The tables are structurally clear, but using customer UUIDs instead of customer names makes the best-customer results less immediately readable for nontechnical users.
What was measured
Result Readability
Is the answer easy for a non-technical user to understand?
transformation
What was given, what came back
Test input: Best customers with unpaid-order and payment-method follow-ups · text · group: ecommerce-nl2sql-benchmark
Input — what we sent
The exact prompt
Who are my best customers — the ones who order the most and spend the most? Follow-up 1: For the top 3 from that list — do any of them have unpaid orders? Follow-up 2: What payment methods do these top 3 usually use?
A conversational multi-table customer analysis that identifies best customers by both order volume and spend, then drills into unpaid orders and payment methods for the top 3.
Why this input is hard
- · Ambiguous business-term interpretation
- · Multi-table joins across customers orders and payments
- · Aggregation and ranking
- · Follow-up context retention
- · Scoped drill-down to the top 3 customers
- · Readable customer-level output
Output — unretouched
Also checked on this input — same tool, 5 other criteria
Ambiguity Handling✓ WorkedWhen the phrase "best customers" was ambiguous, it did not guess a single meaning; it split the request into separate order-count and spend rankings.Chart / Visualization Support✓ WorkedSupports visualization on the customer-analysis thread by generating bar-chart views for both spend ranking and order-count ranking.Follow-Up Context✓ WorkedCarries the top-3 customer identities forward across follow-ups and regenerates fresh SQL on each turn, preserving context correctly across at least two drill-down questions.Plain English Query Handling✓ WorkedHandles an informal conversational request about top customers without needing the user to translate it into SQL.SQL Visibility✓ WorkedShows the generated SQL inline so users can inspect the aggregation and ordering logic, including the GROUP BY and ORDER BY clauses.
Provenance
- Observation
- 47bff1e4-d428-4f7d-98df-6a986d163cd5
- Evidence run
- db2bb5d5-0e0e-4cb3-8d76-3555c45c23cd
- Study
- Query Live Databases Using Plain English with AI
- Research task
- 86b9y6c99
- Tested at
- not recorded
- Source
- first-party
- Evidence state
- verified
- Proof shown
- input + output shown
- Cost / latency
- not captured
- Repeat run
- not captured
- Tester
- not captured
The last three rows are honest blanks, not placeholders — our capture has no field for them yet.
Query this
get_evidence({
tool: "querio",
scenario: "ecommerce-nl2sql-benchmark"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 2 other tools
measured on Result Readability
AskYourDatabase✓ WorkedPresented the follow-up results as clearly labeled customer status blocks such as 'All Clear', '1 Unpaid', and 'All 4 Unpaid!', which makes the risk scan easy.Definite✓ WorkedThe ranked customer table was readable and easy to scan, with rank, orders, total spend, and average order value clearly laid out for the top 20 customers.
This evidence is published in
From the same study (page rebuilt from a later run)
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com