementing the solution.

For example:

• Test Case 1: If a lead has no activity for 30 days, create a task for follow-up.
• Acceptance Criteria: A task is created if the lead has not been contacted via email, phone, or meeting for 30 days.

This adds transparency to the handoff process and helps developers stay on track.

6. Document any changes during the review process

If changes are made to the original user story during the review process, be sure to document them. This ensures everyone is on the same page and helps avoid confusion later on. Version control is especially helpful here, as it allows teams to compare versions and see what has changed.

Final thoughts on writing data-based user stories

Writing data-based user stories is essential for creating intelligent, data-driven solutions that support automation, decision-making, and efficient workflows in Salesforce. By focusing on clear data for AI Salesforce, well-explained triggers, and handling edge cases, you ensure your stories align with the needs of both developers and admins. This approach not only streamlines the build process but also results in more reliable and actionable outcomes.

As a Business Analyst, it’s important to continue refining how you write user stories. The tools available within Salesforce, like Agentforce, make it easier to incorporate AI and automation into your user stories. The key is to always stay focused on the data and how it drives actions within the Salesforce platform.

By adopting these practices and using the templates and checklists provided, you’ll be well on your way to crafting powerful data-based user stories that drive the success of your Salesforce projects.

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