Query your data in natural language with Gemini assistance

Conversational Analytics is an AI-powered data querying tool that helps you write questions in natural language, empowering those with no expertise in business intelligence to gain value from your data. To produce the most reliable answers possible, Conversational Analytics uses your LookML models to understand how it should query your data.

Learn how and when Gemini for Google Cloud uses your data. As an early-stage technology, Gemini for Google Cloud products can generate output that seems plausible but is factually incorrect. We recommend that you validate all output from Gemini for Google Cloud products before you use it. For more information, see Gemini for Google Cloud and responsible AI.

Before you begin

To use Conversational Analytics, you must meet the following requirements.

  1. You must be a user under a Looker Studio Pro subscription. Looker Studio Pro licenses are available at no cost to Looker users.
  2. An administrator must have enabled Gemini in Looker for Looker Studio.
  3. The dataset that you want to analyze must be in Google BigQuery, Google Sheets, a CSV file, a data extract, or Looker (which is a different product than Looker Studio).

Supported data sources

Before you can ask questions of your data, you must have data sources connected to Looker Studio. Conversational Analytics works with the Google BigQuery, Google Sheets, CSV, data extracts, and Looker data connectors.

Set up connections to these data sources by following the instructions in the following articles:

You can view the data sources that have already been added to your Looker Studio by navigating to the Data sources page in Looker Studio.

Limits of data sources

Be aware of these data source limitations:

  • Conversational Analytics doesn't support BigQuery's Flexible Column Names feature.
  • Conversational Analytics doesn't work well with data sources that have field editing in reports disabled because this setting prevents Conversational Analytics from creating calculated fields.
  • When the data source is Looker, Conversational Analytics cannot override the default value of an always_filter parameter or a conditionally_filter parameter.
  • When the data source is Looker, Conversational Analytics cannot set the value of a filter-only that is defined using the LookML parameter parameter.

Conversational Analytics can be accessed in the following ways:

  • Navigate directly to Conversational Analytics.
  • Choose Conversational Analytics from the navigation panel of Looker Studio.
  • Choose Conversation from the Create menu of Looker Studio if you are in your Sandbox workspace.

Manage conversations

Sets of questions that you ask about a dataset are organized by conversation. Splitting work into multiple conversations can be useful for organizing lines of inquiry. Previous conversations are listed in the schedule Recent panel of Conversational Analytics. Clicking on any existing conversation lets you return to the conversation and ask additional questions.

Create a new Conversation

To create a new Conversation, click the New button in the upper left of Conversational Analytics. Questions and results are saved for future viewing in the "Sandbox" location of the project that you choose.

The first required step for a Conversation is to choose which data source you want to investigate. To choose a data source, click an existing data source, or create a new one by choosing Connect to data.

If you're having trouble making a data source appear, validate that it's one of the supported data connector types.

Name a conversation

Conversational Analytics automatically generates a conversation's title that is based on your first question and response. To change the generated name, follow these steps:

  1. From the Recent panel, open the conversation.
  2. Click the title at the top of the page.
  3. Enter a new conversation name.
  4. To save your changes click elsewhere on the page, or press return (Mac) or Enter (PC).

The conversation name is changed to My Marketing Report.

Delete a Conversation

To delete a conversation, click the trash icon in the top right corner of the Conversation. You can find deleted Conversations in the Trash section in the left pane of Conversational Analytics, where they can be restored or permanently deleted. Select a Conversation in the Trash to restore or permanently delete it.

Conversations that remain in the Trash for more than 30 days are automatically deleted.

Search Conversations

You can search a Conversation by using the Search Conversational Analytics search bar at the top of the page.

Ask Questions

You can ask and edit your questions to get insights from your data.

Ask questions about a data source

Once you have created a Conversation, you can type questions about the data into the Ask a question field at the bottom of the screen. The questions don't need to be in a specific format or use a specific syntax. However, they do need to relate to the data source that you've selected. Conversational Analytics will take previous questions and answers into account as you continue the Conversation.

Conversational Analytics supports questions that can be answered by a single Looker Studio visualization, for example:

  • Metric trends over time
  • Breakdown or distribution of a metric by dimension
  • Unique values for one or more dimensions
  • Single metric values
  • The top dimension values by metric

Conversational Analytics doesn't yet support questions such as the following:

  • Percent change of a metric over time, including period-over-period analysis
  • Prediction and forecasting
  • Advanced statistical analysis, including correlation and anomaly detection

For more guidance on crafting questions, see Best Practices.

Suggested questions

If you're not certain where to begin, Conversational Analytics suggests starting questions at the bottom of a Conversation under What questions can I ask?. Click a suggested question to generate an answer.

Edit questions

You can modify your most recent question in a Conversation by clicking the pencil icon next to the prompt. The question can then be edited and updated. If you choose to update the question, the previous prompt and response is removed and replaced with the updated prompt.

Get additional insights

When Conversational Analytics is able to provide additional data insights about a response, an Insights button will appear below the response. Click it to see additional information about your query. The Insights feature only analyzes the data that was returned by your prompt and won't run additional queries to fetch additional data.

Determine how an answer was calculated

To see how Conversational Analytics arrived at an answer or created a visualization, select How was this calculated? below the response. This will provide an overview of the steps taken by Conversational Analytics, including the fields that were used, the calculations that  were done, the filters that were applied, and other details.

Best practices

Review the following best practices to help Conversational Analytics provide the most helpful answers.

Setting up a data source

Setting up a data source in the ideal manner can help Conversational Analytics provide the most helpful answers. Consider following these best practices when creating a data source:

  • Only include fields in the data source that should be used for analysis by end users. You can exclude other fields entirely, or hide them in the data source.
  • Give each field a clear and concise name. For Looker data sources, the field labels that are defined in Looker are automatically used by Looker Studio.
  • Give each field a clear description, including example values where relevant. These field descriptions are included in the prompt that is sent to Conversational Analytics, and they can be helpful for providing context. Example values are especially helpful for string fields.

Prompting

When writing questions for Conversational Analytics, consider following these best practices:

  • Use the exact field names that are included in the data source when possible. This will help Conversational Analytics disambiguate similarly named columns. You can view these field names by clicking View data source in the data sidebar.
  • To narrow down results by including or excluding specific data, state the field and the filter value directly when possible. For example, instead of asking for "German sales", ask for "sales where the country is Germany", or "sales where the region is DE".

Data agents

Data agents build on the power of Conversational Analytics to further refine the experience of users with no expertise in business intelligence to gain value from your data. With Data agents, you are able to customize the AI-powered data querying agent with context and instructions specific to your data.

For example, maybe you define a "loyal" customer as one who has made more than five purchases within a certain timeframe. Or, you want to save your users time, so all responses from your data agent should be summarized in 20 words or fewer. Also, you want numbers to be formatted to match company standards. These types of instructions and more can be used to build a data agent that knows how your users want to interact with your data. Visit the Data agents documentation page to learn more.

Provide feedback

You can provide feedback to Google about Conversational Analytics in either of the following ways:

  • Click the thumbs-up or thumbs-down icon under each response.
  • Click the Send Feedback button at the bottom of the left-hand pane.

If you're sharing negative feedback, you'll have the option to include additional details, including a copy of the Conversation that you were having. Please do not share sensitive information with Google such as passwords, payment information, or personal customer details.