TrendSeer / Commerce Research Desk

TrendSeerFounder Briefs

Product risk briefs for small ecommerce stores before they spend on ads or inventory.

Launch offer

Manual first batch
$10 starter brief24-hour manual reviewEvidence checksStop-loss rules

Trend Capture: quality inputs, updated weekly

Capture commerce signals before you spend on ads or inventory.

TrendSeer turns one store context, competitor references, public URLs, and a first-test budget into a traceable trend card. It is built for small Shopify operators who need a bounded research decision, not an overconfident prediction.

Start capture

Source-first capture

Turn explicit URLs, marketplace snippets, manual notes, and competitor references into traceable inputs before any recommendation appears.

Evidence-capped decision

Weak or blocked sources cap the action language. The page can say test, watch, or avoid, but it will not manufacture confidence.

Founder brief workflow

Capture becomes the first step of a $10 starter brief: trend card, evidence gaps, first-test suggestion, and stop-loss boundary.

Capture Intake

Submit one product decision

Use real merchant constraints. The output is only as strong as the sources you provide.

Capture Status

Waiting for capture

pending

Submit the intake to inspect source lanes and recommendation caps.

Source Lanes

Amazon / marketplace actor

apify_marketplace_actor

pending

Submit merchant context to inspect source readiness.

Items: 0

No trend card yet. Run capture to see real source-lane status, recommendation caps, and next evidence actions.

Next Step

Continue into source planning

Capture is not the final truth. Continue into source planning before turning a trend card into a client brief.

Open source plan

Strategic methods

A restrained system for product-risk evidence.

Collect only explicit sources supplied by the merchant or approved lanes.

Separate source availability from market proof so blocked collection remains visible.

Route promising captures into a human-reviewed $10 starter brief instead of self-serve automation.