Spreadsheet Answerability Checker Demo
A sales ops lead is preparing a Monday revenue review from a small CRM export: customers, orders, and a sheet of questions from the team. Some questions are straightforward, like which products generated the most revenue. Others ask for profitability, regional performance, or delayed orders, but the workbook is missing the fields those answers depend on. ThinkRows separates the questions the file can support from the ones that would need more evidence, then uses the mapped columns to generate a focused follow-up workbook.
Start with the workbook the team brought in
These are the original sheets ThinkRows receives. The tabs keep each sheet visible so the rest of the walkthrough can point back to the actual columns, gaps, and relationships in the file.
- Customers the team wants to segment, with signup dates, status, and some missing regions.
- Orders tied to customer IDs, products, quantities, and revenue for the review.
- A Questions sheet capturing what the sales team wants answered before Monday.
ThinkRows checks the evidence before the review
The Monday review needs more than a cleaned spreadsheet. It needs a clear line between questions the export can answer and questions that would send the team chasing a false signal. ThinkRows reads the sheets, maps the relationships, and shows where the evidence stops.
Step 1: Start with the questions waiting for Monday
The sales ops lead uploads the CRM export, adds the review context, and includes the questions the team plans to ask: product purchases, revenue by region, profitability, and delayed orders.
Before the verdicts, ThinkRows turns sheets into usable tables
The CRM export has sheet tabs, but that does not make it a trustworthy data model. ThinkRows first finds the actual customer, order, and question tables, extracts them, and uses those tables as the evidence for the review.
Step 2: Map the customer and order evidence
It maps customers, orders, products, and the team's business questions, then uses those relationships to judge product and revenue questions without guessing.
Step 3: Return verdicts the team can discuss
The output package keeps the question verdicts, extracted orders, and extracted customers as separate Excel tables. The same mapped columns power the follow-up workbook the sales ops lead can send after the review.
Then sales ops asks for the workbook they need next
Once the report shows which fields are safe to use, the sales ops lead can ask for a small follow-up workbook in plain English. This is where the answerability check turns into a concrete file the team can inspect or send around.
Transform: Ask for the follow-up table in plain English
The request references mapped columns with @ mentions, so ThinkRows knows which quantity, order ID, and customer fields belong in the follow-up table.
Plan: Review the plan before generating the workbook
ThinkRows shows the source tables, output sheet name, validation result, and sample preview before the sales ops lead approves generation.
Preview: Check the rows before the file is created
The preview confirms the shape: order ID, quantity, and customer for the orders that match the requested filter.
Result: Download the follow-up workbook
The final screen produces the compact table as a workbook, ready for the review follow-up instead of another round of manual copying.
Final outputs
The final package gives the review a safer starting point
It maps customers, orders, products, and the team's business questions, then uses those relationships to judge product and revenue questions without guessing.
The output package keeps the question verdicts, extracted orders, and extracted customers as separate Excel tables. The same mapped columns power the follow-up workbook the sales ops lead can send after the review.
Output workbook tables
ThinkRows returns the identified tables as Excel output. Use the tabs to inspect the extracted tables from this demo.
