Slated CX automatically processes all conversations that happen in Salted CX Live Conversations and other integrated contact center platforms. It automatically reviews multiple performance factors and surfaces metrics in dashboards and reports. These auto-detected data are provided to individual engagements. The following attributes and metrics are provided if they are relevant for the given engagement.
| Property | Description |
|---|---|
| Expressed Satisfaction | Automatically detected customer satisfaction that is explicitly expressed by the customer. This can be statements like “your process is ridiculous”, “thank you so much, you saved my day”. |
| Customer Satisfaction | Automatically detected customer satisfaction based on the conversation content even when customer does not explicitly express it. This takes into consideration what is discussed and how smoothly the conversation goes from the customer. |
| Understanding | Automatically detected the agent ability to understand the customer request and responding to the actual customer question including details and specifics related to that customer request. When agent responds too generally, responds to a question that is not asked or does not cover customer specifics of the requests it lowers the score. The need of customer to repeat their requests or important details of it lowers this score. |
| Adaptability | Automatically detects agent’s ability to deviate from their script of process to improve the customer experience. This metric requires as an input the processes description in the company for accurate numbers. Without those this metric is filled for small number of conversation where it can be assumed the agent is limited by a process. |
| Adherence | Automatically detects agent adherence to a script or process. This metric requires as an input the processes description in the company for accurate numbers. Without those this metric is filled for small number of conversation where it can be assumed the agent is limited by a process. |
| Clarity | Automatically detects clarity of the response. This tries to identify whether there is no ambiguity. Clarity score is also negatively impacted if there is unnecessary filling phrases or phrases that repeat simple customer requests. |
| Completeness | Automatically detects completeness of the agent responses. When the customer needs to ask additional questions the score is negatively impacted. |
| Language Skills | Automatically detects the agent language — spelling, grammar, interpunction and phrasing. |
| Persuasion | Automatically detects the agent ability to persuade the customer, address their concerns and objections. |
| Resolution | Automatically detects whether the customer request was resolved and categorizes it into one of these:
Resolved — the agent resolved the customer request so the customer confirms it is resolved
Unresolved — the customer gives a feedback that the proposed solution does not work for them and there is no other solution provided by the agent
No Response — the agent seemingly provided a solution from the customer but there is not a followup response from the customer so it is not possible with high confidence to classify the resolution
Declined — the agent provided the customer with a solution the customer does not agree with but the solution is based on the company policy and the conversation is considered concluded even when the customer request is not addressed they way the customer wanted |
| Severity | Automatically detects severity of the customer request. The severity indicates how impacted the customer would be if their request is not resolved. High severity indicates health impacts, high financial impact, inability to experience important live events, etc. Low severity are generic informative questions. |
| Empathy | Automatically detects empathy on the agent side such as acknowledgment of the customer frustration and responding accordingly when the customer is agitated or in distress. |
| Topic | The key topic that is discussed in the engagement. There is only one key topic per engagement even when there are potentially more topics discussed. The topic is intended to be filled by AI. |
| Topic Category | The categorization of the topics to higher level. The topic category is intended to be filled with AI. |
Content Considered by Auto Summary
The conversations may be complex, involve multiple participants, the same agent may join multiple times, and the conversation may change channels.
The Auto Summary always provides results on the engagement level. Each conversation may have multiple auto summaries if it has multiple engagements.
Auto summary of individual engagements:
- Takes into consideration selected turns prior the analyzed engagement End Time no matter which engagement in the same conversation the turns are related to. This enables the auto summary to better understand the context (what customer mentioned before agent joined, what information was already collected, etc.)
- Ignores all turns after the engagement End Time even when they are associated with the engagement. This can be for example “Thank you”, “Goodbye” from the customer that is intentionally ignored as it is not actionable.
- At least one non-customer turn must be present in the engagement to be included in the auto summary.
- Auto Summary focuses on the given engagements but is influenced by the rest of the conversation.
- The maximum number of turns preceding the analyzed engagement is limited to 50, but may be lower in conversations that contain very long turns (long emails).
Multiple Participants
The following conversation has 3 engagements. Bot, Frank (internal agent), and Japan Travel (external agent) are helping the customer with rebooking their trip.
Customer: Hello.
Bot joined the conversation.
Bot: Hello, how can I help you?
Customer: I would like to rebook my trip to Japan. My family is sick.
Bot: Is this related to the booking ORDER-123?
Customer: Yes.
Bot: Let me escalate your request to an agent to verify whether the rebooking is possible for your case.
Please reach out to the travel agency to verify what the rebooking options are, because the rebooking is less than 2 weeks before departure.
Frank joined the conversation.
Frank: Hello, my name is Frank.
This trip starts in less than 2 weeks, so changes to the booking are restricted. Let me invite the travel agency to this conversation to see if there are any options. It can take some time for them to join. Please be patient.
Is there anything else I can help you with in the meantime?
Frank invited Japan Travel to this conversation
Customer: Understood. I will wait.
Japan Travel joined the conversation.
Japan Travel: Hello, we can rebook the trip for a $100 change fee. Would you like me to change your travel dates?
Available dates are: 10 August to 24 August and 7 Sep to 21 Sep
Customer: That is great. August, please.
Japan Travel: OK. Done. Anything else I can help you with?
Customer: No. That’s all.
Japan Travel: Great. Have a nice trip to Japan, bye.
Japan Travel left the conversation
↑ All turns before this event are used for the Japan Travel engagement auto summary
Customer: Wait, how do I pay the $100?
Frank: The rebooking fee was paid from your credits. Is that OK?
Customer: Yes, that’s fine. Was just wondering.
Frank: OK. Anything else I can help you with?
Customer: No, that’s it.
Frank left the conversation
↑ All turns before this event are used for the Frank engagement auto summary
Customer: Thanks.
Bot: Was your request resolved?
Customer: Yes.
Bot: Thank you for reaching out to us. Have a nice day. Bye.
Bot left the conversation the conversation
↑ All turns before this event are used for the Bot engagement auto summary
Customer: Bye.
Changing Channels
Changing a channel creates a new engagement even when the agent does not change. This means one agent gets multiple separate engagements, with a separate auto-summaries per conversation.
Customer: Hello. I need to get the invoice by email.
Frank joined the conversation.
Frank: Hello, my name is Frank.
Sure. Give me a few moments, and I will send it over to you.
Frank changed the channel to Email.
↑ All turns before this event are used for the Frank engagement 1 auto summary
Frank: Hello,
As mentioned in the chat, the invoice is attached. Frank, Demo Adventures
Customer: Thank you.
Frank changed the channel to Chat.
↑ All turns before this event are used for the Frank engagement 2 auto summary
Frank: You are welcome. Anything else I can help with?
Customer: No. That is all.
Frank: You are welcome. Anything else I can help with?
Frank left the conversation
↑ All turns before this event are used for the Frank engagement 3 auto summary
Customer: Bye.
Multiple Participants Overlapping
The content from other participants is considered in the summary, bot it is not the focus of it. However it may provide an important context.
Customer: Hello. I need a refund for my order because I didn’t notice the trip starts from a different city with the same name.
Frank joined the conversation.
Frank: Hello, I am sorry. In this case, we cannot provide the refund.
Customer: Are you serious? I spend thousands of dollars with you every year, and I cannot even get like $200 back in my entire lifetime? There are still 4 days until the trip starts, surely you can still sell my seat to somebody.
Frank: I am sorry. According to our policy, I cannot do anything.
Customer: I want to speak with your manager.
Frank: OK. I understand. I have invited my manager to this conversation. Please give her a few moments.
Customer: OK.
Mellisa joined the conversation.
Mellisa: Hello, I am really sorry for the inconvenience. I have looked into the case, and in this exceptional case, I can authorize a refund to the credits in your account. Is that acceptable?
Customer: That’s OK. Thank you.
Authorized this exceptional refund due to excessive spending by the customer and a clean history.
Mellisa: No problem. You should already see the full amount in your credits. Anything else we can help you with?
Customer: Do the credits expire on something?
Frank: These credits do not expire, and you can spend them on any experience on our websites.
Mellisa left the conversation.
↑ All turns before this event are used for Melissa's engagement auto summary
Customer: Thanks.
Frank: Anything else I can help you with?
Customer: That’s it.
Frank: Great. Have a nice day. Goodbye.
Frank left the conversation.
↑ All turns before this event are used for Frank's engagement auto summary
Customer: Bye