Beauty Salon Daily Operations Report

A portfolio-ready Make automation scenario that reads CRM and automation log data from Airtable, aggregates operational activity, calculates event-type summaries, and sends a concise Telegram report for quick business visibility.

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Scenario modules
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Tests passed
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Event types
Tested successfully
Overview

Project Overview

A reporting layer for a beauty-service CRM pipeline. The scenario turns raw CRM and automation-log records into a concise operational summary that a business owner can read without opening Airtable or Make.

MakeAirtableTelegram BotOperational Reporting
/ beauty-salon-daily-operations-report
MAKE SCENARIO { "source": "Airtable / Leads_clean + Automation_Logs", "event_summary": { "lead_created": 6, "duplicate_lead": 4, "missing_email": 4, "workflow_error": 1 }, "delivery": "Telegram Bot", "schedule": "daily_09_00_configured_inactive", "status": "tested_successfully" }

Problem

Operational data existed in Airtable, but the owner would still need to manually inspect lead rows and automation logs to understand daily activity.

Solution

Make reads the relevant Airtable tables, aggregates records, calculates event counts, and sends a compact Telegram report.

🎯

Outcome

A repeatable daily report that proves data retrieval, aggregation, event categorization and Telegram delivery in one scenario.

Architecture

Automation Architecture

The scenario uses a linear production-safe design: read source records, aggregate bundles, calculate event categories, build a report variable, then send it to Telegram. Click any module to inspect it.

Search Leadssource · Airtable Aggregateaggregate Search Logssource · Airtable Event Countssummary Aggregate Logsaggregate Build Reportcompose Telegramnotify
Click a node to inspect it

A daily Make scenario: read Airtable CRM + logs, aggregate event counts, build a report, and send it to Telegram.

Test Matrix

Final Test Matrix

The scenario was manually executed after configuration. Daily 09:00 scheduling was configured but left inactive to avoid unnecessary Make operations.

TestExpected resultStatus
Airtable Leads_clean readLead records retrieved✓ Passed
Airtable Automation_Logs readLog records retrieved✓ Passed
Lead aggregation10 lead records counted✓ Passed
Log aggregation10 log records counted✓ Passed
Event type summary6 new leads, 4 duplicates, 4 missing-email events, 1 workflow error✓ Passed
Telegram deliveryDaily report delivered to bot chat✓ Passed
Schedule configurationDaily at 09:00 configured, scenario left inactive intentionally✓ Passed
Production note: The scenario is intentionally deactivated after successful testing. This prevents unnecessary scheduled executions while preserving a demonstrable production-ready configuration.
Proof, not mockups

Screenshots & Evidence

Final proof screenshots from the working Make scenario, Telegram output and Airtable source tables.

Make final scenario architecture
Make final scenario architecture

Complete production-ready reporting scenario with Airtable searches, array aggregators, event-type summaries, report composition and Telegram delivery.

Telegram report delivery
Telegram report delivery

Final operational report with dynamic counts: 10 lead records, 10 log records, 6 new leads, 4 duplicate attempts, 4 missing-email events and 1 workflow error.

Airtable Automation_Logs
Airtable Automation_Logs

Operational event history used for lead_created, duplicate_lead, missing_email and workflow_error summaries.

Airtable Leads_clean
Airtable Leads_clean

Validated lead records used as the CRM source table for the daily reporting scenario.

Notes

Limitations & Intentional Decisions

Scenario is inactive

Daily 09:00 scheduling is configured but inactive by choice. This avoids unnecessary Make operations while keeping the setup demonstrable.

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Demo dataset

Visible records are sample data created for the portfolio case study. No real client data is exposed.

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Explicit event searches

Separate Airtable searches were chosen over complex inline array expressions to improve readability, reliability and debugging.

Skills Demonstrated

Beyond app-to-app integration.

This project demonstrates Make automation design beyond basic app-to-app integration.

Make Scenario Design

Built a readable scenario with clear module naming, controlled data flow and separated reporting responsibilities.

📊

Airtable Data Operations

Used Airtable searches with formula filters to retrieve targeted CRM and operational log data.

Σ

Aggregation Logic

Used array aggregators and __IMTAGGLENGTH__ to convert bundles into usable report metrics.

📋

Operational Reporting

Converted raw records and event logs into a concise report for business decision-making.

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Telegram Delivery

Configured Telegram Bot integration for direct operational notifications.

Production Judgment

Configured scheduling but deactivated the scenario after proof to control unnecessary operations.

Handoff notes: Final packaging will include Make blueprint/export, clean screenshots, README, restore checklist, GitHub structure and Vercel portfolio integration. Credentials and tokens must never be committed.
×Enlarged proof screenshot