Flex Insights Data Model

The Flex Insights Data Models consists of data sets. Each data set, or group of data objects, represents a business entity in the contact center. Data sets are connected to each other based on their real-world relationships.

The following entity-relationship diagram maps how data sets within the model can be viewed with a real-world perspective:

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Each data set contains one or more of the following data objects:

• Date Dimensions: values that represent the date (or the date and time) that specific events occurred. You can use date dimensions to filter and segment data. For more information, see the Date Dimensions section.
• Attributes: values that represent a single quality that describes or relates to the data set to which it belongs. Attributes can have text or numeric values. You can use attributes to filter and segment data.
• Facts (formerly known as Measures): KPIs and other metrics that represent mathematical calculations or aggregations. Facts are calculated as sums, averages, etc., or counts of distinct values. Facts can be segmented by attributes or dates.

This section defines the model's main data sets and lists corresponding data objects. Please note that some data sets do not contain data by default and require custom data integration.

You can view the complete list of data sets by selecting the Manage tab in the Analytics Portal.

Conversations represent interactions between agents and customers. Each row in the Conversations data set represents a single Segment that is a part of a conversation or an agent activity (agent status data). These data enable the representation of all of the steps a customer went through when having a conversation with the contact center. You can also correlate these data with agent status data for reporting.

This data set contains data from TaskRouter events.

This data set includes the following attributes:

Agents handle conversations with customers. This data set enables you to segment and filter conversations by the agents who handled them.

This data set contains data from TaskRouter worker attributes. Check this resource to learn more about how worker data can be populated into Insights.

This data set includes the following attributes:

• Agent Attribute 1, Agent Attribute 2 and Agent Attribute 3: Custom agent attributes.
• Agent ID (Primary Key - PK): An identifier assigned by contact center management to uniquely identify the agent.
• Date - Joined: The date when the agent joined the company. Available in Flex Insights when you provide values via custom task attributes.
• Date - Left: The date when the agent left the company. Available in Flex Insights when you provide values via custom task attributes.
• Department: A set of Teams. This is a higher-level organization unit than a Team.
• Email: The agent's email address.
• First Name: The agent's first name.
• Last Name: The agent's last name.
• Location: The agent's physical location.
• Manager: The agent's manager. This is a single person who is responsible for the agent.
• Phone: The agent's phone.
• Role: The agent's role. It enables the segmentation of agents by their role in the company.
• State: The current state of the agent. It indicates whether they still work in the contact center. Possible values: Active, Inactive.
• Team: The agent's Team.

Workload breaks down conversations and agent activity (agent status data) into 15-minute intervals. This data set enables accurate intraday workload reporting.

This data set includes the following attributes:

• Activity: The agent status the agent was in during the 15-minute interval.
• Order: The order of this workload item within the segment.
• Workload Kind: The kind of the original segment related to this workload. Refer to "Workload Kind" in Workload Reporting for a list of possible values.

This data set includes the following facts:

• Activity Time: The time the agent spent in the agent status during the 15-minute interval.
• Parallel Conversations: The number of conversations the agent was engaged in (including wrap up) while being in the associated agent status during the 15-minute interval.
• Talk Time: The time the agent spent in talk time for the associated segment during the 15-minute interval.
• Wrap Up Time: The time the agent spent in wrap up for the associated segment during the 15-minute interval.

Customers are people who contacted the center or were contacted by the center. This data set enables you to segment and filter conversations by demographic attributes.

This data set contains data that TaskRouter provides, together with a customer phone number.

This data set includes the following attributes:

• Customer (PK): A reference to a single customer. Depending on how well Insights is able to connect individual contact information with a specific customer, one person may appear in several customer records. For example, if Insights is unable to associate a person's phone number and email address, they will appear in two records.
• Acquisition Date: The date when the customer was acquired.
• Area: The geographical area where the customer is located.
• Category: An attribute enabling custom slicing of customer data by category.
• Country: The country where the customer is located.
• Customer Attribute 1, Customer Attribute 2 and Customer Attribute 3: Custom customer fields.
• Email: The customer's primary email.
• Gender: The gender of the customer. Possible values: Female, Male, Other, Unknown.
• Geo Location: GPS coordinates of a representative city or location within the area.
• Name: The full name of the customer. Includes the first name and the last name if they are available.
• Organization: The organization to which the customer belongs.
• Phone: The customer's primary phone number.
• Region: A higher-level geographical unit than Country. It allows the grouping of countries into regions. There is no required set of regions. Each Flex customer may implement their own segmentation of the world.
• Type: An indicator that distinguishes between actual customers and agents that are identified as the "customer" in a conversation (in case of internal agent-to-agent segments). See the Flex Insights Data Model Caveats.
• Year of Birth: The date of birth of the customer.

This data set includes the following facts:

• Acquisition Cost: The cost of acquiring the customer.
• Business Value: A positive or negative value expressing how the company values the customer in terms of future possible income or a similar metric.

Supervisors are people that provide feedback to agents using Assessments. This data set enables you to understand how feedback influences performance. Agents that provided feedback to other agents or assessed their conversations also appear in the Supervisors data set.

By default, this data set contains the data of the contacts who made assessments.

This data set includes the following attributes:

• Supervisor (PK): A Supervisor is anyone who provided feedback on a conversation or an agent, including agents themselves.
• Department: The supervisor's department, which is a set of Teams.
• Email: The supervisor's email address.
• Manager: The supervisor's manager.
• Role: The supervisor's role, such as the job title or role indicating their permissions.
• State: The current state of the supervisor. It indicates whether they still work in the contact center.
• Team: The supervisor's team.

Assessments enable you to categorize conversations, attach comments, and score conversation quality. This data set enhances understanding of different, measurable quality aspects of conversations.

This data set contains manual entries that come from filled conversation questionnaires and comments in Flex Insights.

This data set includes the following attributes:

• Assessment (PK): A distinct assessment of a conversation quality, given for a question by an assessor.
• Answer: The answer selected from the range of available answers for the given question.
• Assessment Type: A reference to the Conversation Screen from which the assessment originated. Possible values: Quality (Assess feature), Comment (Comment feature).
• Category: The category of the metric. Enables the grouping of metrics into categories for reporting on a higher level.
• Comment: A free-form comment that a supervisor may attach to the assessment.
• Metric: The assessed question in a questionnaire.
• Rejection: [Not in use] The reason why the assessment was rejected. The person who was supposed to asses the question declined to asses it, as it was not relevant or was impossible to assess.
• Report: This indicates whether the assessment should appear in reports. Enables excluding an assessment from reports if, for example, it is a training score or other assessment that should not influence an agent's performance rating. Possible values: Yes, No. If the conversation was assessed but then the assessor removed their scores, the assessments Report flag will be set to No.
• Review: [Not in use] A reference to the review during which the assessment was done. Enables grouping of assessments into logical units.

This data set includes the following facts:

• Assessed End Position: The end offset in the segment related to the assessment.
• Assessed Position: The offset in the segment related to the assessment.
• Max Score: The maximum possible score of the metric. Equal to 1 for percentages.
• Min Score: The minimum possible score of the metric. Equal to 0 for percentages.
• Score: The score in the metric original scoring scale, as defined by the Min Score and Max Score bounds. It may also be outside of these bounds for bonus points and extra negative points.
• Score Percentage: The score, when normalized to a percentage.
• Time - Assessment in Seconds: The duration of the content that was the focus of the assessment, expressed in seconds.
• Weight: The weight of the metric, as set up in the external system. Enables reporting on different metrics that have different importance to an overall score.

This section provides descriptions for date dimensions that are present in the model. Usually, the primary date dimension is the right dimension to use. Use other dimensions for reporting needs that are focused on specific business processes. All dates have a set of attributes that you can use to display data from several different temporal perspectives. All dates are in the Gregorian civil calendar.

The model includes the following date dimensions:

• Date: The primary date and time used by the majority of events. The date and time when a segment started.
• Date - Assessment: The date and time when an individual assessment was performed.
• Date - Joined: The date when an agent joined the company (available in Flex Insights when you provide values via custom task attributes).
• Date - Left: The date when an agent left the company (available in Flex Insights when you provide values via custom task attributes).
• Date - Workload: The date that is used for intraday workload reporting. This date dimension enables reporting on exactly how much time agents spend in each agent status and conversations in every 15-minute interval.

Date and Date - Assessment date dimensions also have a time dimension that represents the time in minutes that is associated with the start of a segment. You can use the following attributes to understand intraday facts:

• Hour, Hour - Assessment: The hour of the day for the event in the range from 0 to 23, respectively from 0 AM to 11 PM (you can select a different label to represent time according to your preference).

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• Interval 30 Minutes, Interval 30 Minutes - Assessment: The 30-minute interval in which an event happened.

• Interval 15 Minutes, Interval 15 Minutes - Assessment: The 15-minute interval in which an event happened. The interval is based on the segment/activity start time. For example, conversations starting between 01:15 PM and 01:30 PM are in the interval named 01:15 PM.

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• Time, Time - Assessment: The time in hours and minutes when the event happened. It represents the finest granularity of a time dimension.

Segments, Conversations, Cases, Campaigns, Projects and Initiatives form a hierarchical structure of conversations between your agents and your customers. These attributes enable different levels of analysis:

• Segment: An atom of any conversation. A segment represents an interval in time dedicated to certain phases during a Conversation.
• Conversation: A communication between one customer and all agents in the contact center handling them. A conversation is composed of one or more Segments.
• Case: Multiple conversations regarding the same issue or topic.
• Project: Multiple cases related to the same project.
• Campaign: A business goal-oriented communication campaign with a set of customers. This might be an outbound sales campaign, marketing campaign leading to inbound conversations, social media content publishing, etc.
• Initiative: The highest level of grouping of conversations, intended for representing high-level business initiatives of the company.

Flex Insights groups segments into a conversation based on a conversation identifier extracted from TaskRouter event attributes. Flex Insights uses exact matching of IDs with heuristics that attempt to group segments with the same customer within a short period of time into a single conversation. The exact behavior depends on the conversation channel(s) and can be customized by supplying a custom conversation ID as a task attribute.

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• Learn more about conversation structure in Insights