Querri for Cleaning Lists & Notes An AI Data Analytics Tool for List Cleaning in Excel, CSVs, and CRM Exports — Without Formulas

Messy lists are the silent killer of business insights...duplicates, typos, and format issues all get in the way. Querri makes it easy to clean and standardize your lists so you can trust your data and move forward faster.

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See Querri Clean Lists in Action

Watch how Querri uses agentic AI to transform a messy spreadsheet into clean, reliable data — ready for reporting, analysis, or dashboards.

Why Dirty Lists Wreck Your Analysis

When lists aren't cleaned properly, everything downstream suffers.

Messy data leads to:

  • Duplicate rows that inflate counts
  • Inconsistent categories that break grouping and reporting
  • Free-text notes that never get used
  • Hours lost fixing spreadsheets before every analysis

Most teams don't realize how much insight they're losing until they clean the data properly — and by then, decisions have already been made.

Dirty data analysis problems
Querri data cleaning interface

Querri Turns Messy Lists into Reliable, Ready-to-Use Data

Querri lets you upload your list—no matter how messy—and get clean, deduplicated, and standardized results in minutes.

Just describe what you want: "Clean up inconsistent capitalization and spacing in customer names," and Querri does the rest. It highlights issues, suggests fixes, and transforms your data automatically.

You can preview, edit, and export a clean list—ready for analysis, outreach, or reporting.

Turning Notes & Comments into Structured Data

Most lists hide valuable insights in notes and free-text columns.

Querri's Researcher tool turns that unstructured text into usable data by extracting themes, categorizing comments, summarizing long entries, and surfacing trends across thousands of rows.

Instead of ignoring messy notes fields, Querri can:

  • Extract key themes and patterns from notes columns
  • Turn unstructured comments into categories or tags
  • Summarize long text fields into usable insights
  • Surface trends hidden across thousands of rows

What was once ignored text becomes structured data you can analyze, filter, and visualize.

Querri Researcher structured data extraction from notes

Business Outcomes of Cleaned Lists

Clean, Deduplicated Lists You Can Trust

Hours saved on manual spreadsheet cleanup

More accurate reporting and forecasting

Better segmentation for marketing and sales

Smarter joins and analysis across data sources

How-To in Five simple steps

1

Upload Your List

Import Excel, CSV, or exports from tools like CRMs, Sheets, or cloud storage.

2

Profile the Data

Querri scans for missing fields, inconsistent formats (like dates, phone numbers, states), and duplicated rows.

3

Clean It Up

Use prompts like: "Remove duplicates based on email and name" "Fix inconsistent state abbreviations" "Standardize casing for names and addresses" "Flag incomplete rows with missing phone numbers"

4

Review and Approve

See suggestions and choose what to apply. You stay in control.

5

Export or Automate

Download the cleaned list or set it to auto-clean on upload for future runs.

How to clean data with Querri

Best Practices

Start With a Clear Key

Know what field(s) define a duplicate—email, name + address, SKU, etc. This makes deduplication reliable.

Watch for Hidden Inconsistencies

"New York" vs. "NY", "Inc." vs "Incorporated"—small differences break joins and analyses. Use Querri to standardize categories and text fields

Segment Before You Clean (Optional)

If your list has multiple types of entries (e.g., vendors and customers), segment them first. Different types often need different rules.

Automate for Reuse

If you regularly pull data from the same source, set up auto-cleaning rules in Querri so your lists stay ready to go.

Data cleaning best practices

FAQs

How do I find issues in a messy spreadsheet or list?
Upload your list and ask Querri to scan for common issues. Querri will identify missing fields, duplicates, typos, and formatting inconsistencies automatically.
Can Querri clean lists with names, emails, and phone numbers?
Yes. You can ask to standardize names (capitalize properly), deduplicate by email, and fix phone number formatting.
How do I clean and merge lists from multiple sources?
Querri can merge lists and help align formats across them. Use prompts like "Merge and deduplicate these customer lists by email."
Can I customize the cleaning rules?
Absolutely. You can ask for specific rules like "Only keep the most recent row per email" or "Exclude test records."
What formats can I export the cleaned data in?
CSV, Excel, and JSON are supported.
Will Querri show me what was changed?
Yes. Every change is transparent, and you can access the code, the plain-English summary, and analytical logic for every step by expanding a table or graph.
How do I extract data from a notes or comments column?
Use Querri's Researcher tool to analyze notes and comments row by row. Describe what you want to extract—such as themes, categories, names, or amounts—and Querri turns free-text into structured, analysis-ready columns automatically.
How can I clean data automatically on an ongoing basis?
Once a list is cleaned, you can automate the process so new data is cleaned the same way every time — keeping your analysis reliable without repeated manual work.
How do I standardize data across multiple spreadsheets?
Upload multiple files into Querri and clean them using consistent rules. This makes it easy to standardize categories, formats, and naming across datasets.
How can I clean lists without using Excel formulas?
Querri replaces formulas with a conversational interface. You describe what you want cleaned, and Querri applies the changes transparently — no VLOOKUPs, IF statements, or scripts.
How do I clean messy spreadsheets automatically?
Upload your spreadsheet to Querri and ask it to scan for common issues. Querri automatically detects duplicates, missing values, inconsistent formatting, and messy categories, then applies clean-up steps using AI—no formulas, scripts, or manual work required.
Can I use AI to clean CSV files?
Yes. Querri uses AI to clean CSV files by profiling the data, identifying errors or inconsistencies, and standardizing fields automatically. Once cleaned, the data can be exported or reused for analysis, reporting, or dashboards.
Frequently asked questions about data cleaning

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