# Quickstart
Source: https://docs.usedaymark.io/getting-started/quickstart

Understand how Daymark works and follow a simple path to your first AI-powered insight.

## What to know before you start

<Columns>
  <Card title="Data source" icon="database">
    Prepare at least one data source: Google Sheets, a CSV file, or a PostgreSQL database. Daymark will pull data from these data sources.
  </Card>

  <Card title="Questions (optional)" icon="comments">
    You can start with a specific business question, or use Daymark’s starter questions to explore your data right away.
  </Card>
</Columns>

Follow the steps below inside your workspace to reach your first usable insight.

***

<img alt="Quickstart flow" />

## Quickstart: Create your first insight

### 1. Open Daymark and go to Explore

Log in to your Daymark workspace. The Explore page opens with a chatbox where you can ask questions and a visible **Add Data Source** button.

***

### 2. Connect your data

1. Click **Add Data Source** on the Explore page.
2. Choose where your data lives:
   * **Google Sheets:** Authenticate and select the sheet or tab you want to analyze.
   * **Upload CSV file:** Upload a CSV file directly.
   * **PostgreSQL:** Enter your database connection details.
   * **Demo sample data:** Use a sample dataset if you're just exploring Daymark.
3. Follow the prompts to complete the connection.

Once connected, Daymark indexes your data automatically so you can start asking questions immediately.

***

### 3. Ask a question in plain English

Type your question into the chat box as if you were talking to a teammate:

* “What were our total sales last month by region?”
* “Which product had the highest daily active users this quarter?”
* “Daily sign-ups vs conversions this month.”

You can also pick from the **suggested questions** in the chat. You don’t need to know table names or write SQL. Just describe what you want to understand.

***

### 4. Review and refine the visual answer

Daymark returns an answer as a **chart or table**, depending on your question:

* Bar charts for comparisons
* Line charts for trends over time
* Tables for detailed records

If the result isn’t exactly what you need, create a new query and ask the question again.

***

### 5. Add the insight to a dashboard

When you see an answer worth tracking:

1. Click the **⋮** menu on the top-right of the chart.
2. Select **Add to Dashboard**.
3. Choose to create a new dashboard or add it to an existing one.

***

### 6. Share and keep everyone aligned

Open the dashboard view and click **Share**. Enter your teammates’ email addresses to give them access.

They’ll receive a secure link and always see the latest version of the dashboard, powered directly by your data.

***

## What’s next

<Columns>
  <Card title="Connect more sources" icon="plug" href="/tutorials/connect-postgresql">
    Learn how to add additional databases, Sheets, or CSV workflows.
  </Card>

  <Card title="Build a dashboard" icon="chart-line" href="/tutorials/dashboards/building-dashboards">
    Create a shareable dashboard that keeps your key metrics and charts in one place.
  </Card>
</Columns>

With your first insight live, keep iterating: ask the next question, add it to the same dashboard, and build a Product, Revenue, or Ops view grounded in real data.


# Chart Types
Source: https://docs.usedaymark.io/glossary/chart-types

Understand how Daymark selects charts for your questions

## Overview

Daymark chooses a chart or table based on the type of question you ask.
Use the guide below to understand what each chart type is best suited for.

***

## Chart Selection Guide

| Chart Type      | Primary Goal          | Best Used For                                    |
| --------------- | --------------------- | ------------------------------------------------ |
| Pie             | Composition           | Showing parts of a whole                         |
| Scatter         | Correlation           | Finding relationships between two variables      |
| Funnel          | Sequence              | Identifying drop-offs in a process               |
| Bar (Multiple)  | Comparison            | Comparing different groups in the same category  |
| Bar (Stacked)   | Part-to-Whole + Total | Showing how categories contribute to a total sum |
| Line (Multiple) | Trends                | Tracking how several items change over time      |
| Table           | Detail                | Displaying high-precision, multi-variable data   |

***

## Tips for Better Charts

* Use time-based questions for line charts
* Use category comparisons for bar charts
* Use funnels for conversion steps
* Use tables when exact values matter

Daymark will still choose the chart automatically, but clearer questions yield more useful visuals.


# Glossary
Source: https://docs.usedaymark.io/glossary/glossary

Key terms used in Daymark documentation

## Data Source

A system or file that Daymark connects to in order to read and analyze data, such as a database, spreadsheet, or CSV file.

## Natural Language Query

A question asked in plain English that Daymark interprets and converts into a data query.

## Dashboard

A saved collection of charts that updates as the underlying data changes and can be shared with others.

## Visualization

A graphical or tabular representation of query results, including charts and tables.


# Introduction
Source: https://docs.usedaymark.io/index

Learn how Daymark helps teams explore data, ask better questions, and make confident decisions using AI.

## What is Daymark?

Daymark is an AI-powered data exploration platform that helps teams ask questions in plain language and instantly get clear, actionable insights from their data.

Instead of writing SQL, building dashboards from scratch, or waiting on analysts, Daymark lets you explore your data conversationally — turning everyday business questions into visual answers.

Daymark is built for speed, clarity, and decision-making.

***

## Who is Daymark for?

Daymark is designed for teams that work with data but don’t want to wrestle with it.

* **Product Managers** exploring usage, retention, and feature impact
* **Founders & Leaders** tracking growth, revenue, and performance
* **Analysts** accelerating exploration and reducing repetitive queries
* **GTM & Ops teams** answering questions without engineering support

If you can ask the question, Daymark helps you find the answer.

***

## How Daymark works

At a high level, Daymark helps you move from **question → insight** in minutes:

1. Connect your data sources (databases, spreadsheets, or CSVs)
2. Ask questions in natural language
3. Daymark interprets your intent and queries your data
4. Results are returned as tables, charts, or summaries
5. Save, share, and build dashboards from your insights

You stay focused on **what to learn**, not **how to query**.

***

## Get started in minutes

The fastest way to experience Daymark is to follow the Quickstart.

<Card title="Quickstart" icon="rocket" href="getting-started/quickstart">
  Connect your data, ask your first question, and explore your first dashboard.
</Card>

***

## What you’ll find in the documentation

This documentation is organized to help you succeed quickly and then go deeper when needed.

<Columns>
  <Card title="Getting Started" icon="play" href="/getting-started/quickstart">
    Set up Daymark, connect your first data source, and get your first insight.
  </Card>

  <Card title="Tutorials & Guides" icon="book" href="/tutorials/connect-postgresql">
    Step-by-step guides for connecting data, building dashboards, and best practices.
  </Card>

  <Card title="Glossary" icon="list" href="/glossary/glossary">
    Definitions of key terms used throughout Daymark and this documentation.
  </Card>
</Columns>

***

When you’re ready, start with the Quickstart and explore from there.


# Connect Google Analytics
Source: https://docs.usedaymark.io/tutorials/connect-google-analytics

Connect a Google Analytics property to Daymark with step-by-step guidance

## Overview

Connect **Google Analytics** to Daymark to analyze website traffic, user behavior, and conversion performance. This connection lets you:

* Track users, sessions, and page views over time
* Analyze traffic sources, landing pages, and user locations
* Ask natural language questions about your analytics data

You will sign in with Google, select a Google Analytics account and property, and choose how much historical data to sync.

***

## Connect Google Analytics in Daymark

### Open the Explore page

From your Daymark workspace, go to **Explore** to start connecting a new data source.

<img alt="Explore page with Add data source button" />

***

### Open Data Connectors

Click **Add data source** to open the list of available connectors. Select **Google Analytics** from the list.

<img alt="Data connectors list showing Google Analytics" />

***

### Sign in with Google

Click **Connect with Google** and complete the Google sign-in flow.

<Note>
  Daymark uses read-only access to retrieve Google Analytics data that the user is authorized to view and does not create, edit, or delete any Analytics resources.
</Note>

<img alt="Google sign-in screen" />

During this step, allow Daymark access to your Google Analytics data. These permissions are required to read property metrics and dimensions.

***

### Select Account, Property, and Settings

Complete the connector form:

* **Select Google account** that owns or has access to Analytics
* **Choose an Analytics property** you want to connect
* **Select the date range** for data sync
  Examples: last 30 days, last 90 days, last 12 months, or all available data

Click **Continue** once the selections are complete.

<img alt="Account, property, and date range selection screen" />

***

### Import Data

Daymark will start syncing data from Google Analytics. Once complete, your data will be ready for analysis in Explore.

<img alt="Data import in progress" />

***

## Connection Complete

After the sync finishes, ask your questions on the Explore page in plain English and turn answers into tables, charts, or dashboards. For example:

* “How many users visited the site last month?”
* “Which pages have the highest bounce rate?”
* “Compare organic vs paid traffic over time”

***


# Connect Google Search Console
Source: https://docs.usedaymark.io/tutorials/connect-google-search-console

Connect a Google Search Console to Daymark with step-by-step visuals

## Overview

Connect Google Search Console to uncover which search queries drive traffic, identify top-performing landing pages, track trends over time, and analyze performance.

You can use this connection to:

* Understand which queries bring visitors to your site
* See top landing pages and performance over time
* Break down results by country, device, and page

You will authenticate with Google, choose the site property you want to analyze, and set the earliest date you want to sync.

***

## Connect Google Search Console in Daymark

### Open the Explore page

From your Daymark workspace, open **Explore** to start the connection flow.

<img alt="Explore page with Add data source button" />

### Open Data Connectors

Click **Add data source** to open the connector list, then choose **Google Search Console**.

<img alt="Data connectors modal showing Google Search Console option" />

### Connect your Google account

Select **Connect with Google →** and complete the Google sign-in flow.

<Note>
  Daymark only reads data the user has permission to access in Google Search Console and does not modify or write back to the data.
</Note>

<img alt="Opened the Google Search Console Step 1" />

### Choose your property and date range

Use the connector form to finish the setup:

* **Select the Search Console property** you want to analyze (e.g., [https://example.com](https://example.com))
* **Choose the date range** Daymark should pull data for (last 30 days, last 90 days, last 12 months, or all time)

After confirming your selections, click **Continue**.

<img alt="Select properties and timeline Step 2" />

### Import Data

Daymark will sync the selected Search Console data and prepare it for querying. When the sync completes, you can start asking questions.

<img alt="Data Import Step 4" />

***

## Connection Complete

Once the sync completes successfully, ask your questions on the Explore page to see trends, patterns, and insights from your Search Console data.


# Connect HubSpot
Source: https://docs.usedaymark.io/tutorials/connect-hubspot

Connect HubSpot to Daymark with guided steps

## Overview

Daymark's HubSpot connector brings your HubSpot CRM data into Daymark so you can analyze it alongside other sources—like your product database (PostgreSQL), Google Sheets, and CSVs. This empowers your team to answer cross-source questions, such as connecting product usage to acquisition sources, revenue to acquisition sources, or support outcomes to customer cohorts.

Ask questions in plain English and Daymark automatically returns the right output (charts, tables, and summaries). Save answers into dashboards that can be updated and shared as a single source of truth across marketing, sales, success, and product teams.

Daymark respects HubSpot permissions—users only see data they're authorized to access. The connector is **read-only** for HubSpot and operates within HubSpot API usage limits and guidelines.

Daymark uses synced HubSpot data to power analytics, dashboards, and cross-source questions when you connect additional sources like PostgreSQL, Google Sheets, or CSVs. Daymark does **not** write data back to HubSpot.

***

## Install the app

### Open the Explore Page

From your Daymark workspace, go to **Explore** to start the connection.

<img alt="Explore page with Add data source button" />

### Choose HubSpot

Click **Add data source** and select **HubSpot** from the connector list.

<img alt="Data connectors modal with HubSpot selected" />

### Connect HubSpot account

Once you select HubSpot, a connection modal will appear. Follow these steps to authorize Daymark to access your HubSpot data:

1. Click **Continue to HubSpot**. This will open the HubSpot login and authorization page in a new tab.
   <img alt="HubSpot login and authorization page" />
2. Select the HubSpot account you want to connect.

<img alt="HubSpot account selection" />

3. Review the requested scopes on this screen. Daymark requests access to read contacts, companies, deals, and tickets.
4. Click **Connect app**.

After authorization, you will be automatically redirected back to Daymark to finish selecting your data.

### Select Tables and Fields

Choose the tables (e.g., Contacts, Companies, Deals, Tickets) and columns you want to include:

* Use **Select all** to include every field
* Or choose only the fields relevant to your analysis

Click **Done** to finish.

<img alt="Field selection during HubSpot import" />

### Import Data

Daymark validates the connection and starts importing your CRM data. Once the import is complete successfully, you can start analyzing the data in Daymark.

<img alt="Importing data from HubSpot" />

***

## Connection Complete

Once the import completes successfully, ask your questions on the Explore page to see trends, patterns, and insights from your HubSpot data in Daymark.

***

## Use the app

Once connected, you can immediately start asking questions about your HubSpot data in plain English. Daymark will analyze your contacts, companies, deals, and tickets to provide charts, tables, and summaries.

For example, ask questions like:

* "Show me all deals closed this quarter by sales rep"
* "What's the conversion rate from contact to customer by source?"
* "List all open support tickets by priority"

You can also combine HubSpot data with other connected sources for cross-source analysis:

* "Show me product usage by customer segment" (combining HubSpot + PostgreSQL)
* "What's the revenue by marketing campaign?" (combining HubSpot + Google Sheets)

***

## Uninstall the app

To uninstall the Daymark connector from your HubSpot account, follow the instructions in the [HubSpot Knowledge Base article on uninstalling integrations](https://knowledge.hubspot.com/integrations/how-do-i-uninstall-an-integration).


# Connect PostgreSQL
Source: https://docs.usedaymark.io/tutorials/connect-postgresql

Connect a PostgreSQL database to Daymark with guided steps

## Overview

This guide expands the PostgreSQL connection flow with visuals.
Use it when connecting a new database for the first time.

***

## Connect a PostgreSQL to Daymark

### Open the Explore Page

From your Daymark workspace, go to **Explore** to start the connection.

<img alt="Explore page with Add data source button" />

### Choose PostgreSQL

Click **Add data source** and select **PostgreSQL** from the connector list.

<img alt="Data connectors modal with PostgreSQL selected" />

### Enter Connection Details

You can use either a connection string or manual fields.

#### Option 1: Connection string

Paste your PostgreSQL connection string into the **Connection String** field.

#### Option 2: Manual fields

Fill in the form with your database details:

* **Host**
* **Port** (default `5432`)
* **Database name**
* **Username**
* **Password**

Click **Connect Database**.

<img alt="PostgreSQL connection form" />

### Select Tables and Fields

Choose the tables and columns you want to include:

* Use **Select all** to include every field
* Or choose only the fields relevant to your analysis

Click **Done** to finish.

<img alt="Field selection during PostgreSQL import" />

### Connect and Import

Daymark validates the credentials and starts importing. Once the import is complete successfully, you can start analyzing the data in Daymark.

<img alt="Importing data from PostgreSQL" />

***

## Connection Complete

Once the import completes successfully, ask your questions on the Explore page to see trends, patterns, and insights from your data in Daymark.


# Connect Sheet
Source: https://docs.usedaymark.io/tutorials/connect-sheet

Connect a Google Sheet to Daymark with step-by-step visuals

## Overview

This guide walks through connecting a Google Sheet to Daymark using the Explore flow.
It expands on the Google Sheets setup with step-by-step visuals and field selection tips.

***

## Connect a Google Sheet to Daymark

### Open the Explore Page

From your Daymark workspace, open **Explore** to start the connection flow.

<img alt="Explore page with Add data source button" />

### Open Data Connectors

Click **Add data source** to open the list of available connectors.

<img alt="Data connectors modal showing Google Sheets option" />

### Share the Sheet with Daymark

In Google Sheets, click **Share** and add the Daymark service account as a viewer:

`connector@daymark-473507.iam.gserviceaccount.com`

<img alt="Share instructions and Daymark service account email" />

### Paste the Sheet Link

Back in Daymark:

1. Paste the Google Sheet URL
2. Optionally enter a specific tab name
3. Click **Upload**

<img alt="Connect Google Sheets modal with link and tab fields" />

### Select Fields for Insights

Choose the columns you want Daymark to use:

* Select **All** to include every column
* Or pick only the fields relevant to your analysis

Click **Done** to import the data.

<img alt="Field selection for Google Sheets import" />

### Importing Data

Daymark prepares the sheet data for analysis. Once the import is complete successfully, you can start analyzing the data in Daymark.

<img alt="Importing data from Google Sheets" />

***

## Connection Complete

Once your data is imported, ask your questions on the Explore page to see trends, patterns, and insights from your sheet data in Daymark.


# Connect Shopify
Source: https://docs.usedaymark.io/tutorials/connect-shopify

Connect Shopify to Daymark with guided setup steps

## Overview

Daymark's Shopify connector lets you bring your Shopify store data into Daymark for analysis, dashboards, and cross-source reporting.

This guide walks through:

* Creating an app in Shopify Dev Dashboard
* Configuring required API scopes
* Entering your Shopify credentials in Daymark
* Completing OAuth and importing data

***

## Prerequisite: Create a Shopify app in Dev Dashboard

Before starting the integration in Daymark, create and configure your app in the Shopify Dev Dashboard.

### Step 1: Create the app

1. Open the [Shopify Dev Dashboard](https://dev.shopify.com/dashboard/).
2. In the left navigation, select **Apps**.
3. Click **Create app**.
4. Select **Start from Dev Dashboard**.
5. Name your app (for example, **Daymark**) and click **Create**.

### Step 2: Configure access and required scopes

1. Open the app's **Versions** tab.
2. In **Access > Scopes**, add the required scopes below.
3. If Shopify shows that some scopes require permission, click **Request access** from the same screen.
4. In **API access requests**, open **Protected customer data access** and click **Request access**.
5. In **Select your data use and reasons**, choose **App functionality**.
6. In **Protected customer fields**, select **Name**, **Email**, **Phone**, and **Address**, and set the reason to **App functionality** for each field.
7. Save your access request details.

Use this exact scopes list:

```text theme={null}
read_assigned_fulfillment_orders,read_audit_events,read_customer_events,read_checkouts,read_customers,read_fulfillments,read_gift_card_transactions,read_inventory,read_inventory_shipments,read_inventory_shipments_received_items,read_inventory_transfers,read_locations,read_marketing_events,read_merchant_managed_fulfillment_orders,read_orders,read_products,read_shipping,read_store_credit_account_transactions,read_third_party_fulfillment_orders,customer_read_customers,customer_read_orders,customer_read_store_credit_account_transactions,unauthenticated_read_customers
```

### Step 3: Set app URLs and release the version

1. Return to the app **Versions** tab.
2. Set **App URL** to:

```text theme={null}
https://usedaymark.io
```

3. Add **Redirect URL** as:

```text theme={null}
https://app.usedaymark.io/shopify/callback
```

4. Select the **Webhooks API version** (typically the newest version).
5. Click **Release**.

### Step 4: Get credentials

1. Open the app's **Settings** in Dev Dashboard.
2. Copy **Client ID** and **Client secret**.

<Note>
  Keep your Client ID and Client secret private and store them securely.
</Note>

***

## Connect Shopify in Daymark

### Open the Explore Page

From your Daymark workspace, go to **Explore** to start the connection.

<img alt="Explore page with Add data source button" />

### Choose Shopify

Click **Add data source** and select **Shopify** from the connector list.

<img alt="Data connectors modal showing Shopify option" />

## Setup

In the Shopify connector screen in Daymark, you will provide:

* **Shopify store**: your store subdomain (for example, `your-store`) or full URL (for example, `https://your-store.myshopify.com`)
* **Client ID**: from your Shopify custom app API credentials
* **Secret Key**: from the same Shopify custom app API credentials page

<img alt="Shopify connector form" />

### Connect and authorize in Daymark

1. Return to Daymark's Shopify connector form.
2. Enter **Shopify store**, **Client ID**, and **Secret Key**.
3. Click **Continue to Shopify**.
4. Complete Shopify authorization and return to Daymark.

### Import Data

Daymark validates the connection and starts importing your Shopify data. Once the import is complete successfully, you can start analyzing the data in Daymark.

<img alt="Data Import Step 4" />

***

## Connection Complete

Once the import completes successfully, ask your questions on the Explore page to see trends, patterns, and insights from your Shopify data in Daymark.

***

## Use the app

After connecting Shopify, you can ask questions such as:

* "What are my top products by revenue this quarter?"
* "Show daily orders and average order value for the last 90 days"
* "Which customers placed repeat orders this month?"

You can also combine Shopify data with other connected sources for cross-source analysis in Daymark.


# Building Dashboards
Source: https://docs.usedaymark.io/tutorials/dashboards/building-dashboards

Create dashboards from questions and charts

## Overview

Dashboards in Daymark are built from the answers you generate on the Explore page.
You ask a question, review the chart or table, and add the best insights to a dashboard.

***

## Before You Start

Make sure you have:

* Reviewed the [Quickstart](/getting-started/quickstart) if you're new to Daymark
* A connected data source
* A set of questions you want the dashboard to answer

***

## Build a Dashboard

<Steps>
  <Step title="Ask a focused question">
    Start with questions that match the decisions you want to support. For example, trends, comparisons, or funnel drop-offs.
  </Step>

  <Step title="Review the visual answer">
    Daymark returns a chart or table based on your question. Confirm it matches the insight you want to track.
  </Step>

  <Step title="Add the chart to a dashboard">
    Open the chart menu and add the result to a new or existing dashboard.
  </Step>

  <Step title="Repeat for key insights">
    Continue asking questions and add only the charts that matter to the dashboard goal.
  </Step>
</Steps>

***

## Guidance on Selecting Questions

A dashboard is only as useful as the questions behind it.
Choose questions that:

* Tie directly to goals or KPIs
* Can be acted on by your team
* Explain trends, changes, or performance gaps

***

## Next Steps

After building the dashboard, share it with your team and keep it updated as data changes.


# Sharing Dashboards
Source: https://docs.usedaymark.io/tutorials/dashboards/sharing-dashboards

Share dashboards securely with your team

## Overview

Once your dashboard is ready, you can share it with teammates so everyone sees the same data-backed view.
Sharing uses a secure, password-protected link.

***

## Share with Your Team

<Steps>
  <Step title="Open the dashboard">
    Navigate to the dashboard you want to share.

    <img alt="Dashboards list view" />
  </Step>

  <Step title="Click Share">
    On the dashboard page, click **Share** in the top-left corner to start sharing.

    <img alt="Share button in dashboard" />
  </Step>

  <Step title="Add teammate access">
    Enter your teammate's email in the popup to grant access.

    <img alt="Share popup with email field" />
  </Step>

  <Step title="Send the share link">
    Once Click on **Share**. Daymark automatically sends a password-protected link. Recipients enter the access key to view the dashboard.
  </Step>
</Steps>

***

## What Teammates See

* The same dashboard layout and charts
* Up-to-date results powered by the connected data source

***

## Security Notes

* Links are password-protected
* Access is granted only to the teammates you invite


# Connect Google Ads
Source: https://docs.usedaymark.io/tutorials/integrations/google-ads

Connect a Google Ads account to Daymark with step-by-step visuals

## Overview

Connect **Google Ads** to Daymark to analyze your campaign performance, understand spend trends, track conversions, and measure ROI across channels. This connection enables you to:

* View clicks, impressions, cost, and conversion metrics over time
* Break down performance by campaign, ad group, keyword, country, and device
* Ask natural language questions about your Google Ads data in Explore

You will authenticate with Google, choose the Ads account and campaigns you want to analyze, and set the earliest date you want to sync.

***

## Connect Google Ads in Daymark

### Open the Explore page

From your Daymark workspace, open **Explore** to begin the connection flow.

## <img alt="Explore page with Add data source button" />

### Open Data Connectors

Click **Add data source** to open the connector list, then choose **Google Ads** from the options.

<img alt="Data connectors modal showing Google Ads option" />

***

### Connect your Google account

Select **Continue to Google** and complete the Google sign-in flow.

<Note>
  Daymark only reads data that the user has permission to access in Google Ads and does not modify, create, or manage ads in the account.
</Note>

<img alt="Google Ads connector sign-in step" />

You may be prompted to grant Daymark permission to view your Google Ads account data. Approve all requested scopes so Daymark can fetch campaign, ad group, and performance data.

***

### Choose your Account & Settings

Use the connector form to finish the setup:

* **Select the Google Ads account** that has access to your Google Ads\
  Select the account ID shown next to your Google Ads account name (as highlighted below).\\
  <img alt="Google Ads account name with customer ID shown in the header" />
* **Manager Account ID (optional)** Use this only if you signed in with a manager (MCC) account. Enter the manager account's customer ID
* **Set your date range** — common choices are last 30 days, last 90 days, last 12 months, or all time

After confirming your selections, click **Continue**.

<img alt="Select Google Ads account and timeline step" />

***

### Import Data

Daymark will begin syncing your Google Ads data and prepare it for querying. When the sync completes, you can start asking questions.

<img alt="Data import step" />

***

## Connection Complete

Once the sync completes successfully, ask your questions on the Explore page to see trends, patterns, and insights. For example:

* “Which campaigns drove the most conversions last quarter?”
* “Show cost per conversion for all campaigns this month”
* “Compare mobile vs desktop click-through rates”

***


# NeonDB
Source: https://docs.usedaymark.io/tutorials/integrations/neondb

Connect NeonDB to Daymark using a connection string

## Overview

Daymark connects to NeonDB through a PostgreSQL connection string.
This guide shows where to find it in Neon and how to use it in Daymark.

***

## Get the Neon Connection String

<Steps>
  <Step title="Open your Neon project">
    In Neon, open the project you want to connect.
  </Step>

  <Step title="Open the Connect panel">
    Click **Connect** to open the connection options.
  </Step>

  <Step title="Show the password">
    In the connection string section, enable **Show password** so the full string is visible.
  </Step>

  <Step title="Copy the connection string">
    Copy the full connection string.
  </Step>
</Steps>

***

## Connect NeonDB in Daymark

### Open the Explore Page

After login, open the Explore page and click **Add Data Source**.

<img alt="Explore page with Add data source button" />

### Choose PostgreSQL

Choose **PostgreSQL** as the data source.

<img alt="Data connectors modal with PostgreSQL selected" />

### Enter Connection Details

Paste the Neon connection string into the **Connection string** field.

<img alt="PostgreSQL connection form" />

### Select Tables and Fields

Choose the tables and columns you want to include.

<img alt="Field selection during PostgreSQL import" />

### Connect and Import

Daymark shows the import progress as it pulls in your data. Once the import is complete successfully, you can start analyzing the data in Daymark.

<img alt="Importing data from PostgreSQL" />

***

## Connection Complete

Once the import completes successfully, ask your questions on the Explore page to see trends, patterns, and insights from your data in Daymark.


# Supabase
Source: https://docs.usedaymark.io/tutorials/integrations/supabase

Connect Supabase to Daymark using a connection string

## Overview

Daymark connects to Supabase through its PostgreSQL connection string.
This guide shows how to retrieve the Supabase connection string and use it in Daymark.

***

## Get the Supabase Connection String

<Steps>
  <Step title="Open your Supabase project">
    In Supabase, open the project you want to connect.
  </Step>

  <Step title="Open the Connect panel">
    Click **Connect** in the top bar to open the connection options.
  </Step>

  <Step title="Select Transaction pooler">
    In the **Connection string** tab, set **Method** to **Transaction pooler**.

    <img alt="Supabase connection string with Transaction pooler selected" />
  </Step>

  <Step title="Copy the connection string">
    Copy the connection string shown in the panel.
  </Step>
</Steps>

<Note>
  The connection string includes the database password you set when you created the Supabase project.
</Note>

***

## Connect Supabase in Daymark

### Open the Explore Page

After login, open the Explore page and click **Add Data Source**.

<img alt="Explore page with Add data source button" />

### Choose PostgreSQL

Choose **PostgreSQL** as the data source.

<img alt="Data connectors modal with PostgreSQL selected" />

### Enter Connection Details

Paste the Supabase connection string into the **Connection string** field.

<img alt="PostgreSQL connection form" />

### Select Tables and Fields

Choose the tables and columns you want to include.

<img alt="Field selection during PostgreSQL import" />

### Connect and Import

Daymark shows the import progress as it pulls in your data. Once the import is complete successfully, you can start analyzing the data in Daymark.

<img alt="Importing data from PostgreSQL" />

***

## Connection Complete

Once the import completes successfully, ask your questions on the Explore page to see trends, patterns, and insights from your data in Daymark.


# Question Best Practices
Source: https://docs.usedaymark.io/tutorials/question-best-practices

Write clear questions to get precise insights

## Overview

Daymark works best when questions are specific and tied to a decision.
This guide shows how to frame questions so the results are accurate and easy to act on.

***

## Start with the Decision

Before asking a question, clarify the decision it supports:

* What action will you take if the result changes?
* Who needs the answer and when?
* What metric defines success?

***

## Use Clear, Concrete Language

Well-scoped questions reduce ambiguity and improve chart selection.
Include the key elements below when relevant:

* **Metric** (revenue, signups, churn rate)
* **Timeframe** (last 30 days, Q2, month over month)
* **Segment** (plan type, region, channel)
* **Comparison** (this month vs last month, A vs B)

Example:

* Instead of: "How are we doing?"
* Ask: "What is the month-over-month revenue change for Enterprise customers in Q2?"

***

## Align Question Type to the Output

Different question types produce different visuals:

* **Trends** → line charts
* **Comparisons** → bar charts
* **Composition** → stacked bars or pie charts
* **Funnel steps** → funnel charts
* **Exact values** → tables

If you want a specific view, ask in a way that implies it.

***

## Ask in Layers

Start simple, then refine:

1. Ask a broad question to establish the baseline
2. Narrow by time, segment, or category
3. Compare to a previous period or cohort

Example:

* "What is churn rate this quarter?"
* "Break churn rate by plan type."
* "Compare churn by plan type vs last quarter."

***

## Use Column Names When Possible

When you can, reference the actual column names from your data source.
This helps Daymark match your question to the right fields.

***

## Common Mistakes to Avoid

* Asking multiple unrelated questions at once
* Omitting timeframes for trend questions
* Using vague terms like "better" or "worse" without a metric

***

## Next Steps

If you are new to Daymark, start with suggested questions in the chat and refine from there.


# Slack Integration
Source: https://docs.usedaymark.io/tutorials/slack-integration

Connect Slack to Daymark and ask questions from Slack threads

## Overview

Connect **Slack** to Daymark so your team can ask questions directly from Slack and receive a Daymark report overview in the same thread.

This integration lets you:

* Mention `@Daymark` in Slack channels to ask questions
* Get responses directly in the thread where the question was asked
* Daymark sends the link of the report so anyone on your team can view detailed insights
* Use the app in both public and private channels after inviting it

***

## Prerequisites

Before installing Daymark in Slack, make sure you have:

* An active **Daymark account**
* Access to the target **Slack workspace**.
* At least one **data connector** already connected in Daymark so the Slack app can access data

### Access Control

All threads created through the Daymark Slack integration are visible to your team in Slack.

***

## Connect Slack in Daymark

### Step 1: Open the Slack integrations page

After logging in to Daymark:

* Open **Team** from the sidebar
* Go to **Integrations**
* In the integrations list, find **Slack**
* Click **Connect** to start the Slack OAuth flow

<img alt="Slack integration page with Connect button" />

### Step 2: Authorize Daymark

You will be redirected to Slack to authorize the integration:

1. Select your Slack workspace
2. Review the permissions Daymark is requesting
3. Click **Allow** to grant access

Daymark can read recent conversations in channels where it has been invited. When someone in the channel mentions `@Daymark` and asks a data question, Daymark will reply in the same thread with the answer.

Once authorization is complete, the Slack integration status in Daymark will appear as **Connected**.

<img alt="Slack integration connected status in Daymark" />

***

## Use the app in Slack

After the integration shows as connected in Daymark, open your Slack workspace to start using it.

### Step 1: Invite the app to a channel

In any Slack channel where you want to use Daymark, invite the app first:

```text theme={null}
/invite @Daymark
```

### Step 2: Ask a question

In a Slack channel where the app is present, mention `@Daymark` and ask your question:

```text theme={null}
@Daymark What is the monthly revenue trend?
```

Daymark will reply in the same Slack thread with a report link and overview based on your request.

Example questions:

* "What is the monthly revenue trend?"
* "Which products grew the fastest this quarter?"
* "Show pipeline created this month by owner"

While Daymark processes the request:

* `👀` appears while the request is running
* `✅` appears when the response succeeds
* `⚠️` appears if the request fails

Once Daymark is connected and invited to a channel, your team can ask data questions and get answers directly in Slack.


# Upload CSV
Source: https://docs.usedaymark.io/tutorials/upload-csv

Upload a CSV file to Daymark with step-by-step visuals

## Overview

This guide expands the CSV upload flow with step-by-step visuals.
Use it to bring a CSV file into Daymark and select the fields you want to analyze.

***

## Upload a CSV to Daymark

### Open the Explore Page

From your Daymark workspace, go to **Explore** to start the upload.

<img alt="Explore page with Add data source button" />

### Choose CSV Upload

Click **Add data source** and select **Upload CSV File** from the connector list.

<img alt="Data connectors modal with Upload CSV File selected" />

### Select the CSV File

Drag and drop your file or click to browse.

Make sure the first row contains column names so Daymark can label the data correctly.

<img alt="CSV upload dropzone" />

### Upload the File

Click **Upload CSV** to start processing.

<img alt="Upload CSV button on the upload modal" />

### Select Fields for Insights

Choose the columns you want to include:

* Select **All** to include every column
* Or select only the fields relevant to your analysis

Click **Done** to finish.

<img alt="Field selection after CSV import" />

### Import Data

Daymark imports the file and prepares the data for analysis. Once the import is complete successfully, you can start analyzing the data in Daymark.

<img alt="CSV import progress indicator" />

***

## Connection Complete

Once your data is imported, Ask your questions on the Explore page and explore trends, patterns, and insights from your CSV data in Daymark.