> ## Documentation Index
> Fetch the complete documentation index at: https://rankahead.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# GEO Tasks: Kanban Board for AI Optimization

> Plan and track your generative engine optimization actions with a kanban board organized by category, impact, effort, and target LLM provider.

The GEO tasks board is a kanban-style workspace for planning and tracking the actions that improve your brand's presence in AI-generated answers. Each task represents a specific optimization action — writing a piece of content, adding schema markup, building citations, or engaging in forums. You assign an impact score and an effort score to each task so you can prioritize the work that moves the needle most efficiently.

## Board columns

The board has three columns that represent the status of each task.

<CardGroup cols={3}>
  <Card title="To do" icon="circle">
    Tasks you've identified but haven't started yet.
  </Card>

  <Card title="In progress" icon="loader">
    Tasks you're actively working on.
  </Card>

  <Card title="Done" icon="circle-check">
    Completed tasks you want to keep for reference.
  </Card>
</CardGroup>

You can move tasks between columns by dragging them or by editing the task and changing its column field.

## Task categories

Every task belongs to one of four categories. The category describes the type of GEO action the task represents.

<AccordionGroup>
  <Accordion title="Content gap">
    A **content gap** task involves creating content for topics where your brand is missing from AI-generated answers. AI models answer questions based on what exists on the web — if there's no content on your domain covering a topic, you won't appear in answers about it. Use gap analysis to identify these topics, then create content gap tasks to track the work of filling them.
  </Accordion>

  <Accordion title="Schema markup">
    A **schema markup** task involves adding structured data to your pages so AI models can more easily parse and understand your content. Schema types like `FAQPage`, `HowTo`, `Article`, and `Organization` make it easier for AI systems to extract and cite accurate information from your site.
  </Accordion>

  <Accordion title="Citation building">
    A **citation building** task involves getting your domain cited on other authoritative sites — industry publications, directories, partner pages, and similar sources. AI models use citations to establish credibility. The more your domain is mentioned in trustworthy contexts, the more likely it is to be cited in AI-generated answers.
  </Accordion>

  <Accordion title="Forum presence">
    A **forum presence** task involves engaging in forums and community platforms like Reddit and Quora. These sites are scraped heavily by AI training pipelines, meaning thoughtful, well-attributed answers in the right threads can surface your brand in AI responses. Tasks in this category typically involve writing responses, asking questions, or building a presence in communities relevant to your domain.
  </Accordion>
</AccordionGroup>

## Create a task

<Steps>
  <Step title="Open the GEO tasks board">
    Navigate to **Content** in the sidebar, then select **GEO tasks**.
  </Step>

  <Step title="Add a new task">
    Click **New task** to open the task creation form.
  </Step>

  <Step title="Set the title">
    Write a clear, specific title that describes the action — for example, "Add FAQ schema to pricing page" or "Publish comparison article: us vs. competitor X."
  </Step>

  <Step title="Choose a category">
    Select the category that best fits the type of work: **Content gap**, **Schema markup**, **Citation building**, or **Forum presence**.
  </Step>

  <Step title="Score impact and effort">
    Assign an **impact** score (1–5) and an **effort** score (1–5).

    * **Impact** reflects how much completing this task is expected to improve your AI visibility.
    * **Effort** reflects how much work is required to complete the task.

    See [Prioritizing tasks](#prioritizing-tasks) below for guidance on how to use these scores.
  </Step>

  <Step title="Select a column">
    Choose the column this task should start in — typically **To do** for new work you haven't started.
  </Step>

  <Step title="Target LLM providers (optional)">
    Tag the task with one or more LLM providers if the task is specifically aimed at improving visibility in a particular AI system. Available providers include **ChatGPT**, **Perplexity**, **OpenAI**, **Anthropic**, and **Google**, among others.
  </Step>

  <Step title="Add notes (optional)">
    Use the notes field for context, research, links, or anything else your team needs to execute the task.
  </Step>

  <Step title="Link a prompt (optional)">
    If the task is related to a specific tracking prompt, link it using the prompt field. This lets you monitor whether your visibility on that prompt changes after the task is complete.
  </Step>

  <Step title="Save the task">
    Click **Save**. The task appears in the column you selected.
  </Step>
</Steps>

## Prioritizing tasks

Use the impact and effort scores to decide what to work on first. The most efficient tasks are those with **high impact and low effort** — they deliver the most improvement for the least work.

A simple way to think about prioritization:

| Priority       | Impact     | Effort     | Action                  |
| -------------- | ---------- | ---------- | ----------------------- |
| Quick wins     | High (4–5) | Low (1–2)  | Do these first          |
| Major projects | High (4–5) | High (4–5) | Plan and schedule       |
| Fill-ins       | Low (1–2)  | Low (1–2)  | Do when capacity allows |
| Avoid          | Low (1–2)  | High (4–5) | Deprioritize or drop    |

<Tip>
  When you're unsure about impact, use your prompt data as a signal. If a topic has a high number of impressions in AI answers but your brand doesn't appear, content covering that topic likely has high impact.
</Tip>

## Targeting specific LLMs

Not all optimization actions affect every AI system equally. Forum presence on Reddit, for example, has a stronger effect on models that draw from community content, while schema markup may be more relevant for Google AI Overviews. When you know a task is specifically aimed at a particular model, tag it with the relevant LLM providers.

Tagging tasks with target LLMs helps you:

* Filter the board to see work focused on a specific provider
* Distribute effort across different AI systems intentionally
* Identify gaps in your optimization strategy for a particular model

<Info>
  LLM provider tags are organizational — they don't change how Rankahead generates or publishes content. They're a way for your team to stay aligned on which tasks target which AI systems.
</Info>

## Move tasks between columns

Move a task to reflect its current status:

* **Drag and drop** — grab the task card and drop it into a different column on the board
* **Edit the task** — open the task, change the **Column** field, and save

Keep the board up to date so your team has an accurate picture of what's in flight and what's finished.

## Link a task to a prompt

Linking a task to a tracking prompt lets you correlate your optimization work with changes in AI visibility. After you complete the task, monitor the linked prompt's results over the following weeks to see whether your brand's presence in AI answers improved.

To link a prompt, open the task and select from the **Prompt** dropdown. Any prompt you've created for the selected domain is available to link.

<Tip>
  Create a habit of reviewing linked prompt data 2–4 weeks after marking a task as done. This gives AI models time to index and incorporate any new content or signals from your work.
</Tip>