Conversational Analytics in Looker

Conversational Analytics is a chat with your data feature powered by Gemini for Google Cloud. Conversational Analytics empowers users with no expertise in business intelligence to ask data-related questions in regular, natural (conversational) language, and go beyond static dashboards. Conversational Analytics is available in Looker (Google Cloud core) and Looker (original) instances.

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.

For setup requirements, known limitations, and a list of key features, see the Conversational Analytics landing page.

Supported data sources

The following data sources are supported for using Conversational Analytics with Looker Studio in Looker:

You can access Conversational Analytics in the following ways:

Start a conversation

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. To create a new conversation, follow these steps:

  1. Navigate to Conversational Analytics.
  2. Click + Create conversation.

  3. Select the source of your conversation:

    • Explores: To start a conversation based on a Looker Explore, select the Explore panel. The project name is listed beside the Explore name.

    • Agents: Data agents are customized with context and instructions that are specific to your data. To start a conversation with an existing data agent, select Agents, and then select a data agent. To create a new data agent, select + Create agent.

  4. To start the conversation, enter your question and press return (Mac) or Enter (PC).

You can return to the conversation from the Recent section.

Ask questions

You can ask questions to get insights from your data. When you're beginning a new conversation, Conversational Analytics suggests some starting questions to ask.

Ask questions about a data source

Once you have created a conversation, you can ask questions about the data in the Ask a question field within the conversation.

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 may rephrase your question after you've written a query, and the rephrased question will be displayed in the conversation window following your original question. For example, Conversational Analytics might rephrase the question "What is the mean of user ages?" to "What is the average user age?"

Conversational Analytics will take previous questions and answers into account as you continue the conversation. You can take previous answers and build on them by further refining results or changing the visualization type.

For more guidance on creating questions, see Limitations on questions.

Manage queries within a conversation

When you converse with data, you can manage the conversation by stopping an active query response while it is running or by deleting the most recent question and its response.

Stop a query response

To stop running a query after you've sent a message, click Stop response. Conversational Analytics stops running the query and displays the following message: The query was cancelled.

Delete the most recent question

To delete the most recent question and its response, follow these steps:

  1. Hold your cursor over the most recent question, and then click Delete message.
  2. In the Permanently delete message? dialog, click Delete to permanently delete the question and its response.

Understand query results and calculations

When you ask questions about your data in Conversational Analytics, the response might include a visualization, a data table, or other details, depending on your specific query and the connected data.

In addition to this query response, Conversational Analytics provides the following options for understanding query results and calculations:

Determine how an answer was calculated

To see how Conversational Analytics arrived at an answer or created a visualization, click How was this calculated? within the query results.

When you click How was this calculated?, Conversational Analytics displays a Text section. The Text section provides a plain text explanation of the steps that were taken by Conversational Analytics to arrive at the given answer. This explanation includes the raw field names that were used, the calculations that were done, the filters that were applied, the sort order, and other details.

Get additional insights

When Conversational Analytics is able to provide additional data insights about a response, an Insights keyboard_arrow_down button will appear below the response. Click Insights keyboard_arrow_down to see additional information about your query. Insights only analyzes the data that was returned by your prompt and won't run additional queries to fetch additional data. Insights can be a useful source for ideas for follow-up questions to continue the conversation.

The following is an example of some insights that might be returned by the prompt "How many users are in each state?":

  • A general summary of high and low data volume areas. For example:
    • "California, Texas, and Ohio are key states for business operations based on the data provided."
    • "England and specific regions in China, namely Anhui and Guangdong, show significant business activity."
    • "Some states, including Mie, Akita, and Iwate, have minimal presence based on the data."
  • An assessment of the variability of the dataset. For example, "The data indicates varying operational scales across different locations."

Manage conversations

You can change the names of conversations, delete conversations, or restore them from the trash folder.

Name a conversation

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

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

Delete a conversation

To move a conversation to the trash, open the conversation and click Move to trash.

Restore or permanently delete a conversation

To restore or permanently delete a conversation from the trash, follow these steps:

  1. Within Conversational Analytics, select Trash in the left navigation panel to view the list of conversations that have been moved to the trash.
  2. In the Trash section, click the name of the conversation that you want to restore or permanently delete.
  3. In the Are you sure? dialog, select one of the following options:
    • Cancel: Cancels the action.
    • Restore: Restores the conversation. The conversation can be accessed from the Recent section of the left navigation menu within Conversational Analytics.
    • Delete forever: Permanently deletes the conversation.

Connect to data

You can connect to new Looker Explores within your instance to use with Conversational Analytics.

Best practices for 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.
  • Give each field a clear and concise name.
  • Give each field a clear description, including sample 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. Sample values are especially helpful for string fields.

Connect to Looker data

You start a conversation directly with a Looker Explore or with a data agent that is built with a Looker Explore.

Before you begin

To use a Looker Explore with Conversational Analytics, the Looker connector must be enabled for the Looker instance that you are connecting to within Conversational Analytics. To enable the Looker connector, your Looker instance must meet the prerequisites that are described in Connecting to Looker Studio.

Use a Looker Explore as a data source

Looker Explores appear in the list of available Explores on the Chat with your data page. To use a new Looker Explore as a data source in Conversational Analytics, follow these steps:

  1. In Conversational Analytics, on the Chat with your data page, select the Explores tab.
  2. Select an Explore from the list, or search for a specific Explore.
  3. Click Connect to start a conversation.

Converse with a Looker data source

Once you've connected to a Looker Explore, you can ask questions about your Looker data.

When you converse with your data, the collapsible Data panel shows the name of the Looker Explore that is being used by the conversation. The Data panel also provides the following options:

  • View fields: View the Explore in a new browser window by clicking View fields.
  • New conversation: Start a new conversation with the Looker Explore that the current conversation is using.

Open in a Looker Explore

To open the query results as an Explore, click Open in Explore within the query results.

Additional resources