Logical Model
Logical Model is the way the data in Salted CX are organized so they are easy to use for wide range analytical needs. Logical Model is designed to be easy to understand for people without deep technical knowledge. Understanding logical model is helpful for creating custom metrics and building reports and dashboards.
Data available in the Logical Model differs by connected data sources and their setup. The Logical Model can work perfectly fine if the data are not complete. Subset of metrics will be available.
Data Sets
Data sets represent different king of items stored in the logical model. Salted CX uses limited set of data sets that enable users to quickly navigate in it.
Each data set has a set of attributes, facts and references to related data sets.
| Entity | Description |
|---|---|
| Activity | Detailed break down of agent load and activity. |
| Agent | The person or a service that interacts with customers on behalf of the company. Each engagement is associated with one agent. |
| Customer | The person that the company engages with during the conversation. We recommend that all engagements in a single conversation be associated with a single customer although it is technically possible to have conversation where multiple customers are involved. |
| Engagement | Individual engagements between agents and customers. Multiple engagements can be grouped into one conversation. |
| Question | Question that was answered in a review. |
| Review | Review represents individual responses, comments and tags associated with Engagements. Reviews contain feedback from customers, agents, reviewers and automatic reviews. |
| Reviewer | Person or a service that provides Reviews for Engagements. |
| Transaction | Transactions that happened during this engagements. Transactions can have associated revenue and costs to enable reporting on financial aspects of the engagements. There can be multiple transactions for a single Engagement. |
| Turn | Granular breakdown of individual engagements. Turns represent different events in different types of engagements. In messaging they represent a single message sent by a participant, in voice conversation, they represent a single talk by one of the participants, in menu engagements they represent individual menu steps, etc. Turns are not available for reporting. They are visible in the customer journey. |
Attributes
Attribute is a property of a Data Set that can be used for segmentation and filtering of data visible in the reports and dashboards.
Attribute and label values are limited to 100 characters. If an attribute or label value is longer than 100 characters the value is trimmed. Whenever a value is trimmed the event is reported to Technical Log as a warning.
We recommend watching for trimmed values as they may lead to skewed reporting. If multiple values have the same first 100 characters and differ only after those characters, segmenting by such attributes will merge metrics from these two different values into one segment.
Enumerations
Enumerations are special types of attributes that can contain only values allowed by Salted CX. Unsupported values cause failure to load data using our Ingest API.
Entities
Entities are very simple Data Sets. Unlike Data Sets they have only one attribute with two labels and no facts. Every entity has the same set of one attribute and 2 labels for that attribute.
| Property | Type | Description |
|---|---|---|
| <Entity Name> | PID | Permanent identifier generated by Salted CX and uniquely identified the item. The PID cannot be changed after the entity is created. |
| <Entity Name> ID | Label for <Entity Name> | ID that the entity has in a third-party system. Salted CX does not enforce any format for the ID. The ID has to fit into 100 characters as attributes have to. |
| <Entity Name> Name | Label for <Entity Name> | Name that is the default representation of the entity in the user interface. The name should be easy for users to read and understand. The name is also limited to 100 characters. |
Entities enable you to have unique representation of important items in the contact center while having a human friendly visualization. Entities also enable you to easily rename the items without breaking relationships between important data points.
PID
Each item in a data set and every entity has a unique Permanent Identifier — PID. PID is a special type of an attribute. PID is always an UUID that is either generated by random or deterministically based on identifiers in the connected platform. Once a PID is generated for an item it cannot be changed in the future.
Labels
Labels are alternative visualizations for attributes. While you might use hard to read value that you for sure know is unique as attribute value, the unique value might be very inconvenient to read for end users.
There might be two items with the same label but different underlying attribute value. If such label is used in insights you will see two different segments with the same name and different metric values.
Similarly to attributes the label values are limited to 100 characters. If a label value is longer than 100 characters the value is trimmed. Whenever a value is trimmed the event is reported to Technical Log as a warning.
As labels are not directly used for segmentation and filtering the data trimmed labels have less impact on data correctness. However if there are two labels that have the same first 100 characters the insights may be misleading - for example you can see twice the same label value or accidentally filter for a different value.
Facts
Fact is a numeric value in the Logical Model. Facts can be used for arithmetic operations, can be aggregated and ultimately are the foundation for crating metrics.
Metrics cannot be used for filtering in insights and dashboards. However you can use values of facts in metric filtering conditions.
When you load custom data and provide non-numeric value where a fact is expected the value is ignored and the event is reported in Technical Log as a warning. Number in quotes is also not considered a fact.
Date, Time and Duration
All dates and times in logical model have one minute granularity. There are multiple date and times in the Logical Model.
All durations in logical model are in seconds.
Technical items in data sets
Some data sets have technical values. Technical values have attribute Type set to value Technical. You can use this attribute to filter the technical items in the data sets out.
Technical items are by default stored in Agent, Customer and Engagement data sets.
Data not in logical model
The logical model does not contain the following data:
- Conversation content such as transcript or voice recordings. It may however contain metadata extracted from the content such as discussed topics, sentiment and other features extracted from the content. The content is stored separately and displayed only when users drill down to customer journey and have permission to view the conversation content.
- Customer personally identifiable data. Customer personally identifiable data are removed and replaced by identifiers from customer profile. We do not expose personal identifiable information in analytics and even in customer journey. To display personal identifiable information user has to have a dedicated permission and click on a specific masked value to view it.
Technically you can provide pieces of conversation content and personally identifiable data in attributes and labels when loading custom data to Salted CX. However we strongly discourage you from doing that as it bypasses compliance enforcement in Salted CX.