Data-driven product roadmaps

AI Customer Feedback Analysis Agent

Understand what your customers really want

Delegate your feedback analysis to a specialized AI agent. It reads and understands thousands of survey responses, support tickets, and call transcripts to automatically identify key themes, gauge sentiment, and extract actionable insights.

Ideal for

Product Management

Customer Experience

Marketing

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

See AI Customer Feedback Analysis Agent in action

Play video

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    SMC  logo
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    Mars Logo
    Roche logo
    Sony logo
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Quarterly NPS Survey Analysis

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Time comparison

Time comparison

Traditional way

Days of manual tagging

Days of manual tagging

With V7 Go agents

Minutes

Minutes

Average time saved

99%

99%

Why V7 Go

Why V7 Go

Automated Thematic Analysis

Reads thousands of unstructured comments and automatically groups them into key themes (e.g., 'Pricing,' 'Performance,' 'UI/UX'), instantly showing you what customers are talking about.

Automated Thematic Analysis

Reads thousands of unstructured comments and automatically groups them into key themes (e.g., 'Pricing,' 'Performance,' 'UI/UX'), instantly showing you what customers are talking about.

Automated Thematic Analysis

Reads thousands of unstructured comments and automatically groups them into key themes (e.g., 'Pricing,' 'Performance,' 'UI/UX'), instantly showing you what customers are talking about.

Automated Thematic Analysis

Reads thousands of unstructured comments and automatically groups them into key themes (e.g., 'Pricing,' 'Performance,' 'UI/UX'), instantly showing you what customers are talking about.

Sentiment Scoring

Analyzes the language of the feedback to assign a positive, negative, or neutral sentiment score, allowing you to quickly gauge customer happiness at a granular level.

Sentiment Scoring

Analyzes the language of the feedback to assign a positive, negative, or neutral sentiment score, allowing you to quickly gauge customer happiness at a granular level.

Sentiment Scoring

Analyzes the language of the feedback to assign a positive, negative, or neutral sentiment score, allowing you to quickly gauge customer happiness at a granular level.

Sentiment Scoring

Analyzes the language of the feedback to assign a positive, negative, or neutral sentiment score, allowing you to quickly gauge customer happiness at a granular level.

Feature Request Extraction

Identifies and consolidates every product feature request or suggestion from your customer feedback, creating a data-driven input for your product roadmap.

Feature Request Extraction

Identifies and consolidates every product feature request or suggestion from your customer feedback, creating a data-driven input for your product roadmap.

Feature Request Extraction

Identifies and consolidates every product feature request or suggestion from your customer feedback, creating a data-driven input for your product roadmap.

Feature Request Extraction

Identifies and consolidates every product feature request or suggestion from your customer feedback, creating a data-driven input for your product roadmap.

Root Cause Analysis for Churn

Focuses on feedback from detractors or churned customers to pinpoint the root causes of dissatisfaction, providing clear, actionable insights to improve retention.

Root Cause Analysis for Churn

Focuses on feedback from detractors or churned customers to pinpoint the root causes of dissatisfaction, providing clear, actionable insights to improve retention.

Root Cause Analysis for Churn

Focuses on feedback from detractors or churned customers to pinpoint the root causes of dissatisfaction, providing clear, actionable insights to improve retention.

Root Cause Analysis for Churn

Focuses on feedback from detractors or churned customers to pinpoint the root causes of dissatisfaction, providing clear, actionable insights to improve retention.

Multi-Channel Feedback Consolidation

Creates a unified view of customer sentiment by analyzing and consolidating feedback from all your channels: NPS surveys, support tickets, app store reviews, and sales call transcripts.

Multi-Channel Feedback Consolidation

Creates a unified view of customer sentiment by analyzing and consolidating feedback from all your channels: NPS surveys, support tickets, app store reviews, and sales call transcripts.

Multi-Channel Feedback Consolidation

Creates a unified view of customer sentiment by analyzing and consolidating feedback from all your channels: NPS surveys, support tickets, app store reviews, and sales call transcripts.

Multi-Channel Feedback Consolidation

Creates a unified view of customer sentiment by analyzing and consolidating feedback from all your channels: NPS surveys, support tickets, app store reviews, and sales call transcripts.

Trend Monitoring Over Time

Processes feedback on an ongoing basis to track how sentiment and key themes are changing over time, allowing you to measure the impact of your product improvements.

Trend Monitoring Over Time

Processes feedback on an ongoing basis to track how sentiment and key themes are changing over time, allowing you to measure the impact of your product improvements.

Trend Monitoring Over Time

Processes feedback on an ongoing basis to track how sentiment and key themes are changing over time, allowing you to measure the impact of your product improvements.

Trend Monitoring Over Time

Processes feedback on an ongoing basis to track how sentiment and key themes are changing over time, allowing you to measure the impact of your product improvements.

Customer voices

Customer voices

Connect AI to the voice of your customer.

Connect AI to the voice of your customer.

Turn unstructured feedback into your most valuable strategic asset.

Turn unstructured feedback into your most valuable strategic asset.

Finance

Legal

Insurance

Tax

Real Estate

Finance

Legal

Insurance

Tax

Real Estate

Finance

Legal

Insurance

Tax

Real Estate

Customer Voices

Features

Features

Results you can actually trust.
Reliable AI document processing toolkit.

Results you can trust.
Trustworthy AI document processing toolkit.

Supporting complex documents.

Up to 200 pages.

Customer feedback is everywhere. This agent is built to find insights in any unstructured text format, from multi-tab survey export spreadsheets to messy email threads and raw transcripts from support calls.

Input types

50+ languages

Free-Text Surveys

200 pages

Multi-modal

Document types

PDFs

URL

Tables

Emails

Spreadsheets

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.

Up to 200 pages.

Customer feedback is everywhere. This agent is built to find insights in any unstructured text format, from multi-tab survey export spreadsheets to messy email threads and raw transcripts from support calls.

Input types

50+ languages

Free-Text Surveys

200 pages

Multi-modal

Document types

PDFs

URL

Tables

Emails

Spreadsheets

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Supporting complex documents.

Up to 200 pages.

Customer feedback is everywhere. This agent is built to find insights in any unstructured text format, from multi-tab survey export spreadsheets to messy email threads and raw transcripts from support calls.

Input types

50+ languages

Free-Text Surveys

200 pages

Multi-modal

Document types

PDFs

URL

Tables

Emails

Spreadsheets

Vendor_US.xlsx

3

Supply_2023.pptx

Review_Legal.pdf

Reach 99% accuracy rate

through GenAI reasoning.

Good product decisions require a nuanced understanding of feedback. The agent uses AI reasoning to accurately interpret customer comments, distinguish between a bug report and a feature request, and correctly gauge sentiment.

Model providers

Security note

V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.

Answer

Type

Text

Tool

o4 Mini

Reasoning effort

Off

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Reach 99% accuracy rate

through GenAI reasoning.

Good product decisions require a nuanced understanding of feedback. The agent uses AI reasoning to accurately interpret customer comments, distinguish between a bug report and a feature request, and correctly gauge sentiment.

Model providers

Security note

V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.

Answer

Type

Text

Tool

o4 Mini

Reasoning effort

Off

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Reach 99% accuracy rate

through GenAI reasoning.

Good product decisions require a nuanced understanding of feedback. The agent uses AI reasoning to accurately interpret customer comments, distinguish between a bug report and a feature request, and correctly gauge sentiment.

Model providers

Security note

V7 never trains models on your private data. We keep your data encrypted and allow you to deploy your own models.

Answer

Type

Text

Tool

o4 Mini

Reasoning effort

Off

Low

Mid

High

AI Citations

Inputs

Set a prompt (Press @ to mention an input)

Trustworthy results,

grounded in reality.

You can trust the insights you share with your team. Every identified theme, feature request, or sentiment score is visually linked back to the original customer comment, providing a clear and undeniable source for every data point.

Visual grounding in action

00:54

Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.

Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.

Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.

Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.

Prior Warning and Ignoring Compliance

02

01

01

02

Trustworthy results,

grounded in reality.

You can trust the insights you share with your team. Every identified theme, feature request, or sentiment score is visually linked back to the original customer comment, providing a clear and undeniable source for every data point.

Visual grounding in action

00:54

Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.

Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.

Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.

Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.

Prior Warning and Ignoring Compliance

02

01

01

02

Trustworthy results,

grounded in reality.

You can trust the insights you share with your team. Every identified theme, feature request, or sentiment score is visually linked back to the original customer comment, providing a clear and undeniable source for every data point.

Visual grounding in action

00:54

Deliberate Misrepresentation: During the trial, evidence was presented showing that John Doe deliberately misrepresented his income on multiple occasions over several years. This included falsifying documents, underreporting income, and inflating deductions to lower his tax liability. Such deliberate deception demonstrates intent to evade taxes.

Pattern of Behavior: The prosecution demonstrated a consistent pattern of behavior by John Doe, spanning several years, wherein he consistently failed to report substantial portions of his income. This pattern suggested a systematic attempt to evade taxes rather than mere oversight or misunderstanding.

Concealment of Assets: Forensic accounting revealed that John Doe had taken significant steps to conceal his assets offshore, including setting up shell companies and using complex financial structures to hide income from tax authorities. Such elaborate schemes indicate a deliberate effort to evade taxes and avoid detection.

Failure to Cooperate: Throughout the investigation and trial, John Doe displayed a lack of cooperation with tax authorities. He refused to provide requested documentation, obstructed the audit process, and failed to disclose relevant financial information. This obstructionism further supported the prosecution's argument of intentional tax evasion.

Prior Warning and Ignoring Compliance

02

01

01

02

Enterprise grade security

for high-stake industries.

Customer feedback often contains Personally Identifiable Information (PII). V7 Go is built to protect this sensitive data, processing all your survey and ticket information within your secure, private environment.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for high-stake industries.

Customer feedback often contains Personally Identifiable Information (PII). V7 Go is built to protect this sensitive data, processing all your survey and ticket information within your secure, private environment.

Certifications

GDPR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

Enterprise grade security

for high-stake industries.

Customer feedback often contains Personally Identifiable Information (PII). V7 Go is built to protect this sensitive data, processing all your survey and ticket information within your secure, private environment.

Certifications

GPDR

SOC2

HIPAA

ISO

Safety

Custom storage

Data governance

Access-level permissions

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Next steps

Next steps

Building your roadmap on guesswork?

Send us an export of your latest survey data or support tickets. We'll show you the data-driven insights our AI agent can provide to guide your strategy.

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

Uncover hidden liabilities

in

supplier contracts.

V7 Go transforms documents into strategic assets. 150+ enterprises are already on board:

  • Mercedes-Benz logo
    SMC  logo
    Philips logo
    Bayer Logo
    Mars Logo
    Roche logo
    Sony logo
    Alaris logo

Answers

Answers

What you need to know about our

AI Customer Feedback Analysis Agent

What sources of customer feedback can it analyze?

The agent can analyze any text-based feedback, including survey responses (NPS, CSAT), support tickets from systems like Zendesk, online reviews from sites like G2, and transcripts from sales or support calls.

+

What sources of customer feedback can it analyze?

The agent can analyze any text-based feedback, including survey responses (NPS, CSAT), support tickets from systems like Zendesk, online reviews from sites like G2, and transcripts from sales or support calls.

+

What sources of customer feedback can it analyze?

The agent can analyze any text-based feedback, including survey responses (NPS, CSAT), support tickets from systems like Zendesk, online reviews from sites like G2, and transcripts from sales or support calls.

+

How do we define the themes or categories for the analysis?

You have two options: you can provide a predefined list of categories for the agent to use, or you can allow the agent to use its own reasoning to discover and create emergent themes based on what it finds in the data.

+

How do we define the themes or categories for the analysis?

You have two options: you can provide a predefined list of categories for the agent to use, or you can allow the agent to use its own reasoning to discover and create emergent themes based on what it finds in the data.

+

How do we define the themes or categories for the analysis?

You have two options: you can provide a predefined list of categories for the agent to use, or you can allow the agent to use its own reasoning to discover and create emergent themes based on what it finds in the data.

+

Is the sentiment analysis accurate? Sarcasm can be tricky.

Modern AI models are increasingly adept at understanding nuance and sarcasm. While not perfect, the agent provides a strong directional analysis. Most importantly, every sentiment score is linked back to the source text, so you can always see the original context.

+

Is the sentiment analysis accurate? Sarcasm can be tricky.

Modern AI models are increasingly adept at understanding nuance and sarcasm. While not perfect, the agent provides a strong directional analysis. Most importantly, every sentiment score is linked back to the source text, so you can always see the original context.

+

Is the sentiment analysis accurate? Sarcasm can be tricky.

Modern AI models are increasingly adept at understanding nuance and sarcasm. While not perfect, the agent provides a strong directional analysis. Most importantly, every sentiment score is linked back to the source text, so you can always see the original context.

+

Can it tell me which customers are at risk of churning?

The agent can identify customers who express strong negative sentiment or repeatedly mention critical issues. By integrating with your CRM, this analysis can be used to create a 'health score' or automatically flag at-risk accounts for your Customer Success team.

+

Can it tell me which customers are at risk of churning?

The agent can identify customers who express strong negative sentiment or repeatedly mention critical issues. By integrating with your CRM, this analysis can be used to create a 'health score' or automatically flag at-risk accounts for your Customer Success team.

+

Can it tell me which customers are at risk of churning?

The agent can identify customers who express strong negative sentiment or repeatedly mention critical issues. By integrating with your CRM, this analysis can be used to create a 'health score' or automatically flag at-risk accounts for your Customer Success team.

+

How is this different from the text analysis tools in SurveyMonkey or Zendesk?

Those tools are excellent for analyzing data within their own silos. This agent's power is in consolidating and synthesizing feedback from *all* your channels—surveys, tickets, calls, reviews—into a single, unified view of the customer.

+

How is this different from the text analysis tools in SurveyMonkey or Zendesk?

Those tools are excellent for analyzing data within their own silos. This agent's power is in consolidating and synthesizing feedback from *all* your channels—surveys, tickets, calls, reviews—into a single, unified view of the customer.

+

How is this different from the text analysis tools in SurveyMonkey or Zendesk?

Those tools are excellent for analyzing data within their own silos. This agent's power is in consolidating and synthesizing feedback from *all* your channels—surveys, tickets, calls, reviews—into a single, unified view of the customer.

+

What is the output of the analysis?

The output is typically a structured dashboard or spreadsheet that summarizes the findings, including charts of key themes, sentiment trends, and a prioritized list of feature requests, all with drill-down capability to the source comments.

+

What is the output of the analysis?

The output is typically a structured dashboard or spreadsheet that summarizes the findings, including charts of key themes, sentiment trends, and a prioritized list of feature requests, all with drill-down capability to the source comments.

+

What is the output of the analysis?

The output is typically a structured dashboard or spreadsheet that summarizes the findings, including charts of key themes, sentiment trends, and a prioritized list of feature requests, all with drill-down capability to the source comments.

+