The AI Assistant That Tracks Your Entire Business: Sales, Tasks, Emails, Clients

As a solopreneur, you are the CEO, the CMO, the Support Lead, and the Janitor.

You have data everywhere:

* Stripe for revenue.

* Asana/Notion for tasks.

* Gmail for client comms.

* Google Analytics for traffic.

To get a "pulse check" on your business, you have to log into 5 different dashboards. It takes 20 minutes, and usually, you just get distracted by a notification and forget why you logged in.

What if you had a Chief of Staff who handed you a single-page executive summary every morning at 8:00 AM?

"Good morning. Yesterday we made $400. Traffic is up 10%. You have 3 urgent emails from VIP clients, and your main goal today is finishing the landing page."

This guide shows you how to build that AI Chief of Staff using Make.com and GPT-4.

Time to build: 45 minutes Tools required: Make.com, OpenAI API, Stripe, Google Analytics, Gmail, Task Manager (Asana/Notion)

Why You Need an AI "Chief of Staff"

Context Switching Kills Focus: Every time you check Stripe, you risk falling down a rabbit hole. This automation brings the data to you.

Pattern Recognition: AI can spot trends you miss. It can say "Revenue is down 15% this week compared to last week."

Accountability: Starting the day with a clear summary of "What I accomplished yesterday" vs "What I need to do today" keeps you honest.

The Workflow Blueprint

Trigger: Scheduled every morning at 8:00 AM.

Gather: The automation runs parallel paths to fetch data from Stripe, Analytics, Gmail, and Asana.

Aggregate: It combines all this raw text into one large "Context String".

Analyze: GPT-4 reads the context and writes a structured report.

Deliver: The report is emailed to you (or sent to Slack).

Step-by-Step Setup Guide

Phase 1: The Data Collectors

Create a new Scenario in Make.com. Start with a Timer trigger set to run "Every day at 8:00".

Add a Router to split the flow into multiple paths. We will gather data in parallel.

Path A: Revenue (Stripe)

Add Stripe -> "List Balance History" or "List Charges".

Filter for Created >= addDays(now; -1) (Yesterday).

Add a Text Aggregator module. Group the amounts to get a total sum.

Path B: Traffic (Google Analytics 4)

Add Google Analytics 4 -> "Run a Report".

Date range: Yesterday.

Metrics: activeUsers, screenPageViews.

Add a Text Aggregator to format this into a string: "Yesterday's Traffic: [Users] users, [Views] views."

Path C: Tasks (Asana/Notion)

Add Asana -> "Get Tasks from a Project".

Filter for Completed At >= Yesterday OR Due Date = Today.

Add a Text Aggregator. Format: "- [Task Name] (Status: [Completed/Due])".

Path D: Emails (Gmail)

Add Gmail -> "Search Emails".

Query: label:inbox is:unread category:primary.

Add a Text Aggregator. Format: "- From: [Sender Name], Subject: [Subject]".

Phase 2: The Brain (OpenAI)

Now, we need to bring all these paths back together.

Note: In Make, parallel paths don't automatically merge. You usually store the results in variables or use a specific pattern. For simplicity, you can run these modules in series (one after another) instead of parallel if you are new to Make.*

Let's assume you ran them in series. You now have 4 text strings: RevenueString, TrafficString, TaskString, EmailString.

Add OpenAI (ChatGPT) -> "Create a Completion".

Model: gpt-4 (or gpt-4o).

System Prompt:

> You are a ruthless, efficient Chief of Staff for a busy solopreneur. Your job is to summarize the business performance. Be concise. Use bullet points. Highlight red flags.

User Prompt:

> Here is the data for yesterday:

>

> Financials: {{RevenueString}}

> Traffic: {{TrafficString}}

> Tasks: {{TaskString}}

> Inbox: {{EmailString}}

>

> Write my Daily Executive Briefing.

Phase 3: The Delivery

Add Gmail -> "Send an Email".

To: Your Email.

Subject: ☀️ Daily Business Briefing - {{formatDate(now; "MM/DD")}}

Body: Map the output (Content) from the OpenAI module.

Optional: Convert Markdown to HTML using a "Markdown" module before sending for a prettier email.

Advanced Enhancements

1. "Sentiment Analysis" on Support Tickets

Connect your Helpdesk (Zendesk/Freshdesk). Ask AI to analyze the tone of tickets.

Report:* "Customer sentiment was negative yesterday. 3 complaints about the login page."

2. Competitor Watch

Add a module to scrape a competitor's pricing page or check their latest tweet. Include this in the briefing.

Report:* "Competitor X launched a Black Friday deal today."

3. Weekly vs Daily

Clone this scenario to run on Fridays. Change the date filters to addDays(now; -7). Change the prompt to "Write a Weekly Review".

Real-World Example: The "SaaS Founder" Dashboard

I use this for my SaaS. My morning email tells me:

MRR Movement: Did we gain or lose subscribers? (Stripe)

Server Health: Were there any downtime alerts? (Datadog/Email alerts)

Demo Requests: Who booked a call? (Calendly)

I read it while drinking coffee. By the time I sit at my desk, I know exactly what fire to put out or what win to celebrate.

Conclusion

You don't need a dashboard with 50 charts. You need insights.

By automating the collection and synthesis of your business data, you stop being a "Data Entry Clerk" and start being the Executive.

Ready to build this?

* Get your free Make.com account here

* Get an OpenAI API Key

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