Standard Workspaces are the building blocks of Pi Datametrics, consisting of the main groupings of the search terms, markets, and search engines they are tracking. Creating standard workspaces correctly and with the right information is important to gain good results from the tools.

Workspaces and Search Term Groups are how data is structured in Pi.

Workspaces are the primary or parent categorisation of search terms tracked in your account.

A standard workspace focuses on the search results of a single market.

Search Term Groups are a secondary level, sometimes referred to as child categorisation, within Workspaces.

For search terms, the workspace and search term group structure in your account are key to surfacing insights that will keep you ahead of the competition.

You can create Workspace A and Workspace B and within these, you can create search term groups that contain your search terms. This is the structure that is used to create the outputs of Pi's tools:

Standard Workspaces control:

Standard Workspaces should be organised to align with the business goals and objectives of your company and team.

For example, you could create workspaces based only on high traffic terms and another based on high conversion terms, or there could be a workspace assigned to different departments or product categories.

For example, if you have a fashion website, you may set up three workspaces based on product categories:

There can be multiple workspaces depending on the types of search terms, the search engines, and competitor sites where insight is needed. Ultimately, you can have unlimited workspaces.

These are workspaces comprised of search terms in search term groups, tracking for desktop or mobile devices in search engines such as Google, Bing, Baidu, and Google AI mode.

Compound Workspaces are a collection of standard workspaces. They can show a holistic view of multiple workspaces, either to provide an overview of a single market or a horizontal view across multiple markets.

The ability to have a holistic view allows you to gain a broader oversight of a large dataset that may be spread across multiple workspaces.

Rapid Tracking workspaces provide bi-hourly tracking of search terms. Rapid Tracking offers you near real-time visibility on key terms that are of particular interest or important to your business needs.

Group related prompts into LLM Workspaces to track visibility, citations and sentiment by topic.
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The same principle of organising search data around meaningful topics can be applied to LLM monitoring, such as products, categories, audiences, markets or business themes. Rather than analysing individual prompts in isolation, grouping related prompts helps you understand how your brand and content are represented across the topics and business areas that matter to you.

This structure makes it easier to investigate AI-generated search at a broader level, compare performance across areas of interest, and identify which prompt groups warrant closer monitoring.

Pi’s LLM Monitoring tools then allow you to explore the responses generated for these queries and monitor site citations and brand mentions over time.

Think of the LLM data as:

When in LLM workspaces, this can then be applied to Pi's existing data structure:

Workspaces are a brilliant way to break your data into smaller, more actionable pieces of information. However, they can be aggregated together so you can get a broader sense of your data.

Aggregate your workspaces to a single number and view them all on one page.

Combine multiple workspaces together to understand your Market Potential, Performance, and Opportunity.

Add modules from different workspaces into a single, automated, downloadable report.

Learn how to create workspaces here.