Before completing evaluations, make sure your scorecards and scoring models are already set up. These define what will be measured and how each interaction is scored.

To learn how to build a scorecard, see Building your Scorecard Structure.
To learn more about scoring methods, see Understanding Scoring Models.

Once your scorecards are complete and published, you can begin completing evaluations—either manually through a quality analyst or automatically through AI—to capture insights, measure consistency, and drive meaningful coaching discussions.

Begin Evaluation

To begin an evaluation, you must first select the agent you will be evaluating and the scorecard you want to use.

There are four ways to start a new evaluation and select both the agent and scorecard:

• Users – Start an evaluation directly from the user list by selecting an individual agent.
• Teams – Begin an evaluation from the team view to evaluate an agent within a specific team.
• Scorecards – Start an evaluation by choosing a specific scorecard first, then select the agent.
• Evaluations – Start an evaluation from the Evaluations page, either by repeating a previous evaluation using Evaluate Again or by creating a new one with + New Evaluation.

Users

To start an evaluation from the Users menu, go to the Organization section and select Users. Locate the user you want to evaluate, then click the Action icon at the end of their row and select Evalaute.

A session setup window will appear with the selected user already pre-populated. From there, choose the scorecard you want to use for the evalaution.

Teams

To start an evaluation from the Teams menu, go to the Organization section and select Teams. Locate the team you want to view, then click the Action icon at the end of the row and select View. This will display all users assigned to that team.

Find the agent you want to evaluate, click the Action icon at the end of their row, and select Evaluate. A session setup window will appear with the agent pre-populated. Choose the scorecard you want to use, just as you would when starting an evaluation directly from the Users menu.

Scorecards

To start an evaluation from a specific scorecard, go to the Quality menu and select Scorecards. This will display all available scorecards. Locate the form you want to use, then click the Action icon at the end of the row and select Evaluate.

An evaluation setup window will appear with the selected scorecard already pre-populated. You will then be prompted to choose the agent for the evaluation. A selection window will open where you can select only one agent to coach.

Evaluations

The final two ways to start an evaluation are from the Evaluations page.

• Evaluate Again
  • Use this option to repeat a previous evaluation with the same agent and scorecard. Go to the Evaluations page, locate the completed evaluation you want to repeat, click the Action icon at the end of the row, and select Evaluate Again. A new evaluation will open with the same agent and scorecard pre-populated, allowing you to continue evaluating the agent.
• + New Evaluation
  • You can also start a brand-new evaluation directly from the Evaluations page. Click the + New Evaluation button to open a new evaluation setup window. You will need to select both the agent and the scorecard you want to use before beginning the evaluation.

Completing an Evaluation

Evaluations can be completed in two ways: Manual or AI.

Each scorecard has two main sections—Meta Data and Scoring (or Audit)—and the process for completing these sections differs depending on the evaluation type.

Manual Evaluations

In a manual evaluation, the quality analyst completes all fields directly.

Meta Data fields are free-form inputs used to capture information that is not tied to a specific Yes/No or Selective response. These may include details such as call reason, unique ID, or other contextual information entered by the analyst.

The Scoring/Audit section contains the measurable criteria defined by the scorecard’s scoring model. Depending on the model, responses will be one of the following:

• Yes / No / N/A – for Weighted, Equal, and Audit models
• 0 / 1 / 2 / N/A – for Selective models

Each scoring or audit section also includes a + Notes option. Analysts can enter notes to provide context or specific feedback for each section. These notes appear on the final evaluation for both the manager and agent to review.

AI Evaluations

In an AI evaluation, both the Meta Data and Scoring/Audit sections are completed automatically by the AI.

After selecting the agent and scorecard, the evaluator will be taken to the Upload Calls page. From there:

1. Click Upload to upload one or more calls.
2. Assign each uploaded call to the correct agent.
3. Once all calls are uploaded and assigned, click Evaluate to begin the AI evaluation process.

The AI will transcribe each call into a readable transcript, then compare that transcript against the scorecard criteria using the AI scoring instructions. The evaluation will appear as Pending until the process is complete.

Coaching Session

Once either the manual or AI evaluation is completed, it is automatically sent to the evaluator or assigned manager for coaching.

The manager will see the entire evaluation, can complete the coaching session, and record commitments or feedback. The completed evaluation and coaching session will then appear on the agent’s dashboard for review.

Note: Evaluations using the Audit scoring model are for data collection only. They do not generate a coaching session or appear in the manager’s queue but remain accessible for reporting and trend analysis.

One of the best ways to consistently improve the customer experience is through a Quality Assurance (QA) program—and every QA program starts with a scorecard.

A QA scorecard measures and grades how agents handle customer interactions. It’s built on your company’s values and service standards and forms the foundation of your QA program. A strong scorecard helps contact center agents deliver consistent, high-quality experiences that directly impact satisfaction and loyalty.

Creating a scorecard that quantifies human-to-human interactions isn’t easy—but it’s absolutely possible. Here are four tips to help you build one that works.

Find Balance

When creating scorecard criteria, many contact centers overemphasize policies and procedures while overlooking what matters most to the customer experience. Both sides are important—you need to protect the company’s interests while still focusing on the customer’s needs.

I worked with a large hospitality client facing two challenges:

1. Rising credit card chargebacks that threatened their ability to process payments.
2. A high number of guests accidentally booked at the wrong hotel.

To solve both, we built a verbatim confirmation script into the CRM. Agents had to read it before completing any booking. Chargebacks labeled as fraud dropped significantly, and customers stopped ending up at the wrong location.

Scorecards should absolutely support processes like this—but that shouldn’t be their sole purpose. A scorecard must balance business needs and customer experience. At the end of each interaction, you should be able to answer “yes” to both:

• Would this customer, regardless of the outcome, return or refer their friends?
• Was the company’s value preserved and the company’s interest protected?

Make It Simple

Simplicity is key—for both the evaluator and the agent.

Whether an interaction is evaluated manually by a quality analyst or automatically by AI, the scorecard should focus only on what truly matters. The goal is to measure performance accurately without overcomplicating the process.

For manual evaluations, too many criteria can slow analysts down and make it difficult to complete evaluations efficiently and consistently. A concise scorecard helps analysts focus on what’s most important and provide actionable feedback faster.

For AI-driven evaluations, simplicity matters even more. Each criterion must be clearly written and measurable so the AI can evaluate it precisely. Ambiguous or overly complex items increase the risk of misinterpretation and reduce accuracy.

The same principle applies to agents. The fewer—and clearer—the criteria, the easier it is for them to focus on improving the behaviors that create the optimal customer experience. A well-structured, simple scorecard leads to faster evaluations, consistent outputs, and more meaningful coaching conversations.

Clearly Define Scorecard Criteria

Ambiguity kills consistency.

Imagine telling an agent, “Change your tone.” What does that mean? Without examples or context, it’s meaningless. A clearly defined scorecard eliminates that ambiguity.

Each criterion should describe what good looks like. Consider building a reference guide that explains expectations and includes examples for evaluators and agents. This ensures everyone scores and interprets criteria the same way—making feedback actionable and fair.

For example, in a Selective Scoring Model, you might define:

• Full (2 points): The agent used multiple open-ended questions to understand the customer’s needs.
• Partial (1 point): The agent asked superficial questions but didn’t probe deeply enough.
• None (0 points): The agent made no effort to identify the customer’s needs.

Specific definitions like these reduce confusion, speed up calibration, and improve accuracy and coaching quality.

Be Willing to Change

Your scorecard doesn’t have to be perfect on day one—and it shouldn’t be. As your technology, customers, and market evolve, your scorecard should evolve too.

I once worked with a client transitioning from a Weighted scoring model to a Selective model. Selective scoring focuses on consistency—every criterion carries equal weight, but agents earn points based on how well they meet each standard (think good, better, best).

We tested the new model with a small group of teams to compare results. The goal was to increase CSAT without hurting conversion rates or quality scores. If CSAT rose while performance stayed the same or improved, we considered it a win. The results were strong enough that we rolled out the new scorecard organization-wide.

The lesson: don’t be afraid to experiment. A scorecard is a living framework. Test, learn, and adjust until it drives the business outcomes you want.

Find the Right Tools

Your QA scorecard determines the direction and success of your quality program. Following the four tips above sets the foundation—but the right technology ensures long-term success.

Choose a platform that supports both manual and AI QA to create a complete, adaptive quality ecosystem. Manual QA allows analysts to review complex, high-value interactions that require human judgment, while AI QA ensures every interaction is evaluated consistently and at scale. Together, they provide both depth and coverage.

Look for a solution that allows you to:

• Build fully customized scorecards aligned with your business and customer needs.
• Evaluate interactions through both manual and AI-driven methods.
• Create consistency across every channel and interaction type.
• Conduct quality audits on an individual, team, or organization-wide level.
• Surface trends, coaching topics, and performance analytics to drive continuous improvement.

FiveLumens is a performance enhancement platform that brings training, coaching, and quality together in one place. It helps teams identify opportunities, automate evaluations, and coach effectively—creating a true closed-loop improvement system.

In FiveLumens, every scorecard is structured into sections and criteria that connect to a selected scoring model. This structure allows you to evaluate both customer experience and compliance items with consistency and accuracy.

This article explains how to build a scorecard, including adding sections, creating scoring criteria, selecting a scoring model, and linking your coaching form before publishing.

Scorecard Settings

After entering the name, description, and selecting the groups assigned to your scorecard, you will complete the remaining scorecard settings. These settings determine how evaluations are completed, scored, and used for coaching. There are five key settings to review before continuing.

1. Evaluation Type
   Choose between AI and Manual.
   • Manual evaluations are completed by a quality analyst who listens to the interaction and enters responses directly.
   • AI evaluations are completed automatically by the system using an AI scorecard and AI grading instructions.
     The structure is the same for both types, but the process differs.
2. Scoring Model
   Select which scoring model the scorecard will use. The options and definitions for each model are explained in the Understanding Scoring Models article.
3. Coaching Form
   Each scorecard must be linked to a coaching form. The evaluation—whether completed manually or by AI—will be sent to the assigned manager to coach using the connected form.
   If you have not created a coaching form yet, do so before building your scorecard. This is a required field for publishing.
4. Visible to Manager Only
   When enabled, the evaluation will only be visible to managers. This also marks the evaluation as for coaching purposes only, meaning it still records a score but does not count toward quality or compliance metrics.
5. Coaching Purposes Only
   This setting designates the evaluation for coaching use only. Like the option above, it still records a score but excludes it from the agent’s overall quality or compliance averages.

Note:
If the Audit scoring model is selected, these additional settings—Coaching Form, Visible to Manager Only, and Coaching Purposes Only—will not appear. The Audit model is used solely for data collection and does not generate scores or coaching actions.

Scorecard Builder

The scorecard builder is where you define the structure and content of your scorecard. Each scorecard is divided into two main sections: Meta Data and Scoring. For Audit scorecards, the Scoring section is renamed Audit, though it functions the same way.

The Meta Data section is used to capture information that is not part of the scoring process. Think of it as a space for internal notes or observations. Any data entered here is visible only to administrators and is never shared with agents.

The Scoring section is where evaluation criteria are added and scored according to the selected scoring model. This section determines how performance is measured and how results contribute to QA and coaching.

The next sections explain how the Meta Data and Scoring areas differ for Manual and AI scorecards.

Meta Data Comparison

The Meta Data section allows you to capture information that supports your QA process but is not part of the scoring. To add fields, go to the Action Items menu at the end of the Meta Data section header and select the field type you want to include.

Manual Scorecards

For manual scorecards, you can add up to five Meta Data types:

• Single Select
• Multiselect
• Small Text
• Large Text
• Date

Each field serves a specific purpose. Single Select and Multiselect function the same way they do in coaching forms. You can refer to the Create and Edit Coaching Forms article for a refresher.

The difference between Small Text and Large Text is simply the number of characters allowed when entering data during the evaluation. Date adds a date selector field.

When you select a Meta Data type, a modal will appear where you must enter the required information. Once complete, the field will populate to the scorecard.

Common uses for Meta Data include capturing details such as the main reason for a cancellation call, a unique ID associated with the interaction, or the date the interaction occurred. This information is for internal reference and is never visible to the agent.

AI Scorecards

For AI scorecards, the Meta Data section works differently. There are no predefined field types. Instead, when you enter a description in the modal, the system automatically adds it to the scorecard.

The key difference is that you must also provide AI instructions. These tell the AI what information to extract and how to present it. For example, if you want the AI to identify all reasons for cancellation mentioned during a call, your instructions should list possible reasons and specify the output format, such as “Return a list of reasons separated by commas.”

AI will only perform exactly what it is instructed to do. If directions or output formats are unclear, the AI may generate incomplete or inaccurate results. Always provide specific, detailed instructions and clearly define the desired output.

Scoring Comparison

The Scoring section is where you define the measurable behaviors and standards for your evaluation. It is divided into sections, which help you organize and categorize scoring criteria. For example, you might create separate sections for Sales Skills, Compliance, Call Opening, or Procedures.

To add a new section, click the Action icon at the end of the Scoring section header and select Add Section. Enter the section name and save it. You can edit or delete sections at any time using the same Action menu.

The order of sections does not matter during setup. You can move sections up or down in the scorecard at any time, and there is no limit to how many sections you can add.

Once a section is created, go to the Action icon for that section and select Add Scoring Criteria. This is where you define the criteria description, which appears to both admins and agents in the evaluation view.

At the bottom of each scoring criterion, you’ll find a toggle to designate the item as an Auto Fail. In FiveLumens, Auto Fails are set at the criteria level, not at the section level. This provides flexibility in scorecard design. For example, you may want a verbatim opening statement to be an auto fail placed at the start of the scorecard, following the natural call flow rather than being grouped in a compliance section.

After adding a scoring criterion, you can edit or delete it within that section at any time.

Manual Scorecards

For manual scorecards, you only need to enter the criteria description and determine whether it should be marked as an Auto Fail. Once added, the criterion will appear on the scorecard under the selected section, displaying the scoring model assigned to the overall scorecard.

AI Scorecards

For AI scorecards, the process is almost identical. You add the criteria description and choose whether to designate it as an Auto Fail. However, similar to Meta Data fields, you must also provide AI instructions that guide the system on how to evaluate and score that criterion.

These instructions tell the AI what to look for in the transcript and how to determine a Yes, No, or N/A response. The upcoming article, Creating AI Scorecard Instructions, will explain how to write precise and effective instructions to ensure consistent grading results.

Save Options

After you’ve built your scorecard and added all necessary sections, criteria, and settings, you can choose to either Save Only or Save and Publish your work.

Save Only

Selecting Save Only stores your scorecard in a draft state. This option allows you to continue editing, reviewing, or testing the scorecard before making it active. You can save as many times as needed while you build. Use this option anytime you are still working on the content, refining instructions, or waiting for supporting components like coaching forms to be finalized.

Save and Publish

Choosing Save and Publish makes the scorecard active and available for evaluations. Once published, the structure of the scorecard—such as sections, criteria, and scoring models—can no longer be edited or deleted, as it becomes part of your QA records.

However, scorecard settings (for example, group assignments, visibility, and coaching form linkage) can still be updated after publishing. This allows for flexibility in managing access and usage without altering the evaluation framework.

Before publishing, double-check every detail, including criteria accuracy, scoring model, and attached coaching form. If major changes are needed after publishing, the best practice is to clone the scorecard, make the necessary adjustments, and publish the updated version as a new active scorecard.

Building your scorecard is one of the most important steps in creating a consistent and effective QA process. The structure you design here defines how performance is measured, how insights are generated, and how coaching is guided.

Take the time to plan your sections, criteria, and AI instructions carefully before publishing. Remember, once published, only the settings can be changed—not the structure. A well-built scorecard creates alignment between QA, coaching, and continuous improvement, ensuring every evaluation leads to meaningful action and development.

Each AI scorecard in FiveLumens includes scoring criteria (used for Yes/No or Selective questions) and meta data fields (used to extract additional insights such as reasons, dates, or identifiers). Both require clear, structured instructions that tell the AI exactly what to look for and how to format its output.

Our Customer Success team can work directly with you to help design and refine these instructions, ensuring they align with your business goals and evaluation standards. However, this guide provides a simple framework should you wish to begin creating them on your own.

AI Scoring Instructions

For scoring criteria, the AI uses your written instructions to determine whether the correct response is Yes, No, or N/A. Each criterion includes structured fields in the prompt generator:

• Use Case – Required. Describes what is being evaluated and how the AI should interpret it.
• Yes Exceptions – Optional. Lists any cases that still count as “Yes,” even if they don’t perfectly match the rule.
• No Exceptions – Optional. Lists any cases that count as “No,” even if they seem partially correct.
• N/A Exceptions – Optional. Lists cases where the question doesn’t apply.

When writing AI scoring instructions, describe the intent of the question, the behaviors to look for, and what qualifies as each answer option. Be specific and avoid assumptions—the AI will only do what you instruct it to do.

Example: (Yes/No/N/A)

Question: Did the client call to cancel their account?
Use Case: Determine if the client called to cancel their account. Look for different ways the client could express a desire to cancel. 
Answer “Yes” if the client mentions at any point in the call that they want to cancel their account. 
Answer “No” if the client is not requesting a cancellation.
Answer “N/A” if cancellation is never mentioned.

Yes Exceptions: None
No Exceptions: If the client is calling to check the status of a previous cancellation, answer as “No.”
N/A Exceptions: None

AI Meta Data Instructions

Meta Data fields differ from scoring criteria. Instead of evaluating Yes/No/N/A responses, these instructions tell the AI to extract or summarize specific information from the transcript.

When creating Meta Data instructions, focus on:

1. What you want the AI to find or list (e.g., reasons, dates, product types, issue categories).
2. How you want the output formatted (e.g., list separated by commas, one phrase, or short paragraph).

Be explicit in describing the output so the AI produces consistent and usable data.

Example: (Meta Data Extraction)

Meta Data Field: Cancellation Reasons
Use Case: Identify all reasons the customer gave for canceling their account. Review the transcript and list each distinct reason mentioned.
Output Format: Return a comma-separated list of cancellation reasons. Example: "Too expensive, Found a better deal, No longer needed."

Best Practices

• Always write clear and direct instructions—avoid vague terms like “good tone” or “handled well.”
• Include examples of what qualifies for each answer.
• For Meta Data, specify both the information type and the exact output format.
• Review AI results regularly to fine-tune your instructions for accuracy and consistency.

Creating strong AI scoring and meta data instructions is essential to achieving accurate and consistent evaluation results. Well-written instructions ensure that the AI understands your intent, applies your standards correctly, and produces data you can trust.

Start simple—focus on clarity, structure, and precision—and refine over time as you review AI outputs. And remember, our Customer Success team is always available to help you design, test, and optimize your AI prompts to ensure your scorecards deliver the best possible insights.

Managing scorecards effectively ensures accuracy and consistency across all evaluations. From creation to publishing, and from activation to deletion, each step plays an important role in maintaining a reliable QA process.

This article explains how to create, publish, manage, and delete scorecards in your account.

Create

To create a new scorecard, go to the Quality menu, select Scorecards, and click the blue Add Scorecard button.

For detailed setup steps, see the Creating a Scorecard article.

You can also create a scorecard by cloning an existing one. Go to the end of the row of the scorecard you want to clone, click the Action icon, and select Clone. Other than the name and description, all scorecard settings and structure will be an exact duplicate to the original. Enter a new name, description, and any changes to the existing scorecard. The scorecard is in edit mode until you are satisfied with your changes and publish it.

Publish and Status

To ensure you do not lose your progress while building a scorecard, click the Save Only button. This saves all changes made up to that point.

Once your scorecard is complete, it must be published before managers can use it for evaluations. Click Save & Publish to publish the form. A confirmation window will appear asking you to confirm. When published, the form status will change to Active, and it will be available for use in evaluations.

Note:
It’s important to remember that once a scorecard is published, its structure cannot be changed.
You can still update the name, description, or assigned groups, but all other settings and scorecard structure can not be changed.

You can change a scorecard’s status between Active and Inactive at any time. Deactivating a scorecard does not delete it, but it cannot be used for new evaluations while inactive.

To use the scorecard, switch its status back to Active, and it will become available for new evlauations.

Delete

A scorecard can only be deleted if no evaluations have been completed using it. Once a scorecard has been used in any evaluation, it becomes part of the QA record and cannot be removed.

To delete an eligible scorecard, go to the end of the scorecard row, click the Action icon, and select Delete. A confirmation pop-up will appear asking you to confirm your choice. Once confirmed, the scorecard will be permanently deleted and cannot be recovered.

If the scorecard has been used in evaluations, the Delete option will be disabled. In this case, you can make the scorecard inactive instead to prevent future use while preserving past evaluation data.

Evaluate

After your scorecard is saved and published, you can begin using it for evaluations.
There are five ways to start an evaluation:

1. Teams
2. Users
3. Scorecards
4. Add Evaluations
5. Previously Completed Evaluations

Each method offers a different entry point for creating and managing evaluations. These are explained in detail in the Using Evaluations article.

Managing scorecards carefully ensures your QA program remains accurate, consistent, and aligned with your organization’s goals. Each step—from creation to publication—affects how evaluations are completed and how coaching insights are generated.

Before publishing, always review your scorecards for accuracy and completeness, and use inactive status when retiring older versions to preserve evaluation history. Proper scorecard management keeps your QA process organized and supports a continuous cycle of evaluation, feedback, and improvement.

Both manual and AI evaluations use the same scorecard structure. Manual evaluations are completed by analysts, while AI evaluations apply AI instructions to automatically grade transcripts. AI scorecards support the Weighted, Equal, and Audit models. The Selective model is only available for manual evaluations.

Accounts can create and use an unlimited number of scorecards and can mix manual and AI types as needed. The following articles explain each scoring model in more detail.

Selective Scoring Model

The Selective Scoring Model is available only for manual scorecards and is used when a simple Yes or No answer does not fully capture performance. This model allows evaluators to choose between N/A, 0, 1, or 2 points, providing a more flexible range of assessment for qualitative behaviors.

Many organizations use this model to represent levels of performance, such as None (not good), Partial (good), and Full (best). It is especially useful for criteria where effectiveness varies by degree or effort rather than a strict presence or absence.

Example

Criteria: Did the agent use multiple open-ended probing questions to understand the customer’s needs?

This model provides greater nuance in evaluations and helps analysts identify areas of partial success or progress, not just compliance or noncompliance.

Weighted vs. Equal Scoring Models

Both the Weighted and Equal scoring models use a Yes, No, or N/A format to assess criteria. The difference between them is how points are distributed across the scorecard.

Weighted Scoring allows each question to carry a different level of importance. Administrators can assign specific point values to each criterion so higher-impact behaviors or compliance items have more influence on the final score. This model is best used when some actions are more critical to the customer experience, compliance, or brand standards than others.

Equal Scoring gives every question the same value. Each criterion contributes equally to the total score, regardless of its topic or category. This model provides a simple, consistent approach that works well for general evaluations or when all standards are considered equally important.

Example
If a scorecard includes five questions and one is deemed more important, the Weighted model might assign it 30% of the total score while the remaining four share the other 70%. In an Equal model, each question would simply count for 20% of the total.

Use Weighted when you want to emphasize key criteria and Equal when you prefer a straightforward, balanced scoring approach.

Audit Scoring Model

The Audit Scoring Model functions like the Equal model in structure, using Yes, No, or N/A responses for each criterion. However, the key difference is that Audit evaluations do not produce a score and are not attributed to an agent’s performance.

This model is designed for gathering insights rather than measuring individual results. It allows you to use a scorecard format to collect consistent data across specific call types or scenarios without affecting performance metrics.

For example, an organization might run an audit on closed sales calls to identify which sales techniques are most often used in successful conversions. Conversely, another audit could focus on non-sales calls to uncover missed opportunities or areas for skill development.

Audits are ideal for research, process analysis, and identifying patterns or training opportunities across large sets of interactions without influencing QA scores or coaching outcomes.

Choosing the right scoring model helps ensure your evaluations align with your organization’s goals. Whether you need detailed behavioral insights, consistent compliance checks, or data-only analysis, each model offers a specific purpose. Weighted and Equal provide flexibility in measurement, Selective allows greater nuance for manual evaluations, and Audit supports broader data gathering without impacting scores.

By selecting the right model for each scorecard, you create a balanced approach to quality assurance—one that supports accuracy, clarity, and meaningful coaching outcomes.

• What does your current reporting structure look like?
• Which departments are involved, and how do they interact?
• Where and how will you use the different roles? Do you need additional roles beyond the standard ones?
• How do training, coaching, and quality operate within your existing structure?

Thinking through these questions will help you design an organizational structure and role framework that fits your specific needs.

Plan

Your organizational structure is one of the first and most critical steps in setting up FiveLumens. Take time to plan before you start. Making changes after implementation can create confusion and unnecessary rework. A clear plan from the beginning helps ensure smoother setup and long-term success.

Structure

Groups: Groups define the highest level of your organizational structure. A Group can represent a location, affiliate, or department within your organization. Each Group can have its own administration, including Group Admins, Team Leaders, Team Admins, Quality Analysts, Trainers, and Agents. You can create as many Groups as needed to match your organization’s design.

Teams: Teams manage the levels beneath Groups. Teams allow you to organize users, manage activities, and align operations with how your departments or business units function. Each Team belongs to a single Group and can be nested under another Team to mirror real-world reporting structures.

Limit: There is no limit to the number of Groups or Teams you can create in your account.

Roles and Permissions

FiveLumens includes standard roles and permissions, but you can create custom roles if your structure requires more flexibility. Before assigning users, review each role and its permissions to ensure responsibilities and access align correctly. Proper planning here helps maintain security, accountability, and efficiency across your organization.

Assignments

Trainings, Coaching Forms, and Quality Forms are all assigned at the Group level. Assigning them to a Group ensures that all Teams within that Group automatically receive access. This structure keeps assignments organized, consistent, and scalable as your organization grows.

Here are some examples of how you could set up your organization based upon your structure.

Example 1 – Company

In this organizational structure we have a company that has multiple departments. Within those departments there are different shifts and different teams.

Example 2 – Locations or Accounts

In this organizational structure we have a company with multiple locations or a BPO that has multiple accounts. Even though training might be similar, by breaking them out into different groups and teams you can customize training, coaching and quality based upon the different needs.

Building your organization in FiveLumens sets the foundation for how your entire system functions. By taking time to plan your structure, define roles, and align Groups and Teams to your real-world operations, you create clarity and efficiency from the start. Thoughtful setup ensures that permissions, assignments, and reporting all work seamlessly together, helping your organization scale smoothly and operate with confidence.

The Users section allows you to create, edit, and manage all users within your FiveLumens account. From this area, you can control account access, assign permissions, and organize users based on your operational structure. Managing users effectively ensures accurate reporting, proper visibility, and secure access across your organization.

Creating a User

To create a new user, go to Organization in the left navigation menu and select the Users submenu. In the upper right corner, click + Add User.

A modal will appear with several fields. The required fields are:

• First Name
• Last Name
• Email
• Password
• Role
• Group

All other fields are optional when creating a user.

The Password field includes two options:

1. Send Email toggle: When turned on, this sends an email to the new user prompting them to create their password when they first log in.
2. Manual password creation: You can create a password directly within the modal and share it with the user. This option does not send an email.

You can return later to edit or update the user’s profile settings, but completing these required fields is all that’s needed to create a new user.

Editing a User

To edit an existing user, go to the Users list and click the action icon next to the user’s name. Select Edit. This will open the user’s profile page.

From the User Profile page, you can:

• Update profile information by clicking the settings icon.
• Review the user’s activity across Quality, Coaching, and Training.
• Take additional actions to manage account access and activity history.

There are three available actions for a user:

1. Reset Password – opens a modal where you can manually change the user’s password.
2. Send Reset – sends an email to the user prompting them to reset their own password.
3. Generate Log – creates and downloads a PDF activity log for the user, which can be used for HR or recordkeeping purposes.

These tools allow you to maintain user security, visibility, and accountability across the platform.

Deactivating and Reactivating a User

You can deactivate or reactivate a user through the Status toggle in the Users list.

When you toggle the status to Deactivate, a confirmation modal will appear asking you to verify the action. Deactivating a user does not delete their account or data. It simply prevents them from logging in or accessing the platform until reactivated.

When you toggle the status back to Active, the user will be reactivated immediately and a success modal will confirm the change.

This feature allows you to manage user access efficiently without permanently removing their profile or history.

Deleting a User

To permanently remove a user, click the action icon next to the user’s name and select Delete.

Deleting a user will remove their account and all associated history from the platform. This action is permanent and cannot be undone.

When you choose to delete a user, a confirmation modal will appear to verify the action. Once confirmed, the user and all related data will be permanently deleted from FiveLumens.

Use this action carefully to avoid the loss of important historical data or reporting records.

Managing users is essential to maintaining an organized and secure environment within FiveLumens. By carefully creating, editing, and controlling user access, you ensure that each person has the right permissions, visibility, and responsibilities for their role. Using the available tools to deactivate, reactivate, or delete users helps keep your account accurate and up to date while preserving data integrity across Groups, Teams, and Roles. Proper user management supports smooth operations and accountability throughout your organization.

Groups define the highest level of your organization’s hierarchy, while Teams manage everything within those Groups. Every user in FiveLumens must be assigned to a Team, and all permissions, coaching sessions, evaluations, and reporting flow through that structure.

By creating Teams that align with your departments, lines of business, or operational units, you ensure clear accountability, organized data, and efficient management at every level.

Creating a Team

To create a new Team, go to Organization in the left navigation menu and select Teams. In the upper right corner, click + Add Team.

A modal will appear with four required fields:

• Name: The name of the Team.
• Description: A short summary of the Team’s purpose or function.
• Group: The Group this Team belongs to. This is a single-select dropdown that lists all available Groups. A Team can only be assigned to one Group.
• Nested Under: The parent Team this new Team will belong to, if applicable.

Once you have entered all information, click Create. The new Team will appear in your list and you can begin assigning users to it.

Understanding “Nested Under”

The Nested Under field allows you to build a hierarchy of Teams within a Group. This structure helps organize departments, managers, and sub-teams in a way that mirrors how your organization operates.

For example, imagine a retention department with two directors. Each director manages their own Team, and each of those Teams contains five smaller Teams. In this case, you would:

1. Create one Team for each director.
2. Assign users to those director-level Teams.
3. Create the five sub-Teams under each director’s Team using the Nested Under option.
4. Assign users to each sub-Team.

This structure completes the hierarchy within FiveLumens, where Groups define the highest level of the organization and Teams manage all levels beneath them.

Editing a Team

To edit an existing Team, go to the Teams list and click the action icon at the end of the Team’s row. Select Edit.

This will open the Team settings modal, where you can update the name, description, group, or nested under fields.

After making your changes, click Save to apply the updates.

Deleting a Team

To delete a Team, click the action icon at the end of the Team’s row and select Delete.

Unlike Groups, Teams can be deleted even if they have users assigned to them. When you delete a Team, two things occur:

1. The Team Leader, Team Admins, and all Team Members assigned to that Team will be unassigned.
2. Any Teams nested under the deleted Team will also be unassigned from it.

A confirmation modal will appear asking you to verify the deletion. Once confirmed, the Team will be permanently removed.

Be cautious when deleting Teams, as this action cannot be undone and will affect all users and sub-teams associated with it. Remember this affecting only the assignment of users to teams and not the users themselves.

Assigning and Removing Users from Teams

There are two ways to assign users to a Team within FiveLumens: through User Management or directly from the Teams section.

Assigning Users When Creating or Editing a User

When creating a new user, you will need to assign them to both a Group and one or more Teams. A user can belong to multiple Teams as long as those Teams are within the same Group they are assigned to.

If you are editing an existing user, you can update, change, or remove their Team assignments in the same way. To change a user’s Team assignment, simply check or uncheck the Teams as needed within their profile and save the changes. To remove a user from a Team entirely, uncheck the Team and save. Remember that Teams are tied to Groups, so a user can only be assigned to or removed from Teams that belong to their assigned Group.

Assigning or Removing Users from the Teams Section

You can also manage Team membership directly from the Teams list. Click the action icon at the end of the Team’s row and select Add User.

A modal will appear allowing you to filter users by role and group. You can then select one or multiple users to add to the Team. Once your selections are made, click Save to complete the assignment.

To remove users from a Team, check the box next to each user’s name and select Remove from the options dropdown. This is for bulk removals. You can also click the Edit User action icon, which will open the user’s profile where you can adjust or remove their Team assignments directly.

Team Leader and Team Admin

When creating a Team, no Team Leader is automatically assigned. After adding users to a Team, you can designate one or more users with the Team Leader role to serve as the Team’s leader.

The Team Leader can coach and evaluate all agents assigned to that Team. You can also assign a Team Admin, who functions as a backup to the Team Leader. If the Team Leader is unavailable, the Team Admin can perform the same functions to ensure continuity.

To assign or remove a Team Leader or Team Admin, click the action icon at the end of the Team’s row and select Assign Team Leader or Assign Team Admin. All assigned Team Leaders and Team Admins will be highlighted with the blue color.

It is important to note that a Team Leader or Team Admin must first be added to the Team. However, until they are specifically assigned as the Team Leader or Team Admin for that Team, they will only be considered a member of the Team and not have administrative permissions for it.

Teams are central to how users, roles, and activities are managed within FiveLumens. By creating Teams that reflect your organizational structure, you ensure that coaching, evaluations, and reporting flow accurately through each level of your business. Assigning the right Team Leaders and Team Admins keeps performance management and communication aligned, while proper user assignments maintain clarity and control. A well-organized Team structure allows your organization to operate efficiently and consistently across every Group.

Each Group functions as an independent area within your FiveLumens account. A Group can contain its own set of administrators, including Group Admins, Team Leaders, Team Admins, Quality Analysts, and Trainers, as well as its own Agents. This structure allows each Group to operate with its own permissions, users, and performance data while remaining connected to the overall account.

Coaching Forms, Scorecards, and Trainings are all assigned at the Group level. Because of this, Groups serve as the foundation for how evaluations, coaching, and learning are organized and delivered throughout your organization.

Creating a Group

To create a new Group, go to Organization in the left navigation menu and select the Groups dropdown. In the upper right corner, click + Add Group.

A modal will appear with three required fields:

• Name: The name of the Group.
• Description: A short summary to identify the Group’s purpose or function.
• Nested Under: The parent Group this new Group will belong to, if applicable.

Once you have entered the information, click Create. The new Group will appear in your list, and you can begin assigning users to it.

Understanding “Nested Under”

The Nested Under field allows you to create a hierarchy of Groups based on your organization’s structure. This feature was designed especially for Business Process Outsourcers (BPOs) or organizations that manage multiple clients or business lines within one account.

For example, a BPO may have 40 clients, so they would create 40 separate Groups. If one client has three main lines of business—Customer Support, Retention, and Sales—each can be created as a sub-Group “nested under” that client. Each account manager for the client would then have access only to their assigned department while still remaining within the overall client Group.

It’s important to note that Groups are used to define roles and permissions for admins, while Teams are used to manage team members and agents.

Editing a Group

To edit an existing Group, go to the Groups list and click the action icon at the end of the Group’s row. Select Edit from the menu.

This will open the Group settings modal, where you can update the name, description, or nested under fields.

After making your changes, click Save to apply the updates.

Deleting a Group

To delete a Group, click the action icon at the end of the Group’s row and select Delete.

If there are users, other than admins, assigned to the Group, you will not be able to delete it. An error modal will appear notifying you that the Group cannot be deleted until all non-admin users have been removed.

If there are no users, other than admins, assigned to the Group, a confirmation modal will appear asking you to verify the deletion. Once confirmed, the Group will be permanently removed.

Be cautious when deleting Groups, as this action cannot be undone.

Groups form the foundation of your organization within FiveLumens. By structuring your account with Groups, you can align users, permissions, and reporting with your operational setup. Because Coaching Forms, Scorecards, and Trainings are all assigned at the Group level, maintaining an accurate Group structure ensures evaluations, coaching, and learning are delivered correctly across your teams. Taking time to build and manage Groups thoughtfully creates clarity, control, and efficiency throughout your organization.