---
title: ASK BOSCO® Analysts
description: Learn how ASK BOSCO® Analysts let you build purpose-built AI agents with scoped data, custom instructions and connectors for AI marketing reporting
---
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# ASK BOSCO® Analysts
## You can now create purpose-built AI agents within AI Analyst, each configured with its own data, instructions, and connectors for a specific team, client, or use case, rather than relying on one general-purpose AI Analyst experience for everyone.
#### What it does
ASK BOSCO® Analysts are focused AI agents you can create and configure for a specific team, use case, or client. Each Analyst is a tailored version of AI Analyst: configured once with a defined scope, so users land in a pre-configured experience the moment they start chatting.
Analysts aren't separate AI bots. They configure the context within the AI Analyst experience itself: which data models the agent can see, custom instructions that shape its behaviour, the connectors it can use, and who the workspace is shared with.
Rather than one generic AI Analyst experience across the whole organisation, Analysts let AI Analyst be shaped around how different users actually work, so questions get answered with the right data, the right definitions, and the right level of context.
---
#### Why it's useful
A single, ungoverned AI Analyst experience across a whole organisation runs into a few problems:
- **Generic answers.** When AI Analyst has access to all data across all teams, responses can lack the specificity and terminology different business functions actually need.
- **Inconsistent definitions.** Without scoped context, there's no way to enforce consistent business terms or governed metric definitions by team or domain.
- **Irrelevant data surfacing.** AI Analyst may draw on data sources that aren't relevant to a particular team or client. An Analyst scoped to specific sources keeps responses grounded only in the data that matters to that audience, so it won't surface insights from channels or datasets they don't use or care about.
Analysts solve this by letting anyone create a purpose-built agent, pre-configured with the right data, context, and instructions for a specific team or use case.
---
#### How to use it
- Open ASK BOSCO® AI Analyst.
- You'll see a new **Analysts** section in the sidebar.
- To create an Analyst: click **View all**, then **Create new**. Name the Analyst, write a description, add instructions, and select up to five data models.
- Chats default to the standard ASK BOSCO® AI Analyst experience unless you select an Analyst.
- Clicking on an Analyst starts a new chat scoped to that Analyst.
---
#### What makes it useful
**An identifiable name and icon.** Each Analyst has its own name and icon, so it's easy to tell them apart at a glance.
**Custom instructions.** Each Analyst can be given detailed instructions (up to 5,000 characters) defining its tone, how it should answer questions, which definitions to apply, what to exclude, and how to handle ambiguity. These override the default AI Analyst behaviour, so every user of that Analyst gets consistent, governed responses.
**AI-assisted setup.** You can use AI Analyst itself to help write an Analyst's instructions. Describe the intended use case, audience, terminology, or desired behaviour in natural language, and AI Analyst will generate tailored instructions you can review and refine before saving.
**Scoped data access.** When you create an Analyst, you select up to five data models for it to use. Anyone using that Analyst can only query those models; they don't need to choose a data source themselves, and can't accidentally query data outside the defined scope.
**Connector control.** You can specify which connectors an Analyst is allowed to use, or block ones that aren't relevant to the use case, giving you extra control over what external tools and data sources it can access during a conversation.
**Sharing and access management.** Analysts can be shared with individual users or groups within your org. Anyone who receives a shared Analyst can chat with it or copy it, and is automatically granted view access to the data models it uses. Only the creator, an admin, or someone with the relevant privilege can edit an Analyst; sharing on its own doesn't grant edit access.
**Easy to create and manage.** Analysts are created directly within AI Analyst via a simple setup page. They can be edited as use cases evolve, copied to create variations, and deleted when no longer needed. The Analyst library is browsable and searchable, with separate views for Analysts you've created and those shared with you.
---
#### Who this helps
**Paid media teams** can use an Analyst scoped to paid media data (Google Ads, Meta Ads), letting channel managers ask performance questions using familiar terms like ROAS, CPM, and CTR, with answers grounded in the right campaigns and accounts. Instructions can define exactly what "at risk" or "underperforming" means for that team, removing ambiguity from AI-generated answers.
**SEO and organic search teams** can use an Analyst configured with organic search data (Google Search Console, GA4) to answer questions about rankings, impressions, and traffic trends in context, without needing to select the right data model themselves. Particularly useful for agencies managing multiple clients, where scope and context need to be clearly defined per account.
**Ecommerce and trading teams** can use a trading-focused Analyst scoped to Shopify and product data, letting merchants and trading managers interrogate sales performance, product trends, and basket behaviour without navigating the full data estate. Instructions can enforce ecommerce-specific definitions and exclude internal or test data from answers.
**Agency account teams** can create client-specific Analysts, each configured with that client's KPIs and terminology, helping account managers surface performance insights and answer client questions quickly and consistently.
---
#### Good to know
- **Instructions are capped at 5,000 characters** per Analyst.
- **Each Analyst can reference up to five data models.**
- **Conversations within an Analyst can't currently be shared** with other users.
- **Instructions aren't visible to users.** Anyone using an Analyst can't see the instructions it was built with, though they can ask the Analyst to describe its scope.
- **Inherits standard AI Analyst constraints.** Data sources still need AI functionality enabled, and answer quality depends on the underlying data model, the same as with standard AI Analyst.
This article was created by Grace. If you have any questions or need a hand, feel free to reach out to us at [**team@askbosco.io**](mailto:team@askbosco.io)[mailto:team@askbosco.io](mailto:team@askbosco.io)
September 2026
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