Home Conversations and Dashboard | Monitoring ClaudIA
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Conversations and Dashboard | Monitoring ClaudIA

Conduct audits to optimize ClaudIA's content and monitor all your conversations and generated data
FabrĂ­cio Rissetto
Ariana Carvalho
By FabrĂ­cio Rissetto and 5 others
‱ 12 articles

How to Use the ClaudIA Metrics Dashboard

When to use - You want to understand how to use the ClaudIA Metrics Dashboard end to end - You need to know what each tab shows and how to filter by project and period - You want to understand why conversations were transferred to N2 and how that connects to your settings - You are getting started with the dashboard and want a visual onboarding (video in Portuguese, English, or Spanish) Prerequisites - Access to the ClaudIA project Hub with the Dashboard enabled About this article The Metrics Dashboard is the consolidated view of your project's ClaudIA performance. It updates automatically and brings together, in one place, retention, quality (CSAT and GenCX Score), transfer reasons, content usage, and flow performance. This article explains how to navigate the dashboard and includes the explainer videos in three languages. How to access and filter Open the dashboard from the project Hub (with the Dashboard enabled). At the top of the screen, use the global filters — they apply to every chart: - Project — selects the operation being analyzed - Start date / End date — the time range applied to all cards - Aggregation (day / week / month) — granularity of the time series How the Dashboard is organized The dashboard is split into tabs, each with an analysis focus: | Tab | What it is for | |---|---| | General Information | Overview: ticket volume, retention vs. goal, response time, and reasons for transfer to N2 | | CSAT | Customer-reported satisfaction, response rate, and breakdown by tag | | GenCX Score | AI-evaluated quality (% of bad cases), including by tag | | Tags | Volume, retention, and CSAT by topic/tag | | Content | Usage of N1/N2/interactive content, retention, and content that most often transfers | | Controlled Flows | Eddie flow performance (executions, drop-off, retention, escalations) | | Classifier and Clarifier | Clarification activations and cases with a high chance of missing content | | Bot Handoff (Asked for Human) | Topics that most drive human requests and content used before the request | | Audit | Audited errors by content, tag, and criticality | | Agentic Usage | Metrics for conversations where Agentic was triggered | | Data to export | Ticket and content listings for external analysis | The structure repeats by dimension (parallelism) One thing that makes the dashboard much easier to read: the same business metrics are repeated for every analysis dimension. In other words, the same "kit" of indicators — Usage, Tickets, Retention, CSAT, and GenCX Score — is available by Content, by Tag, and by Eddie/Flow. Learning to read one dimension means you can read them all. | Dimension | Where to find it | Available metrics | |---|---|---| | Content (section) | Content tab | Usage, tickets, retention, CSAT, GenCX + how much each content transfers to N2 | | Tag (topic) | Tags tab | Volume, tickets, retention, CSAT, GenCX over time | | Eddie / Flow | Controlled Flows tab | Executions, drop-off, tickets, retention, CSAT, escalations | Because the lens is the same, you read any dimension in the same order: Volume → Retention → Quality (CSAT/GenCX) → dig deeper into whatever is off. What you can do with this data (business applications) The dashboard is not just a scoreboard — it points to where to act. Some practical uses: - Prioritize content: find content with low retention or heavy N2 usage and prioritize creating/adjusting material — the most direct path to raising retention. - Turn N2 into N1: the card "Top content transferring to N2 - Potential to increase Retention" lists content currently resolved in N2 that could become N1. Each one is a concrete retention opportunity. - Fix section selection: "N2 Section Selection Errors — Used vs Correct" shows where ClaudIA used the wrong section — a direct content-review backlog. - Assess quality by topic: cross CSAT and GenCX Score by Tag to find topics with the worst experience and act on the prompt or the content for that topic. - Measure each Eddie/Flow's ROI: compare retention, drop-off, and escalations per flow to decide which to keep, adjust, or retire. - Close gaps that drive "Asked for Human": the Bot Handoff (Asked for Human) tab shows the topics that most request a human and the content used right before the request — great to discover what is missing. - Diagnose transfers: use the Reason for Transfer to N2 (below) to tie each handoff to a setting and prioritize the right fix. - Export for external analysis: the Data to export tab provides ticket and content listings for your own cross-analysis or A/B test tracking. :::info Drill-down example — transfers by N2 content. If you notice many conversations going to N2 because of N2 content, you can investigate in layers: 1. Open the "Top content transferring to N2" card and identify the content that transfers the most. 2. Use the Hub links (by content / by reason) to open the real tickets for that content. 3. Decide the action: turn the content into N1 (if ClaudIA can resolve it on its own) or fix/complete the material when the selection was right but the answer was incomplete. ::: Overview: "Resolution Reason N2" metrics (Reason for Transfer to N2) In the General Information tab, the card "Percentage of Tickets by Reason for Transfer to N2" shows why each conversation ended in N2 (transferred to a human). The key point: each reason maps directly to a behavior or setting in your operation. The friendly label shown in the chart corresponds to a rule you defined for ClaudIA — so this card works as a diagnosis of your own configuration. If a reason grows, you know exactly which setting to review. | Reason shown in the Dashboard | What it means / related setting | |---|---| | Customer asked for a human | The customer explicitly requested to talk to an agent | | Frustration detected | Frustration detection identified dissatisfaction in the conversation | | Negative feedback in the satisfaction check | The in-conversation satisfaction check indicated the problem was not solved | | ClaudIA was not confident in the answer | The confidence/attempt limit was reached | | Number of interactions above the message limit | The conversation went past the configured message limit | | ClaudIA went more than 10 minutes without responding | Handover by timeout (no response within the time window) | | Clarification attempt limit reached | The clarifier ran out of attempts to clarify the question | | ClaudIA detected a transfer action | A transfer message/action defined in content was triggered | | ClaudIA used N2 content / N2 content was first in the TOPK / Section reuse limit reached | Rules tied to content marked as N2 in the knowledge base | | No relevant content found | There was no content in the base to answer the request | | Eddie transferred / Error calling Eddie / Repeated Eddie flow / Incorrect use of Eddie | Behavior of controlled flows (Eddie) | | Escalated outside human service hours | The transfer happened outside the configured service hours | | Escalated due to an attachment | The conversation received an attachment and was transferred | | Forced N2 handover | A forced-handover rule was applied | | Multiprompt | The N2 answer was returned via multiprompt | :::info Next to it, in the same card group, "Links to access the Hub - Resolution Reason" takes you straight to the tickets for each reason in the Hub — useful to inspect real examples and understand what led to the transfer. ::: Videos by language Prefer a step-by-step video? Watch the full Metrics Dashboard tutorial in three languages: đŸ‡§đŸ‡· Portuguese (Brazil) https://youtu.be/PxY58YqvGUQ đŸ‡ș🇾 English https://youtu.be/yrsvO3rgzqQ đŸ‡Ș🇾 Spanish https://youtu.be/D524FmoNdX8 Notes - To understand the settings that trigger each transfer reason: ClaudIA Settings — Transfer and ClaudIA Settings — Behavior - To track retention: How to Improve Claudia's Retention? - To use the GenCX Score: How to best use the Gen CX Score - To understand CSAT: How to improve ClaudIA's quality (CSAT)

Last updated on Jul 20, 2026

📊 How to Improve Claudia's Retention?

Explanation of each tab, chart, and table, along with important notes on how to use and interpret the data. 🧭 General Structure of the Retention Section 📌 Important: - The start and end date filters do not apply; they only apply to the main metrics tab. Data is organized in fixed and complete weeks to ensure performance and standardization of analyses. - All percentages shown in the tables are relative to the total tickets for that week. For example, if an escalation reason appears with 2%, it means that 2% of all tickets in that week had that cause. đŸ§© Tab 1 – Retention Metrics - Overall This is the managerial tab, used to monitor progress, goals, and offenders in a consolidated manner. đŸ”¶ Chart: “Total Tickets × % Retained per Week” - Orange bars: total tickets received per week. - Orange line: percentage of tickets retained by Claudia (without escalation). - Helps understand volume trends and AI effectiveness. đŸ”¶ Side indicators: - Retention goal (set in the current operation's target) - Difference from last week vs. goal - Last week's retention - Maximum retention in the last 8 weeks - Average retention in the last 8 weeks đŸ”¶ Table: “Percentage of Tickets by N2 Reason” - Shows the main reasons for escalation to N2, week by week. - Highlights the main offender from the past 4 weeks, with an average value. - Helps identify persistent patterns or reasons, such as use of N2 content or transfer by Controlled Flow. 🛠 Tactical / Operational Tabs These tabs aim to support fine-tuning, content review, and case analysis. The structure is similar across all: 📁 Tab: Used N2 Content đŸ”¶ Table: “Retention Gain Potential by Content – Last 8 Weeks” - Displays the most recurring N2 articles in escalated tickets. - Weekly columns show the percentage contribution of each content item relative to total tickets handled by AI. - Use to prioritize adjustments and migration of content to N1 or interactive (Controlled Flow). đŸ”¶ Table: “Retention Gain Potential by Tags – Last 8 Weeks” - Shows the most recurring tags in escalated tickets. - Weekly columns indicate the contribution percentage of each tag relative to total tickets handled by AI. - Use to prioritize adjustments related to themes/tags. đŸ”¶ Chart: “Top Contents and % Retention Potential – Last 14 Days” - Shows the accumulated retention percentage that could be achieved by optimizing the Top N contents. - Example: optimizing the top 10 contents could yield an approximate 7.7% gain in retention. - Clearly demonstrates the impact of prioritizing adjustments on the right articles. đŸ”¶ Table: “Section Selection Errors – Used vs. Correct” - Shows when Claudia used incorrect content, based on support feedback. - Displays which section was used and which should have been (N1 or INTERACTIVE). - Helps identify content usage issues. 📁 Tab: Transferred by Controlled Flow (by design) đŸ”¶ Table: “Retention Potential (%) by Controlled Flow” - Indicates which Controlled Flows appear most frequently in escalations. - Values per week, allowing trend analysis. - Used to prioritize content or flow structure adjustments. đŸ”¶ Table: “Tickets Escalated by Flow” - Lists real tickets, transfer reasons, and flow links. - Serves for validation and context review. 📁 Tab: Customer Requested Human đŸ”¶ Chart: “Agent Interactions Before Handover” - Shows how many messages the customer exchanged with Claudia before requesting human support. - If most cases fall in the 3 to 5 interactions range, it may indicate lack of initial engagement or ineffective content. đŸ”¶ Table: “Tickets by Interaction Range” - Lists tickets corresponding to the interaction range depicted in the chart. đŸ”¶ Chart: “Top 5 Topics Customers Ask for Human Support” - Shows the most common topics where customers request human support. - Column: absolute volume of tickets | Line: % of total requests. - Helps identify topics with perceived low performance. đŸ”¶ Table: “Content Used Before Customer Requests Human” - Indicates which contents were shown by Claudia before the customer requested support. - Useful to understand if content contributed to frustration or confusion. 📁 Tab: Transferred Due to Controlled Flow Call Failure đŸ”¶ Table: “Controlled Flow Call Error % by Flow” - Shows flows that failed in technical calling, leading to escalation. - Used to identify infrastructure issues or bugs. đŸ”¶ Table: “Tickets with Call Error by Flow” - Lists tickets and flows with errors. - Ideal for validation with the technical team and specific fixes. 📁 Tab: Transferred Due to Controlled Flow Repetition đŸ”¶ Table: “% of Controlled Flow Repetitions by Period” - Indicates which flows reached the attempt limit without resolution. - Shows problems with content effectiveness or the need to adjust the number of attempts. 🧠 Best Practices for Analysis - Use the main tab to monitor overall progress, goals, and major offenders. - Use the tactical tabs to explore specific causes and prioritize content, flow, or response model adjustments. - Always consult ticket links when validating with real examples. If you have questions on how to interpret any data or want to suggest dashboard improvements, contact our team! We’re here to help 🧡

Last updated on Jun 24, 2026

Como auditar as mensagens da ClaudIA

Nessa FAQ e vĂ­deo apresentamos em detalhe como funciona a lĂłgica por trĂĄs da seleção de seçÔes utilizadas pela ClaudIA e a funcionalidade de tagueamento (Tagger) ao encerrar um ticket. TambĂ©m explicamos como auditar esse dado diretamente no Hub, para que vocĂȘ possa receber insights atravĂ©s do Dashboard da Claudia para melhorar o tagueamento. https://www.loom.com/share/f6601cbe38b6400da3830e8fd0d52230 SessĂ”es utilizadas pela ClaudIA: o que sĂŁo, por que importam e como auditar O que sĂŁo “sessĂ”es utilizadas”? Toda vez que a ClaudIA responde a um cliente, ela consulta uma ou mais seçÔes do seu conteĂșdo base (N1 ou N2) para construir a resposta. Essas seçÔes sĂŁo chamadas de sessĂ”es utilizadas. Ou seja, sĂŁo os blocos de conhecimento que a IA usou para formular a resposta enviada ao cliente. 🎯 Por que isso Ă© importante? Essa informação Ă© fundamental para: 1. Entender como a ClaudIA estĂĄ raciocinando em cada resposta. 2. Auditar se ela estĂĄ de fato utilizando o conteĂșdo certo. 3. Treinar e melhorar o comportamento da IA, identificando quando sessĂ”es estĂŁo sendo usadas incorretamente. 4. Definir a tag da conversa: a sessĂŁo com maior peso influencia o algoritmo de tagueamento automĂĄtico. 5. Detectar quando hĂĄ transferĂȘncia para N2, e se ela foi feita com base em conteĂșdo correto. O que foi lançado Agora, vocĂȘ pode: - Ver diretamente quais sessĂ”es foram utilizadas em cada resposta da ClaudIA. - Dar feedback positivo ou negativo sobre o uso dessas sessĂ”es. - Auditar a tag final da conversa com base nas sessĂ”es utilizadas. Como visualizar as sessĂ”es utilizadas 1. Acesse qualquer tĂ­quete no Hub. 2. Encontre a resposta da ClaudIA. 3. Clique no Ă­cone â„č para abrir o detalhe da resposta. 4. VocĂȘ verĂĄ: - O raciocĂ­nio da ClaudIA (termo consultado + intenção). - As sessĂ”es utilizadas para compor a resposta. - Um Ă­cone identificando quais sessĂ”es foram usadas (ex: ✅ ou Ă­cone destacado). - Se houver sessĂ”es N2, elas tambĂ©m aparecem com destaque. Exemplo prĂĄtico Pergunta do cliente: “VocĂȘs integram com o Zendesk e o Intercom?” Resposta da ClaudIA: “Sim! Temos integração nativa com o Intercom. No caso do Zendesk
” SessĂ”es utilizadas: - N1 - IntegraçÔes Intercom - N2 - Zendesk Integração via API Resultado: - A ClaudIA usou conteĂșdo de duas sessĂ”es. - Como uma delas era N2, a conversa foi automaticamente escalada. - A tag da conversa ficou como: Interesse em contratação, pois era a sessĂŁo mais relevante. Como auditar sessĂ”es utilizadas 1. Ao revisar uma conversa, clique no Ă­cone â„č de qualquer resposta. 2. Veja quais sessĂ”es foram marcadas como utilizadas. 3. Avalie se realmente fazem sentido com base na resposta. 4. Clique em 👍 ou 👎 para dar seu feedback sobre o uso da sessĂŁo. Importante: Isso avalia apenas se a sessĂŁo marcada foi usada corretamente, nĂŁo se a resposta foi boa ou ruim. 5. Caso a resposta esteja errada, siga com a auditoria normal no fim do tĂ­quete. O que acontece com esse feedback? - Permite avaliar se a ClaudIA estĂĄ utilizando as sessĂ”es mais adequadas para cada tipo de solicitação. - Apoia a revisĂŁo do tagueamento automĂĄtico, indicando quando ajustes manuais podem ser necessĂĄrios. - Ajuda nosso time a entender se sessĂ”es N2 estĂŁo sendo usadas corretamente, o que impacta a performance da IA e os critĂ©rios de escalada. Importante: a auditoria, por si sĂł, nĂŁo altera automaticamente o comportamento da ClaudIA. Qualquer melhoria depende de ajustes de conteĂșdo, configuração ou estratĂ©gia definidos a partir dessa anĂĄlise. Dicas rĂĄpidas - ⚠ Às vezes, ClaudIA consulta uma sessĂŁo para confirmar algo, mesmo que a resposta nĂŁo tenha trechos literais do conteĂșdo. Isso ainda conta como uso vĂĄlido. - Se vocĂȘ nĂŁo reconhece o conteĂșdo de uma sessĂŁo na resposta, marque 👎 e descreva brevemente por quĂȘ. - O feedback de sessĂŁo nĂŁo substitui a auditoria da conversa. Ele complementa. O que influencia a tag da conversa? Ao fim do ticket, ClaudIA atribui uma tag baseada na sessĂŁo utilizada com maior score (relevĂąncia). VocĂȘ pode revisar essa tag no processo de auditoria: 1. VĂĄ atĂ© o final da conversa. 2. Revise se a tag atribuĂ­da corresponde ao conteĂșdo e intenção. 3. Caso queira alterar, selecione a tag correta e envie a auditoria. Onde tudo isso impacta? - Dashboards de temas atendidos - Indicadores de retenção e escalada - Performance da ClaudIA por sessĂŁo ou assunto - Qualidade das sugestĂ”es automĂĄticas de melhoria - Faturamento (em alguns contratos baseados em sessĂ”es)

Last updated on Apr 13, 2026

Filters and Search System in Conversation

Filters 1. What is the Session ID used filter? This filter allows you to search for conversations based on the session ID (i.e., what content or section Claudia used in the response). To use this filter, you need to enable it in the Hub settings: go to Settings → Other Settings → Show Session ID filter. 2. How does the Helpdesk ID filter work? This filter allows searching for conversations by the external identifier assigned to the ticket by your support system (such as Zendesk, Freshchat, etc.). In the case of Freshchat, there is a peculiarity: the ID that appears in the URL (the "internal ID") may be different from the ID used in Claudia's filter. To perform the correct search, it may be necessary to convert the internal ID to the ID used by the filter using the Freshchat API or request this conversion from support. 3. What are the Start Date / End Date filters for? These filters limit the time period of the analysis, showing only conversations that were closed within the specified range. They are essential for time-based searches, monthly comparisons, trend analysis, and specific audits. 4. What does the Tags filter mean? Allows filtering only those conversations that received certain tags during their flow or at closing. For example: login_error, billing, complaint. If no tag filter is specified (or "All" is selected), all conversations will be displayed regardless of whether they have tags or not. 5. What is the purpose of the Audit filter? This filter can be used to segment conversations that have already been audited from those that have not. Useful for quality teams, reviews, or controls, to focus only on conversations that have been analyzed or those that need to be analyzed. 6. What can the Identifier (Customer / Agent / AI) filter mean? This field probably defines who initiated the conversation: - Customer — conversation started by the end user - Playground — test conversations created in the Playground screen - Optimizer — batch-created conversations based on system history for evaluation. Usually done before launching new operations This filter helps differentiate automated flows from those initiated by humans. 7. What is the Resolution (N1 / N2) filter for? Although not explicitly documented, it is reasonable to assume this filter classifies the type of resolution of the conversation: - N1 — conversations resolved by AI (ClaudIA) - N2 — conversations that required human intervention (handover) With this, you can measure Claudia's autonomy versus cases that demanded escalation. 8. What does Reason for Resolution mean? This filter lists the recorded reasons when closing a conversation. It indicates which functionality was used to finalize in N1 or to transfer to N2 in each conversation. For a clearer parameter, you can access our FAQ category "Conversation Closure" or view the "Resolution Reason" in the internal note of each conversation. This helps you understand why conversations were closed, in addition to their status. 9. What is the purpose of the A/B Test filter? This filter allows selecting conversations belonging to one of the experiment groups (A or B), useful when you or your team are testing different versions of flow, prompts, or AI models. It is a helpful tool for performance comparison between variations. 10. What does Intent / Topics mean? This filter likely allows selecting conversations based on the LAST topic or intent identified by Claudia. The main use case is filtering cases where: Claudia identified the end and needed to close OR "Bot Sale (Forward to Human Check and Forward to Human Multi-prompt)" 11. What could Gen CX Score be? This field represents a score of experience or sentiment generated by the AI (similar to a customer rating or an internal metric). If available, it allows filtering conversations based on the AI's assessment (positive, neutral, negative). It helps prioritize audits at risk of being detrimental or cases where the AI did not behave as most appropriate. 12. What is the purpose of the Controlled Flow Only filter? It is also a reasonable assumption that this filter allows viewing only conversations responded to by the Controlled Flow model — an advanced or specific version of Claudia. This would be useful to compare Controlled Flow's performance versus the standard AI responses.

Last updated on Jun 24, 2026

How to Make the Best Use of the Gen CX Score

What is the Gen CX Score The Gen CX Score is a "Sentiment" metric assessing customer satisfaction by analyzing the entire conversation context. We use Large Language Models (LLMs) for this evaluation, which can range from: - Good (Score 5) - Neutral (Scores 2, 3, or 4) - Bad (Score 1) We categorize the metric this way instead of the traditional CSAT classification to identify extremes. Want a ticket with excellent service, clearly indicating that the issue was resolved? Look for "Good" Want to see tickets with a high risk of negative experience? Look for "Bad" Fluctuations within Neutral mean it's unclear whether there was a negative experience involving service, process, or product. Why Use the Gen CX Score? The goal of the Gen CX Score is to serve as an auxiliary metric for auditing, quality assessment, and CSAT prevention. It doesn't replace any of the above but can generate valuable auxiliary insights. It helps us gain a clear understanding of quality even when the volume of CSAT responses or audits is low. Additionally, when we start analyzing detailed metrics, the number of evaluations and audits disperses, making conclusions difficult (e.g., Controlled Flow performance or Content) Where and How to Use the Gen CX Score? Identify conversations with a high risk of negative experience: Access Conversations > Filter > Gen CX Score ![Image] (https://cloudchat.cloudhumans.com/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBMktaRmc9PSIsImV4cCI6bnVsbCwicHVyIjoiYmxvYl9pZCJ9fQ==--e6cdd11c91e1e8eb06fd5c852a2c9223afc5f2f6/image.png) Filtering for "Bad" will help identify cases with high friction potential for auditing, content adjustments, or configuration changes. Monitor operation with an auxiliary indicator: Access Dashboard > CSAT and GenCXScore ![Image] (https://cloudchat.cloudhumans.com/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBM0NaRmc9PSIsImV4cCI6bnVsbCwicHVyIjoiYmxvYl9pZCJ9fQ==--42252a30ffd73cafeb57fa3c0891dc0f574f2287/image.png) Keep track of operational performance with an additional indicator. Granular insights into content or Controlled Flows: Access Dashboard > Content or Controlled Flows ![Image] (https://cloudchat.cloudhumans.com/rails/active_storage/blobs/redirect/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBNEdaRmc9PSIsImV4cCI6bnVsbCwicHVyIjoiYmxvYl9pZCJ9fQ==--2406bab85ff86f6b4ee4823688f0d7b8ba24cbdf/image.png) Compare specific content or Controlled Flows results to ensure you have a high number of evaluations per interaction.

Last updated on Jun 24, 2026

How to create custom ClaudIA reports (Report Builder)

When to use - You want to create custom reports with the data from conversations handled by ClaudIA (conversations, messages, generated responses, audit feedback, CSAT and content) - You need to go beyond the Dashboard and build your own tables, filters and cross-analyses - You want to export ClaudIA's data in CSV, XLSX or JSON Prerequisites - Access to the Cloud Chat of your project - Being logged in as a supervisor, CX Engineer or administrator About this article The Report Builder lives in Cloud Chat, but it also covers ClaudIA's data. When building a report, you'll find the ClaudIA Topic, with the tables of the conversations handled by the AI. This article shows where to access it — the full step-by-step is in the Cloud Chat guide (links at the end). How it works Where to access it The Report Builder is opened from Cloud Chat, in the Reports area. It's the same tool used for Cloud Chat reports — the difference is the topic you select when building the query. The ClaudIA Topic When selecting the fields, choose the ClaudIA Topic to work with the data from the conversations handled by the AI: - Conversations and messages - Responses generated by ClaudIA - Audit feedback - CSAT - Knowledge base content What you can do - Select dimensions (groupings) and measures (aggregations) to build the table - Apply advanced filters (dates, multiple conditions, across queries) - Use pivot tables, joins and period-over-period (PoP) analysis - Export in CSV, XLSX or JSON :::info Prefer to track ready-made indicators? Use the ClaudIA Metrics Dashboard. The Report Builder is for when you need to customize the analysis. ::: Notes - Full step-by-step: How to use the Report Builder — complete guide - Tables and columns of the ClaudIA Topic: Explanation of the Report Builder tables and columns - For raw data via spreadsheet: How to get a table with ClaudIA's raw data

Last updated on Jul 22, 2026