Example report

This is how it looks

This sample uses a completed DemandEcho investigation. Start with Competitive Intel, then inspect the customer complaints, weak spots, switching reasons, and the public conversations behind every finding.

DemandEcho research dossier UNLOCKEDResearch Report

market signalDeterministic fallback

The signal behind your idea.

A tool that helps Shopify store owners recover abandoned carts with friendly, timed email nudges

Research date: Sep 13, 2026
Searched: 10
Returned: 7
Signals: 38
Coverage: Limited

Demand score

0/100

MODERATE SIGNAL

A real, repeating thread — worth validating further before building.

Derived from observed customer evidence

Executive summary

38 customer signals found across hacker-news and github and stackoverflow and gitlab and stackexchange and lemmy and news (partial coverage — some sources didn’t respond). Strongest customer theme: “Customers want abandoned carts that feel timely and personal”. 1225 non-customer conversations (developer, general or ambiguous) were excluded from the customer-demand assessment. The classification is based on consistent evidence rules and the linked conversations.

Evidence · ModerateCoverage · Limited

Conversations evaluated

1000

All valid public candidates evaluated before relevance and customer-demand exclusions.

Communities evaluated

230

Distinct source communities represented in the collected evidence.

Platforms searched

Public source platforms the research run attempted.

Customer signals

Customer-eligible conversations driving the demand analysis.

Strong customer signals

Customer evidence with high relevance to the idea.

Customer communities

Independent communities with meaningful activity.

Platforms returned

Platforms that returned evidence.

Competitive Intel

Your competitive landscape

Explore the options customers mention and the friction in their workflows. These option mentions need more corroboration before they can support firm competitor conclusions.

1 finding

Observed weak spots

0 findings

Customer complaints

Evidence still limited

No complaint wording was directly stated.

1 finding

Switching reasons

Evidence chronology

When the collected conversations were published

Publication chronology across every dated conversation collected from the searched sources and communities.

Customer themes

What customers keep saying

Themes are built from customer evidence only — each one links to the actual customer conversations that support it. Developer/technical discussion is deliberately excluded from this section.

Interactive brief

Your research, distilled

Read the most important patterns first, then open the evidence behind them whenever you need it.

Why this score

How the demand score breaks down

Six weighted factors, each measured from the persisted evidence and combined by a documented deterministic formula — reproducible, never an AI guess.

Intent strength49%

How explicitly people are seeking a solution for this.

Relevance38%

How closely the conversations match the described idea.

Evidence volume98%

How many distinct conversations were collected.

Source diversity100%

How many independent communities surfaced signals.

Recency97%

How recently the activity happened.

Repeated themes50%

Whether the same theme recurs across evidence.

Factor	Weight	Value	Effect
Intent strength	30%	49%	15 pts
Relevance	20%	38%	8 pts
Evidence volume	20%	98%	20 pts
Source diversity	15%	100%	15 pts
Recency	10%	97%	10 pts
Repeated themes	5%	50%	3 pts

Score = weighted sum of the six factors × a small-sample dampener (×1.00), so a tiny number of very strong signals never looks identical to broad, repeated demand. Reproducible from the persisted evidence.

Communities

Where the demand lives

Ranked by the share of evidence each community contributed. Sampling differs per platform, so treat shares as indicative — never as an exact market measure.

Advisory

What to investigate next

Suggestions derived from the evidence — not actions taken. DemandEcho has not contacted anyone.

Join the conversation in r/lemmy — 8 matching posts found.
Advisory — investigate, do not assume
Reply to “Cart items meta data (custom fields) does not appear on Abandoned carts” — someone is actively looking for a fix like yours.
Advisory — investigate, do not assume
Validate the “Customers want abandoned carts that feel timely and personal” angle first — it appears in 29 conversations.
Advisory — investigate, do not assume
Read “Show HN: Luminal – A truly statically typed Python notebook” closely — it reads as a pain point, not a feature request.
Advisory — investigate, do not assume

Evidence

The conversations behind this report

Every row is a real, publicly observable item — a community post, conversation, or article about the idea. The explorer defaults to Customer signals; use the voice filter to inspect developer/technical or ambiguous discussion separately, so demand review stays honest.

Default view: customer signals

Showing 10 of 47 matching evidence rows

Trust

What is observed, analyzed, and advised

The report separates what DemandEcho actually observed from what the system inferred — and never hides partial coverage.

Observed

Real public conversations, collected and normalized with their original sources preserved.

Analyzed

Intent labels, relevance, themes and the score — derived from the evidence by the model or the deterministic fallback.

Advisory

Next steps are suggestions for you to investigate. DemandEcho never contacts anyone.

10 public platforms were searched; 7 returned usable evidence. The customer-demand view includes only the 20 relevant communities that produced eligible customer signals.

hacker-news
github
stackoverflow
gitlab
stackexchange
lemmy
news

Partial coverage does not invalidate the evidence that was collected — but it means the demand picture may be incomplete. Treat quiet communities cautiously.

This report used consistent evidence rules to classify the collected conversations. Every signal, count, and theme remains tied to the original public source.

Analysis version · 2.2-competitive-stableVersion 2.0-customer-first builds conclusions from customer signals only; developer/technical discussion is excluded from demand unless the idea targets a technical audience. Historical reports keep the version they were built with.

The observed evidence is always stored exactly as collected. Labels and themes are the only parts the model (or the fallback) contributes, and they are validated against the persisted evidence before they appear here.

Now picture your idea here

Run research when you are ready, and the finished report will be built from real public conversations.

Start Research See pricing