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app.athenahq.ai/glossary

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Purpose

The Glossary page serves as an educational reference guide for customers to understand the terminology, metrics, and data models used throughout the AthenaHQ platform. As customers navigate their dashboards, they will inevitably encounter specialized concepts, like Share of Voice, Priority Score, or how volume estimation is calculated. This page centralizes the definitions and mathematical formulas for these concepts in an easy-to-read, accordion-style layout. By reading the Glossary, customers can better understand how to interpret their AI search performance data, how AthenaHQ consumes their credits, and how various metrics relate to their overall brand visibility.

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What’s on the page

Page Header Displays the simple title “Glossary” at the top left of the page view. Glossary Accordion List A vertically stacked list of collapsible cards. Each card covers one specific glossary topic. By default, the first topic is expanded, and the rest are collapsed. How does AthenaHQ’s volume estimation work? An expanded section that explains the Query Volume Estimation Model (QVEM). It outlines the public and private data sources used, the machine learning pipeline that normalizes the data, and how it derives advanced metrics like Prompt Value, Prompt Opportunity, and Ad Spend Savings. It includes a visual flowchart image mapping the data journey. Stream Data A section explaining how AthenaHQ streams active prompts against multiple AI models to receive responses. It defines “Fan-out” (streaming prompts with variations to increase diversity) and details how credit usage is calculated depending on whether a customer uses a single stream or a scheduled recurring stream. Brand Mention Rate Provides the definitions and mathematical formulas for both Relative Mention Rate and Absolute Mention Rate. It includes easy-to-understand worked examples showing how these percentages change based on how often a brand is mentioned compared to its competitors or compared to total responses. Share of Voice (SOV) Explains Share of Voice as a percentage of mentions a brand receives relative to the total number of all brand mentions across tracked prompts. Includes the SOV mathematical formula and a step-by-step example calculating the SOV for a brand and two competitors out of a total pool of mentions. Priority Score Breaks down the Priority Score metric, which weighs which topics need immediate attention. Displays the formulas for calculating the “Raw Score” (factoring in Missing Mention percentages, Missing Sentiment percentages, and Prompt Count Bonuses) and the final normalized “Priority Score.” Model-Based Filtering Clarifies how metrics behave when a user filters their dashboard by a specific AI model (like ChatGPT or Claude). It notes that when a filter is applied, all metrics recalculate using only data from that platform to help spot visibility differences across models. Traffic Source Metrics A brief explanation of metrics related to the distribution of inbound traffic coming from different AI platforms to the customer’s website.

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What you can do here

  • Expand / Collapse glossary sections: You can click anywhere on a topic’s header bar (or the chevron arrow icon on the far right) to toggle the card open or closed. Opening a card reveals its detailed explanation, formulas, and examples.

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Data shown

The definitions, formulas, and diagrams shown on this page are static, educational content written by the AthenaHQ team. Unlike analytics dashboards, this page does not load live data specific to the user’s workspace. However, the page does check the active workspace’s subscription plan, it requires an active paid subscription to render.

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Common workflows

1. Browse all glossary terms
  1. Navigate to the Glossary from the main sidebar navigation.
  2. The page loads with the first section (“How does AthenaHQ’s volume estimation work?”) expanded by default.
  3. Click any other section header in the list to expand it and read the definitions or formulas.
  4. Click the same header again to collapse it, keeping the page tidy.
2. Review a metric formula from another page
  1. While looking at analytics (e.g., Share of Voice or Priority Score) on another dashboard, a customer might click an inline link that says “Understand additional formulas in the glossary →”.
  2. This link takes them to the Glossary page.
  3. The page automatically scrolls to and expands the exact metric they were inquiring about.
  4. The customer reads the full formula and worked example to understand their data.

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Empty, loading, and error states

  • Empty / Error State: If the customer’s active workspace does not have an active subscription (for instance, if they are on a completely free plan or their subscription has lapsed/expired), the Glossary page will render completely blank. No UI or error message is shown; it simply stops rendering.
  • Loading State: Because the text is static, there is no explicit loading spinner for the glossary content. It appears immediately once the page shell loads.
  • Linked from: The main navigation sidebar. It is also heavily linked from inline tooltips and information callouts on analytics dashboards (e.g., “Understand additional features in the glossary →”).
  • Links to: The page does not contain outward links to other parts of the application. It does support self-referential deep-linking (using URL hash anchors like /glossary#share-of-voice) to jump to specific sections.

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Common support questions

Why is my Glossary page completely blank? The Glossary page requires an active subscription to view. If your trial has ended, your subscription payment failed, or you are on a restricted free plan, the page will not load. Once a subscription is activated, the content will appear. How does Athena calculate Priority Score? You can direct the customer to the Glossary, specifically the “Priority Score” section, which breaks down the math: it relies on a “Raw Score” made up of Missing Mentions (70% weight) and Missing Sentiment (30% weight), multiplied by a Prompt Count Bonus, which is then normalized into a 0-100% score. Where does Athena get the data for search volumes? Direct the customer to the very first section in the Glossary. It explains that AthenaHQ uses the Query Volume Estimation Model (QVEM), which pulls from both public search platforms and private third-party data providers, cleaning and normalizing it through a machine learning pipeline. How are my credits being consumed when I schedule prompts? The “Stream Data” section of the Glossary explains this formula clearly. Scheduled streams calculate credits based on: Prompts × Fan-out × Model Credits × Days per week × 4.33 weeks.