How to Automate Weekly Data Reports with Make

Make is a no-code workflow automation platform with connections to over 2,000 apps. Once a scenario is active, it runs on whatever schedule you set and does not require you to open a browser, remember to send anything, or reformat numbers by hand. For teams that spend an hour each week assembling the same report from three different tabs, that is a meaningful change.

What You Need Before You Start

You need three things before building your first automated report.

A Make account. The free plan allows up to 1,000 operations per month and supports scenarios that run as frequently as every 15 minutes. For a weekly report that pulls a few rows of data, the free tier is more than sufficient. Make reported over 700,000 active users in early 2026, with scheduled reporting being one of the most common use cases.

At least one data source connected. The most common starting points for operations teams are Google Sheets, Airtable, HubSpot, Notion, or a standard PostgreSQL or MySQL database. Make connects to all of them through a graphical interface with no coding required.

A delivery destination. That is the Slack channel or email address where the report lands each week.

Step 1 — Create a New Scenario

Log in to Make at make.com, navigate to Scenarios in the left sidebar, and click Create a new scenario. You land on a blank canvas with a single empty module in the center.

Every Make scenario starts with a trigger module that tells Make when to run. Click the empty circle and search for "Schedule" in the app picker, then select the Schedule module.

Step 2 — Configure the Schedule Trigger

The Schedule trigger fires your scenario at any interval you choose. For a weekly report, set the interval to Weeks, choose the day, and set the time.

Make runs all schedule triggers in UTC. If your team is in UTC-5, set the trigger to 13:00 UTC to deliver the report at 8:00 AM Eastern. This is the single most common setup mistake. Set this carefully before activating.

Step 3 — Pull Data from Your First Source

Click the + button to the right of the Schedule module to add your first data module. Search for the app where your data lives.

For Google Sheets, select the Search Rows action. Connect your Google account when prompted, then point Make to the spreadsheet and the sheet tab you want to query. You can filter results by column value to limit rows to the current week.

For Airtable, use the Search Records action with a filter formula such as IS_AFTER({Created}, DATEADD(TODAY(), -7, 'days')) to return only records from the past seven days.

For HubSpot, use Search for Deals and filter by close date or last modified date to pull only the current week's activity.

Each module returns a structured bundle of data that downstream modules reference by variable name. No formulas or code are written at this stage.

Step 4 — Add Additional Data Sources

A real weekly report rarely comes from one place. You might want task counts from Airtable alongside revenue numbers from your CRM and headcount from a Google Sheet.

To pull from a second source, add a new module after the first. Make runs them in sequence and makes all variables from all modules available downstream. If you need parallel fetches that run simultaneously, insert a Router module to split into separate paths, then converge at the aggregation step.

Keep each module scoped to one app and one action. Scenarios that try to do too much in a single module become fragile when one data source changes its structure.

Step 5 — Aggregate and Format the Report

Once data is collected from all sources, add a Text Aggregator module. This module accepts a template string where you reference upstream variables using Make's double-curly syntax: {{1.total}} for the first module's output, {{2.count}} for the second, and so on.

A simple weekly digest template looks like this:

Weekly Summary — {{formatDate(now; "MMMM D, YYYY")}}

Tasks completed: {{1.total}}
New deals closed: {{2.count}}
Revenue this week: ${{2.total_value}}
Top task owner: {{1.owner}}

Make's built-in functions handle date formatting, number rounding, and string operations without any code. If the underlying data needs statistical summarization before it is ready to format, tools like VSLZ can handle that step: upload a file or connect a source, ask for the summary in plain English, and paste the output into your template.

Step 6 — Route to Email or Slack

After the Text Aggregator, add your delivery module.

For Slack, select the Slack app, choose Create a Message, connect your workspace, select the channel, and insert the {{text}} variable from the aggregator into the message body. Slack supports basic markdown, so you can bold section headers with asterisks: Weekly Summary.

For email, use the Email or Gmail module, select Send an Email, set the recipient and subject, then paste the aggregated text into the body field. Use line break tags between sections for paragraph breaks, or wrap the text in pre tags to preserve line spacing exactly as written.

You can add both a Slack message and an email in the same scenario. Both will fire on the same schedule with no extra configuration.

Step 7 — Test and Activate

Before activating, click Run once at the bottom of the canvas. Make executes the scenario immediately with live data and shows you exactly what each module returned and sent.

Check that data values are correct, that the message landed in Slack or your inbox, and that dates and numbers formatted as expected. Fix any variable references that return null. Most nulls are caused by column name mismatches between the filter and the actual spreadsheet header.

Once the test passes, flip the scenario to Active. Make runs it automatically on the schedule you set with no further action needed.

Common Mistakes and How to Avoid Them

Skipping the time zone offset is the most frequent error. Always convert your desired local delivery time to UTC before saving the trigger.

Using Watch Rows instead of Search Rows in Google Sheets will only return rows added since the last run, not all rows in a range. For weekly summaries that need totals across all data, use Search Rows and compute the sum in the aggregator.

Not testing with Run once before activating means the first real delivery is also the first test. This leads to broken reports going to real stakeholders. Always test first.

What Consistent Automated Reporting Delivers

Teams that automate weekly reporting reliably see two outcomes. First, the report goes out every week without depending on someone remembering to send it. Second, data is captured at a consistent point in time each week, eliminating the variation that comes from pulling numbers on different days.

Make reported that teams using scheduled automation scenarios save an average of 3.5 hours per week on manual reporting tasks. Across a five-person operations team, that adds up to over 900 hours per year.

The practical ceiling of this approach is transformation complexity. Make handles fetching, formatting, and routing extremely well. For reports that require significant computation or cleaning across large datasets, the right architecture is to analyze first and then route the output to Make for scheduled delivery.

Start with the simplest possible scenario: one data source, one destination, one schedule. Get that running reliably for two consecutive weeks before adding more sources. Automation that runs consistently is more valuable than automation that is sophisticated but fragile.