Intelligence Satisfaction Score (ISAT)

An industry-first framework to measure the effectiveness of an intelligent virtual assistant

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Limitations in the Current Measurement Frameworks

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CSAT & NPS

Only 2% of users share feedback about their experience with a virtual assistant

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Automation

Useful but does not say anything about queries resolved, false positives, confidence threshold, etc.

 
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Engagement Rate

Standard market metrics such as retention rate, engagement, avg time spent, etc. are not applicable for virtual assistants

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Sentiment Analysis

Complex multi-turn conversations can have various sentiments that make it difficult to analyze

 

The ISAT Score Framework

Steps to Arrive at the ISAT for a given virtual assistant or chatbot

1
Categorize
Conversations
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2
Calculate ISATScore
3
Optimize
Conversation
Flows
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Classifying User Conversations

Analyzing Positive, Negative and Neutral ISAT Conversations

Positive
positive
  • User comes with a query
  • IVA responds appropriately and solves the query
  • Task completion
Negative
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  • High user intent. User repeatedly asks the same query
  • Sends > 2 messages
  • IVA unable to comprehend repeats itself, leading to negative sentiments and unhappy users
Neutral
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  • Low user intent
  • User interacts with the IVA with no clear goal or objective in mind
  • User drops off randomly

Analyzing Negative ISAT Conversations

Conversations with a negative ISAT score are poor experiences that users undergo when the IVA fails to understand and resolve the user’s query. This model is validated by adding all conversations that had a user repetition (UR), bot repetition (BR), and cuss words (CW).

Score
Clients
  • Insurance
  • Finance
  • Healthcare
  • Govt
  • FMCG
ISAT
Bad Chats
  • 12.2%
  • 1.1%
  • 10.4%
  • 18.0%
  • 3.2%
Machine Analysis
UR BR CW Total Negative Conversations
6.0% 3.0% 2.0% 11.0%
1.0% 0.0% 0.0% 1.0%
4.0% 2.0% 2.0% 8.0%
14.0% 3.0% 3.0% 17.0%
1.0% 1.0% 1.0% 2.0%

Decoding False Positives in ISAT

When the IVA fails to recognize the real intent of the user, it sends a wrong response causing False positives, thereby affecting the user experience negatively.

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Combusting Bot Breaks in ISAT

An IVA ‘breaks’ when it is unable to recognize the intent of the user. An IVA designer configures a response to be sent to the user in such a scenario to convey the context and scope of the IVA.

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ISAT Case Study

For one of the world’s largest insurance companies, we used the ISAT as a benchmark to improve the quality of the IVA, thereby improving the overall NPS

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