Getting Started with Excelmatic

Introduction to Excelmatic

Excelmatic is a web-based Excel AI Agent that simplifies data processing, analysis, and visualization through simple commands. Whether you're dealing with messy spreadsheets or need quick insights, Excelmatic helps you get things done faster without deep technical expertise.

Problems Excelmatic Can Solve

Excelmatic addresses a variety of Excel-related challenges across five key areas:

1. Spreadsheet Assistant: Automates routine tasks like data cleaning, formatting, and organization to make your spreadsheets more efficient.
2. Data Analytics: Performs statistical analysis, trend identification, and data summarization to uncover insights from your datasets.
3. Data Visualization: Generates charts and graphs based on your data, helping you communicate findings visually.
4. Business Intelligence: Supports advanced reporting, forecasting, and decision-making tools for business scenarios.
5. Image to Excel: Converts images of tables or data into editable Excel files, saving time on manual entry.

This guide will walk you through how to use Excelmatic in each area, starting with explanations, key ideas, and practical examples.

1. Solving Common Spreadsheet Problems with Excelmatic

Functionality Overview

Excelmatic acts as your Spreadsheet Assistant by handling tedious tasks such as data cleaning, splitting, and merging files. You simply upload your file(s) and describe what you need in natural language—Excelmatic processes it and provides an updated Excel file for download.

Key Ideas

• Start by uploading your spreadsheet to the Excelmatic web app at https://dash.excelmatic.ai.
• Use clear, descriptive commands like "Clean this data by removing duplicates and filling missing values."
• Excelmatic understands context, so specify details like column names or conditions for precision.
• Always review the output and iterate if needed by refining your command.

Practical Examples

1. Data Cleaning:
   Problem: You have a sales dataset with duplicates, missing entries, and inconsistent formatting (e.g., dates in various formats).
   Command: "Clean the dataset: remove duplicates based on 'Order ID', fill missing 'Price' with average, and standardize 'Date' to MM/DD/YYYY."
   Expected Result: A cleaned Excel file with no duplicates, filled values, and uniform dates, ready for analysis.

2. Data Splitting:
   Problem: A large customer list needs to be split into separate sheets or files by region (e.g., North, South, East, West).
   Command: "Split the data into separate sheets based on the 'Region' column."
   Expected Result: An Excel file with multiple sheets, each containing data for one region, making it easier to share or analyze regionally.

3. Multi-File Merging:
   Problem: You have monthly sales reports in separate Excel files that need to be combined into one master file.
   Command: "Merge these files: combine all sheets into one, adding a 'Month' column from the file names."
   Expected Result: A single Excel file with all data consolidated, including a new column for months, eliminating manual copy-pasting.

4. Bonus Example - Formula Automation:
   Problem: Apply complex formulas across a dataset, like calculating profit margins.
   Command: "Add a 'Profit Margin' column: (Revenue - Cost) / Revenue * 100 for each row."
   Expected Result: Updated spreadsheet with the new column populated, formatted as percentages.

2. Performing Common Data Analysis with Excelmatic

Functionality Overview

Excelmatic's Data Analytics features let you run statistical operations, identify patterns, and generate summaries directly on your data. Upload your file and command it to analyze—results come as insights, tables, or updated files.

Key Ideas

• Describe the analysis goal clearly, e.g., "Calculate averages and correlations."
• Reference specific columns or ranges for accuracy.
• Excelmatic can handle large datasets efficiently, providing both numerical results and explanations.
• Use it iteratively: Start broad, then drill down based on initial outputs.

Practical Examples

1. Descriptive Statistics:
   Problem: Summarize a dataset of employee performance metrics (e.g., scores, hours worked).
   Command: "Provide descriptive stats: mean, median, min, max for 'Score' and 'Hours' columns."
   Expected Result: A table with stats like mean score of 85, median hours of 40, plus a brief interpretation.

2. Trend Analysis:
   Problem: Identify sales trends over time in a quarterly report.
   Command: "Analyze trends: plot sales over quarters and calculate growth rates."
   Expected Result: Insights like "Sales grew 15% QoQ," with a simple line chart embedded in the response.

3. Correlation Analysis:
   Problem: Check relationships between variables, like ad spend and revenue.
   Command: "Find correlations between 'Ad Spend' and 'Revenue', and highlight strong ones."
   Expected Result: Correlation coefficient (e.g., 0.85) with an explanation: "Strong positive correlation suggests increasing ad spend boosts revenue."

4. Bonus Example - Outlier Detection:
   Problem: Spot anomalies in a financial dataset.
   Command: "Detect outliers in 'Expenses' using z-score method."
   Expected Result: List of outlier rows with explanations, and an option to remove them in the output file.

3. Creating Data Visualizations with Excelmatic

Functionality Overview

Excelmatic excels at Data Visualization by generating charts from your data descriptions. It supports common chart types and embeds previews, with downloadable Excel files containing the visuals.

Key Ideas

• Upload data and specify chart type, axes, and labels.
• Use commands like "Create a bar chart of sales by product."
• Excelmatic handles styling automatically but allows customization.
• Export charts for use in reports or presentations.

Practical Examples

1. Bar Chart Generation:
   Problem: Visualize product sales comparison.
   Command: "Generate a bar chart: 'Product' on x-axis, 'Sales' on y-axis, sorted descending."
   Expected Result: A bar chart showing top products, embedded preview, and Excel file with the chart sheet.

2. Line Chart for Trends:
   Problem: Show monthly website traffic over a year.
   Command: "Create a line chart: 'Month' on x-axis, 'Traffic' on y-axis, with trendline."
   Expected Result: Smooth line chart with a trendline, highlighting growth, downloadable as Excel.

3. Pie Chart for Proportions:
   Problem: Display market share by category.
   Command: "Make a pie chart of 'Category' shares based on 'Revenue'."
   Expected Result: Pie chart with percentages, color-coded, and an Excel file for editing.

4. Bonus Example - Scatter Plot:
   Problem: Explore relationships between height and weight in a dataset.
   Command: "Scatter plot: 'Height' vs 'Weight', add regression line."
   Expected Result: Scatter points with a fitted line, correlation info, and exportable chart.

4. Conducting Business Intelligence with Excelmatic

Functionality Overview

Excelmatic's Business Intelligence tools enable forecasting, KPI tracking, and scenario analysis. It turns raw data into actionable business insights via commands.

Key Ideas

• Frame commands around business questions, e.g., "Forecast next quarter sales."
• Provide context like historical data periods.
• Excelmatic integrates analysis with visuals for comprehensive reports.
• Use for quick prototypes before full BI tools.

Practical Examples

1. Sales Forecasting:
   Problem: Predict future sales based on past data.
   Command: "Forecast sales for next 6 months using linear regression on 'Date' and 'Sales'."
   Expected Result: Table of predicted values, e.g., "Q3: $150K," with a chart and confidence intervals.

2. KPI Dashboard:
   Problem: Track key metrics like ROI and customer acquisition cost.
   Command: "Create KPI summary: calculate ROI as (Revenue - Cost)/Cost, and CAC as Cost/Customers."
   Expected Result: Dashboard-like table with KPIs, color-coded for performance (green/red).

3. What-If Analysis:
   Problem: Simulate impact of price changes on profit.
   Command: "Run what-if: increase 'Price' by 10% and recalculate 'Profit' for all rows."
   Expected Result: Updated dataset showing new profits, with summary like "Average profit up 12%."

4. Bonus Example - Cohort Analysis:
   Problem: Analyze customer retention by signup month.
   Command: "Perform cohort analysis on 'Signup Month' and 'Retention Rate'."
   Expected Result: Heatmap table showing retention percentages, identifying drop-off patterns.

5. Converting Images to Excel with Excelmatic

Functionality Overview

Excelmatic's Image to Excel feature lets you turn screenshots, scans, photos, or chart images containing tabular (or chart) data into an editable Excel workbook—fully automatically. No prompt or command is required: just open the dedicated page, upload, and download.

Key Ideas

1. In the left navigation, click Image to Excel.
2. Drag & drop or select one (or multiple) image files (PNG, JPG, JPEG, WebP, etc.).
3. Excelmatic auto-detects tables (and in many cases chart bars/lines). A progress indicator shows extraction status.
4. Review the detected preview. If available, toggle options such as:
   • Detect headers / Treat first row as header
   • Merge split cells
   • Keep original formatting (beta)
5. Click Download Excel to get the .xlsx file or Start Chat to immediately run further cleaning, analysis, or visualization commands on the extracted data.

Advanced Tips

• Multiple Tables: If an image has several tables, Excelmatic separates them into different sheets (Sheet1, Sheet2, etc.).
• Rotated / Angled Photos: Light rotation is auto-corrected. For heavy skew, crop/re-shoot for best accuracy.
• Low Contrast or Blurry Images: Increase contrast or re-capture; OCR accuracy drops sharply with glare and compression artifacts.
• Handwritten Content: Supported experimentally—expect more manual review; ambiguous characters may be flagged.
• Charts: For bar/column charts, Excelmatic estimates underlying series values; minor rounding differences are normal.
• Privacy: Images are processed securely; delete them anytime from Recent Conversions (if enabled in your account).

Practical Examples

1. Screenshot of a Table
   Problem: You grabbed a screenshot of an online table instead of copying HTML.
   Action: Go to Image to Excel, upload the screenshot.
   Result: An Excel file with rows/columns aligned to the original table; header row auto-detected.

2. Scanned Invoice
   Problem: You need structured line items from a photographed invoice.
   Action: Upload the image; toggle Detect headers if needed.
   Result: Columns like Item, Qty, Unit Price, Amount plus a summed Total row. Ready for further analysis (e.g., "Calculate total spend by supplier").

3. Handwritten Notes
   Problem: A photo of a whiteboard table with rough figures.
   Action: Upload; review flagged uncertain cells (highlighted).
   Result: Editable sheet with best-effort transcription and notes on ambiguous entries you can correct manually.

4. Chart Image (Bar Chart)
   Problem: You only have a chart PNG from a report—no raw data.
   Action: Upload; Excelmatic detects bar heights and reconstructs an approximate dataset.
   Result: A table of categories and values plus a recreated Excel bar chart you can refine or compare.

5. Multi-Table Financial Snapshot (Bonus)
   Problem: One dashboard screenshot contains three small tables.
   Action: Upload; Excelmatic splits them into separate sheets.
   Result: Workbook with Sheet1/Sheet2/Sheet3 corresponding to each detected table.

When to Refine vs. Re-Upload

• Minor misalignment: Fix directly in Excel or continue in chat (e.g., "Clean header names").
• Systematic column shift: Re-upload a higher resolution image.
• OCR confusion (e.g., O vs 0): Use chat: "Replace letter O with zero in numeric columns." or correct manually.

Getting Help When You Encounter Issues

If something doesn't work as expected:

• Contact support via email at [email protected] or through the in-app chat.
• Join the community forum to ask questions and share tips with other users.
• For advanced issues, provide details like your command, uploaded file type, and error message.

Ready to dive in? Head to https://dash.excelmatic.ai and start your first task! If you have feedback, we'd love to hear it—what's one Excel pain point you'd like solved next?