Guide: How to Build Frequency Tables in Google Sheets

### OverviewEvery business has *that* sheet: hundreds or thousands of rows of leads, orders, survey responses, or ticket logs. Hidden inside is a simple question: "What happens most often?" A frequency table in Google Sheets answers that instantly.Below are three levels of sophistication for building frequency tables:1) Hands-on, manual methods in Google Sheets.2) No-code automation tools to reduce clicking.3) Scaled, AI-agent workflows that let Simular handle the computer work for you.---## 1. Manual ways to build a frequency table in Google SheetsThese approaches are perfect when you’re still designing your analysis or working on small datasets.### Method 1: UNIQUE + COUNTIF (simple categorical analysis)Use this when you want to know how often each category appears (e.g., lead source, campaign, rating).**Step-by-step:**1. **Prepare your data** - Put your raw values in a single column, e.g. column A with header `Rating`. - Make sure there are no completely empty rows in the middle.2. **Generate unique categories** - Click an empty cell, e.g. `B2`. - Enter: `=UNIQUE(A2:A)` - This creates a list of each unique value from column A.3. **Count each category with COUNTIF** - In `C2`, enter: `=COUNTIF($A$2:$A, B2)` - Drag the fill handle down to fill counts for all categories in column B.4. **Turn counts into a proper table** - Add headers: `Category` in B1, `Frequency` in C1. - Optionally, sort by column C (Data → Sort range) to see top values first.**Pros:** - Very transparent; easy to audit. - Works for most everyday business lists. **Cons:** - Needs manual refresh if new categories appear. - Easy to break if someone edits formulas.Official reference: COUNTIF and UNIQUE are documented in Google’s function list: [Google Docs Editors Help](https://support.google.com/docs/topic/3105474).---### Method 2: FREQUENCY for numeric dataUse this when your data is numeric (e.g., deal size, age, response time) and you want to group values into ranges or "bins".**Step-by-step:**1. **Set up your data and bins** - Put numbers in column A (e.g., `A2:A101`). - In column B, define your class boundaries, e.g.: 10, 20, 30, 40.2. **Use the FREQUENCY function** - Select a vertical range next to your bins, e.g. `C2:C6` (note: one more row than your bins). - Type: `=FREQUENCY(A2:A101, B2:B5)` - Press **Ctrl+Shift+Enter** if needed (on some setups) to enter as an array formula; in modern Sheets, just Enter works.3. **Label your results** - Add labels like `<=10`, `11–20`, `21–30`, `31–40`, `>40` aligned with the output in column C.**Pros:** - Perfect for histograms and numeric distributions. - Handles large datasets efficiently.**Cons:** - Less intuitive than COUNTIF. - Slightly rigid: changing bins means rethinking the labels.Official FREQUENCY docs: [FREQUENCY – Google Docs Editors Help](https://support.google.com/docs/answer/3094286).---### Method 3: Pivot tables (fast, flexible, dynamic)Pivot tables automatically count how often each value appears, without writing formulas.**Step-by-step:**1. **Select your dataset** - Click any cell inside your data range (e.g., A1).2. **Create a pivot table** - Go to `Insert → Pivot table`. - Confirm the data range. Choose "New sheet" and click **Create**.3. **Build the frequency table** - In the Pivot table editor: - Under **Rows**, add your field (e.g., `Rating` or `Lead Source`). - Under **Values**, add that same field again and set **Summarize by** → `COUNTA`.4. **Sort & format** - Click the drop-down beside your value field and sort Z→A to see most frequent values first. - Format as needed.**Pros:** - No formulas to maintain. - Updates easily when rows are added (just refresh). - Great foundation for dashboards.**Cons:** - Can feel intimidating for non-analysts. - Less customizable than raw formulas in some cases.Official pivot table guide: [Create and use pivot tables](https://support.google.com/docs/answer/1272900).---## 2. No-code automation around frequency tablesOnce you know how to build frequency tables, the next question is: **how do I stop doing this manually every week?** That’s where no-code tools come in.### Idea 1: Automatically feed new data into Google SheetsUse tools like Zapier, Make, or native integrations (e.g., from your CRM) to pipe new leads, orders, or survey results directly into a "raw data" tab. Your frequency table (built with a pivot table or formulas) then always reflects the latest data.**Workflow outline:**- Trigger: new lead in CRM / new form response. - Action: append a row into `Raw_Data` sheet in Google Sheets. - Your frequency table uses formulas pointing at the entire column (e.g., `A2:A`) so it auto-updates.### Idea 2: Snapshot frequency tables for reportsUse no-code schedulers to copy frequency table results into a "Weekly Report" sheet each Monday morning, timestamped, ready for client or stakeholder review.**Pros of no-code:** - Reduces manual exports and copy-paste. - Good for teams without engineering support. **Cons:** - Still limited to predefined triggers and actions. - Logic can get messy across many zaps or scenarios. - Tools can’t truly "use" the computer like a human does.---## 3. Scaled, AI-agent workflows with SimularAt some point, your spreadsheet work stops being about a single table and starts being about **dozens of repetitive, cross-app workflows**. This is where a Simular AI computer agent shines: it behaves like a power user who never gets tired.### Method 1: Agent builds and refreshes your Google Sheets frequency tables**What the Simular agent does:**- Opens your Google Sheet on your desktop or in the browser. - Imports or syncs new data from email attachments, CSVs, or web apps (just like a human would). - Creates or updates the frequency table using COUNTIF/UNIQUE, FREQUENCY, or pivot tables. - Applies conditional formatting, adjusts sorting, and labels charts.**Why this matters for business owners and agencies:** You define the outcome ("Give me a frequency table of lead source by week"), and the Simular agent performs every click, drag, and formula edit reliably, run after run.**Pros:** - Production-grade reliability over thousands of steps. - Transparent execution: you can inspect every action the agent takes. - No need to redesign your process around APIs; it works on your existing desktop and browser.**Cons:** - Requires a bit of upfront onboarding and prompt design. - Best suited once the workflow is stable and worth automating.Learn more about Simular Pro’s capabilities: [Simular Pro](https://www.simular.ai/simular-pro).---### Method 2: Multi-step analytics workflows driven by an AI agentFor marketers and sales leaders, the frequency table is just step one. A Simular AI agent can:- Pull performance data from ad platforms into Google Sheets. - Build frequency tables for impressions, clicks, or leads by campaign, country, or creative. - Generate summaries and insights ("Top 5 campaigns by lead volume this week"). - Post a formatted report into Slack or email.Here, the agent automates **the entire analytics loop**, not just the table-building step.**Pros:** - End-to-end workflow automation across apps. - Reduces context switching between browser tabs and tools. - Frees up teams to focus on creative and strategic decisions.**Cons:** - Needs clear success criteria and guardrails. - You should review early runs before letting it post directly to clients.By combining Google Sheets’ native power (FREQUENCY, pivot tables) with a Simular AI computer agent, you move from "I know how to build a frequency table" to "I never have to build one manually again."