Engage Voice | Understanding measures and attributes
To create the insight you want, you need to understand what measures and attributes are so you can use them properly. As discussed in Analytical Designer overview, measures are defined as computational expressions of numerical or quantitative data, while attributes are non-measurable descriptors used to break down metrics and measures. Attributes represent qualitative data. This means that measures are data that can be ‘sliced’ by attributes.
For example, Agent Count — the number of agents logged in during a time interval — is a measure. Agent Location is an attribute. If you were to create an insight, Agent Count can be ‘sliced’ by Agent Location to display, say, a bar graph of the number of agents per location.
You also need to know where data from the data catalog are being pulled from, and what their relationships are to each other. There’s more to creating insights than just understanding insight types. Not all measures can be ‘sliced’ by all attributes. There are certain attributes that don’t work on certain measures. This is where the concept of logical data models (LDMs) comes in.
About logical data models
The data used in creating measures and attributes pulled from your contact center’s database are organized into datasets. In Historical Reporting, a dataset is a basic organizational unit for these data. It is a set of related measures, a set of attributes, or a set of both.
Datasets are connected to one another to create exclusive relationships. For example, Dataset A is connected to Dataset B, but is not connected to Dataset C. Dataset B, on the other hand, is connected to Dataset C. This means that A can interact with B but not with C and vice versa. However, B can interact with both A and C.
Try to imagine each dataset as boxes with data in them. Datasets connected to one another constitute a logical data model (LDM). The LDM in Historical Reporting is used to determine which data can interact with another data.
In Historical Reporting, there are two important datasets for data: segment and agent state. Some data are tagged and can be found under those categories, while some are not. When you drag a measure or an attribute to a section on the canvas, the data catalog will repopulate and only data compatible with the one on the canvas will appear in the catalog.
It is also important to understand the concept of the segment and agent state datasets so you don’t confuse compatible data with incompatible data when conceptualizing insights you want to create.
Segment
Segments or call segments are the smaller portions of an interaction between a call’s consecutive states. These consecutive states are parts of a call associated with a specific ‘product’ like an IVR or a queue. Each portion or segment is independent from another segment of that call. To better understand this, read the example below.
Let's look at calls from the perspective of the caller. Let’s say you call a contact center. You get an IVR (Segment 1) which then transfers you to a queue for an agent (Segment 2). After talking to that agent, it turns out you chose the wrong queue so the agent transfers you to the right queue. After waiting for a long time on that queue, you hang up (Segment 3). From your perspective as a caller, you consider all those transfers and queues as one long call.
However, from the perspective of the contact center, that wasn’t just a long call but rather a series of segments independent from one another. Getting an IVR (Segment 1) is independent from getting on a queue and talking to an agent (Segment 2), and so on.
Agent State
Agent states include both call-related and non call-related agent time. Agent states are the agent’s status like Available, On Break, Engaged, and so on. The sum of all agent states when logged in is called ‘Login’ in this LDM.
Now that you have a basic understanding of measures, attributes, and where they come from, let’s take a look at all the specific data under each category. These categories can be found in the data catalog in the left-hand panel.
Measures
As discussed above, measures are computational expressions of numerical or quantitative data. These are data where mathematical functions can be performed. Let’s look at the different measure categories below.
- Agent: Data under this category is related to agent information and activities
- Agent Login Utilization: The percentage of the agent login time spent on calls
- Agent Occupancy: Ratio of time an agent is engaged in productive work to the time they are available
- Agent State Time: The total time an agent spends in some state. You can filter specific states once this is configured
- Agent Utilization: Percentage of paid time that an agent is either performing productive work, or available to handle customer transactions
- Available Time: Total time an agent spent in the Available state
- Away Time: The total time an agent is in an Away state
- Break Time: The total time an agent is in a Break state
- Engaged Time: The total time an agent is in an Engaged state
- Lunch Time: The total time an agent is in a Lunch state
- Non-Work Time: The total time an agent is not working
- Pending Disposition Time: The total time an agent is in any state after a call before submitting a call disposition
- Total Agent Login Time: The total time an agent is logged in
- Total Agent Work Hours: Total time an agent spent working (expressed in number of hours)
- Training Time: The total time an agent is in a Training state
- Work Time: The total working time of an agent
- Call Segment or Segment: Data under this category refers to the smaller portions of an interaction between a call’s consecutive states
- Agent Connected Count: The number of calls connected to agents
- Agent Wait Time: The total time an agent waited for a call
- Average Handle Time: The average time it took agents to handle calls
- Average Hold Time: The average time customers were put on hold by the agent on the call
- Average Ring Time: The average time of ringing per segment
- Average Talk Time: The average time customers spent on the phone connected to an agent or IVR
- Average Wait Time: The average time agents spent waiting for a call
- Average Wrap Time: The average time per call taken by agents to submit a call disposition after a call is disconnected
- Customer Talk Time: The time agents spent talking to customers on calls
- Handle Time: Total handle time or transactions handled by agent
- Hold Time: Hold time duration of interaction
- Manual Dials Count: The number of manual calls placed by agents
- Manual Dials No Connect Count: The number of manual calls placed by agents that were not connected
- Ring Time: Ring time duration
- RNA Count: The number of calls presented to an agent, but not connected (Ring No Answer)
- RNA Time: The total time agent phones were ringing for unanswered calls
- Segment Count: The total number of call segments
- Short Calls: Calls with talk times shorter than 10 seconds
- Successful Count: Number of successful interactions
- Talk Time: The time customers spent on the phone connected to an agent or IVR (including time on hold)
- Wrap Time: The time agents spent between customer disconnection and disposition submission
- Common: Data under this category pulls information from all channels
- Calls Ratio: The ratio of calls from the total calls counted by product, date, and agent
- Inbound: Data under this category pulls from inbound calls
- Average Queue Time: The average queue time of calls
- Average Speed of Answer: The average time callers waited in a single queue
- Average Time of Abandon: The average time callers waited in queues before hanging up
- Inbound Accepted Count: The number of inbound calls distributed to agents
- Inbound Deflected Count: The number of calls sent to another destination
- Max Queue Time: The maximum time a call was waiting in a queue
- Queue Abandon Rate: The percentage of calls abandoned in a queue
- Queue Abandoned Count: The number of inbound calls in which callers hung up while waiting in a queue
- Queue Long Abandon Rate: The rate of calls abandoned in a queue after waiting for a long time
- Queue Long Abandoned Count: The number of calls abandoned in a queue after waiting for a long time
- Queue Segment Count: The number of times calls were queued
- Queue Short Abandon Rate: The rate of calls abandoned in a queue after waiting for a short time
- Queue Short Abandoned Count: The number of calls abandoned after waiting for a short time
- Queue Time: The total time spent waiting in a queue
- Service Level: The ratio of calls that passed the SLA out of total calls queued
- SLA Passed Count: The number of calls answered within configured service level threshold
- SLA Qualified Count: The inbound calls qualified to be counted for service level agreement
- Time to Abandon: The time callers waited in a queue before hanging up
Helpful hint!
The metrics for SLAs reported will be according to the settings that were in effect during the call. This means if SLAs are adjusted, this will be reflected in the report generated.
- Outbound: Data under this category pulls from inbound calls
- Outbound Abandon Rate: The ratio of outbound abandoned calls to the total number of answered calls
- Outbound Abandoned Count: The number of outbound abandoned calls or answered calls that were not connected to an agent
- Outbound Answered Count: The number of outbound calls answered by the party called
- Outbound Answering Machine Count: The number of outbound calls answered by answering machines
- Outbound Busy Count: Number of calls tagged as busy
- Outbound Call Attempts Count: The count of outbound call attempts
- Outbound Complete Count: The number of outbound calls marked as complete in the disposition
- Outbound Contact Count: The outbound calls that resulted in contact
- Outbound Contact Rate: The ratio of outbound calls making contact to total dial attempts
- Outbound Intercept Count: The number of outbound call attempts with Intercept call results
- Outbound Leads Complete by Product Percentage: The number of completed leads
- Outbound Leads Complete Count: The number of completed leads
- Outbound Live Answered Ratio: The ratio of live answered calls to the total call attempts
- Outbound Live Answered Count: The number of outbound call attempts answered by a live person
- Outbound No Answer Ratio: The ratio of unanswered calls to the total calls attempt
- Outbound No Answer Count: The number of outbound call attempts that were not answered
- Outbound No Answer Min Ringing Time: Minimum outbound ring duration with Outbound No Answer call result
- Outbound Other Count: The number of outbound calls with call results other than what is specified in the system
- Outbound Ringing Time: The total ringing time for outbound calls
- Outbound Success Rate: Ratio of outbound calls out of all outbound call attempts
- Outbound Successful Count: The number of successful outbound campaigns
Attributes
Attributes are non-measurable descriptors used to break down metrics and measures and represent qualitative data. Attributes can also be used as filters in your insight, KPI widgets, and dashboards.
- Agent: Data under this category consists of attributes related to agents
- Agent First Name: Displays agents by their first name
- Agent Full Name: Displays agents by their full name
- Agent Group: Displays agent groups by name
- Agent Group ID: Displays by agent group ID instead of group name
- Agent ID: Displays by agent ID number
- Agent Last Name: Displays agents by their full name
- Agent Location: Displays agents by their location
- Agent Login ID: Displays agents by their login ID number
- Agent Team: Displays agent teams
- Agent Type: Distinguishes agents from supervisors
- Base State: State of a logged-in agent. These are the default states that are automatically set by the system
- Pending Disposition: Gathers data for those with pending dispositions
- State: Custom agent states as configured by customers
- Call Segment or Segment: Data under this category refers to the smaller portions of an interaction between a call’s consecutive states
- Agent Connected: Data of agents for when they were connected and handled a transaction or not
- Agent Disposition: The type of agent disposition data to display — default, requeue, or to not display at all
- Agent Presented: Displays whether an agent was with presented calls or not
- ANI: Displays by ANI
- Call Result: Different call results such as inbound abandon or inbound defected, among many others
- Call Type: Inbound or outbound calls
- Complete: Complete or incomplete calls
- Contact: Agent dispositions marked as ‘Contact’
- Dial Type: The type of outbound calling
- DNIS: Displays by DNIS
- Duration Type: Length of call
- Final: Final segment of the call
- Index: Number of the segments of a call
- Presented: Calls that were presented to an agent
- Success: Calls marked as ‘Success’ in agent dispositions
- Term Party: Which party terminated the call
- Term Reason: Reason a call was terminated
- UII: Unique Item Identifiers
- Common: Data under this category consists of attributes pulled from and related to all channels
- Account: The account or client name to display
- Account ID: The account ID is displayed instead of account name
- Product Group: Shows products by group name
- Product Group ID: Product group ID number is displayed instead of the product name
- Product: Displays product name
- Product ID: Displays products by ID number
- Product Type: Displays products by type
- Inbound: Data under this category consists of attributes related to inbound calls
- Abandon Type: Displays long or short abandons
- SLA Passed: Shows calls that were answered by the agent within the threshold configured for the queue
- SLA Qualified: Presents data that passed SLAs. Short calls won’t be counted by the SLA calculation
Helpful hint!
The metrics for SLAs reported will be according to the settings that were in effect during the call. This means if SLAs are adjusted, this will be reflected in the report generated.
- Lead: Data under this category are attributes related to leads
- Lead Aux 1: Shows additional lead information stored in Lead Aux one
- Lead Aux 2: Shows additional lead information stored in Lead Aux two
- Lead Aux 3: Shows additional lead information stored in Lead Aux three
- Lead Aux 4: Shows additional lead information stored in Lead Aux four
- Lead Aux 5: Shows additional lead information stored in Lead Aux five
- Lead City: Presents data for the lead’s city
- Lead Complete: Displays for leads whose status is complete
- Lead Country ID: Displays for the lead’s country ID
- Lead List: Displays for specific lead list names
- Lead List ID: Displays for specific lead list ID numbers
- Lead Max Passes: Displays for leads that have reached max passes
- Lead Pass Count: Shows the pass count of leads
- Lead State: Presents data for the lead’s states
- Lead Status: Displays for the status of leads, whether the lead is ready or complete
- Lead Success: Shows successful outbound calls tagged as ‘Success’ during dispositions
- Lead Timezone: Presents data for lead’s timezone
- Lead ZIP: Presents data for lead’s zip code
- Time: Data under this category consists of attributes that slices data based on time intervals
- Started Half Hour: Presents data for start time with options for every half hour
- Started Hour: Displays data for start time with options for every half hour
- Started Quarter Hour: Presents data for start time with options for every quarter hour or fifteen minutes
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