How to Build Custom Quote Templates in Google Sheets

1. Start With a Manual Quote Template in Google Sheets

Before you automate anything, you need a solid base template.

1. Create a new Google Sheet and name it something like Master Quote Template.
2. In the header rows, add cells for quote number, date, client name, company, contact details, validity period, and payment terms.
3. Build an item table with columns such as Item description, Quantity, Unit price, Discount, Tax rate, Line total.
4. Use formulas for calculations. For example, in Line total use:
   =ROUND((Quantity * Unit_price) * (1 - Discount) * (1 + Tax_rate), 2)
5. Add a subtotal row, tax breakdown, and grand total at the bottom with SUM formulas.
6. Apply formatting: bold headers, currency format on price cells, data validation for tax or currency fields, and conditional formatting to highlight missing required fields.
7. Protect the structure. Lock formula ranges and layout rows so users can only edit input cells, reducing accidental breakage.
8. When sending a quote manually, duplicate the template tab, fill in client details, export as PDF, then email it from Gmail.

Pros (manual): Full control, easy to tweak on the fly, no setup beyond Sheets.
Cons: Error prone, slow at volume, depends on careful humans every time.

2. Semi Automate With Sheets Features and Scripts

Once the basics work, you can strip out some repetition without yet using an AI agent.

• Use a control sheet for products and pricing, then pull those into the quote tab with VLOOKUP or INDEX MATCH based on a product code.
• Add a simple Apps Script or no-code add-on that auto generates a unique quote ID and timestamps when you press a button.
• Create a PDF export script bound to the sheet that saves the quote to a Google Drive folder and opens an email draft with the PDF attached.

This already saves minutes per quote and reduces typing errors, but it still expects a human to know which client, which products, and what discounts to apply.

Pros (semi automated): Faster, fewer typos, still transparent and editable.
Cons: You are still the operator; scripts cannot reason about edge cases or negotiate pricing.

3. Automate at Scale With a Simular AI Computer Agent

Now imagine your quote template is a checklist your Simular AI agent follows on your behalf.

You configure a Simular Pro computer use agent with access to your browser, Google Sheets, and email. Then you describe the workflow in plain language, for example:

• Monitor a CRM view or a dedicated inbox for new quote requests.
• When a new request appears, open the Master Quote Template in Google Sheets.
• Duplicate the template tab and rename it with the client name and date.
• Parse the requested services and quantities from the email or CRM record.
• Look up standard pricing in the products sheet and apply any rules you define, such as partner discounts or volume breaks.
• Fill all client details, line items, and terms into the new quote tab.
• Validate that required cells are not blank and that totals match your pricing rules.
• Export the quote as a PDF and draft an email to the client, ready for your review or automatic sending.
• Log the quote details and link into a summary sheet for reporting.

Because Simular agents operate like a careful human, every step is visible and replayable. You can watch runs, inspect which cells were edited, and adjust your instructions if you want to change pricing logic or formatting.

Pros (AI agent at scale): Massive time savings, consistent formatting, fewer mistakes, and true end-to-end automation from request to ready-to-send quote. Frees sales teams to focus on conversations, not spreadsheets.
Cons: Requires an initial investment of time to define your rules, test edge cases, and decide which steps the agent can fully automate versus where you still want human approval.

4. Choosing the Right Level of Automation

If you only send a few quotes a month, a well-built manual template in Google Sheets may be enough. As volume grows, semi-automated scripts smooth the rough edges. When quoting becomes a daily grind or you have multiple reps sending similar proposals, delegating the flow to a Simular AI computer agent turns quoting into an invisible background process.

The sweet spot for most agencies, service businesses, and SaaS teams is a hybrid: the agent prepares quotes end-to-end, and humans simply review and approve. Your template becomes a living spec for how your business prices work, and the agent handles the clicks.