What automated reporting services include
Automated reporting is a set of scheduled data pulls, calculations and deliveries that turn raw numbers from your business apps into reports people actually read. Data comes from sources like your CRM, Google Analytics 4, ad platforms, Shopify and accounting software, lands in one place, and feeds a live dashboard and a written summary.
The written part matters. Most owners don’t want another dashboard to log into. They want a short note on Monday saying leads were up, cost per lead rose on Meta, and two large invoices are overdue. An AI model writes that summary from the numbers, and every figure links back to the source.
We run reporting this way ourselves. Every client of ours gets a report every two weeks, and the pipelines we build for you follow the same approach.
What we build
Data pipelines
Scheduled pulls from your apps into Google Sheets, BigQuery or a PostgreSQL database, with history kept so you can compare periods.
Dashboards
Looker Studio or Power BI dashboards with the handful of metrics that drive decisions, filtered by team, location or client.
AI-written summaries
A short plain-English digest of what changed and why it might matter, sent by email or posted to Slack or Teams.
Threshold alerts
Messages when something moves outside a range you set, such as ad spend pacing too fast or a day with no leads.
Branded PDF reports
Scheduled PDF reports with your logo for owners, investors or clients who prefer a document.
Agreed metric definitions
A written glossary so ‘lead’, ‘revenue’ and ‘conversion’ mean the same thing in every report.
Reports we automate
Owner’s weekly KPI digest
Leads, booked jobs, revenue, cash in the bank and overdue invoices in one email every Monday.
Automated client reporting for agencies
White-label reports for each of your clients, pulling GA4, Search Console, Google Ads and Meta Ads data, with a drafted commentary your account manager checks before it goes out.
Sales pipeline report
New deals, stage movement, stalled deals and win rate by rep, straight from HubSpot, Pipedrive or Salesforce.
E-commerce performance
Orders, average order value, returns, ad spend and stock levels from Shopify and your ad accounts.
Operations and support
Ticket volumes, response times and backlog from your help desk, plus job completion from field service tools.
How we set up your reporting
- Decide what matters In the free audit we ask who reads each report and which decisions it should inform, then cut everything else.
- Connect sources We connect each data source with read-only access and check the numbers against what the source app shows.
- Build and review You review the dashboard and a sample summary, and we adjust until the numbers and wording are right.
- Run and maintain We fix connectors when an app changes its API and review accuracy as part of our report every two weeks.
Reporting for agencies and multi-location businesses
Agencies tend to spend the most hours on reports, because every client wants their own. We build one pipeline that produces a branded report per client, and our page for marketing agencies covers that setup in more detail. The same approach suits franchises and multi-location businesses that want one view per site.
Reporting often goes hand in hand with other automation. Leads scored by AI lead qualification show up by source and quality, and data from systems without an API can be pulled by our RPA services.
Questions we get about automated reporting
Looker Studio or Power BI?
Looker Studio is free and works well with Google data sources. Power BI suits businesses already on Microsoft 365 or with more complex data models. We’ll recommend one based on your tools and who needs access.
Can you white-label reports for our agency’s clients?
Yes. Reports carry your branding and are sent from your domain. Agencies often have their account managers review the AI-drafted commentary before it’s sent.
What if the numbers in the report don’t match the app?
We check every metric against its source during setup and document how each is calculated. When differences show up later, it’s usually a timezone, attribution or definition issue, and we track it down.
Can we get historical data, not just from today forward?
Usually, yes. Most apps let us backfill past data through their API, though some limit how far back you can go. We’ll confirm what’s available for each source.