Why should I pay when eBay sold is free?

Time is money. Checking eBay sold takes 2-3 minutes per item: searching, scrolling through results, mentally calculating fees and shipping. At a garage sale with 50 potential items, that's 2+ hours of standing around researching. We do it in 30 seconds with instant profit calculations, platform fee breakdowns, and red flags. Same 50 items? 25 minutes total. Plus everything is saved, tracked, and organized. The paid tiers cost less than one decent flip - and you'll find that flip faster.

How is this different from checking eBay sold or asking AI myself?

Three things: speed, accuracy, and tracking. Asking ChatGPT or similar gives you generic guesses without real market data. We combine instant AI identification with actual sales data, then automatically calculate platform fees, shipping estimates, and net ROI. Plus, every analysis is saved to your account so you can track what you've researched, compare items over time, and move items directly to your Flip Tracker.

Where does the price data come from?

We aggregate pricing data from multiple sources including completed sales, active listings, and historical market trends. The AI identifies your item from the photo, cross-references comparable items across platforms, and synthesizes this data to provide accurate market values with confidence levels based on how many data points we found.

What can I analyze? Does it work on any item?

Anything you can photograph. Electronics, clothing, collectibles, toys, tools, furniture: if people buy it on eBay, we can analyze it. Works with photos you take, screenshots from FB Marketplace, OfferUp, Craigslist, or any other source. The AI is trained on millions of product images.

How accurate is the net profit calculation?

We use current platform fee rates (eBay 13.25%, Mercari 10%, Poshmark 20%, FB Marketplace 0%). Shipping estimates are based on typical costs for the item category and size. Your actual results may vary slightly based on your negotiated shipping rates or promotional fee discounts, but you'll be within a few dollars.

What's the Flip Tracker?

Built-in inventory management. When you decide to BUY an item, add it to your tracker in one click. Track what you paid, where you're listing it, and record the sale when it sells. Get real P&L numbers, ROI by category, average days to sell, and exportable reports for taxes.

Do I need to download an app?

No app required. Underpriced is a web app that works in any browser (Chrome, Safari, Firefox) on desktop or mobile. Just go to underpriced.app and you're ready to go. Add it to your home screen for quick access while sourcing.

What if the AI makes a mistake?

That's why we include Sold Comps links with every analysis. One click takes you directly to eBay Sold listings, Poshmark, Mercari, and Terapeak so you can verify the price yourself in seconds. See exactly what similar items actually sold for. We show you confidence levels and data points too — low confidence means fewer comps were found, so hit those links and double-check. The AI does the heavy lifting, but you always have the tools to verify.

Can I use this at thrift stores or garage sales?

Absolutely, that's what it's built for. You need cell service or WiFi for the AI analysis (it runs in the cloud). Most places have signal. If you're in a dead zone, snap photos and analyze them when you get signal, or save them for later.

Is there a free plan?

Yes! Get 5 free analyses with all AI features included — Sold Comps, Due Diligence, Fake Check, Negotiator, Help Me Sell, and FlipExpert AI. No credit card required. It's enough to test the tool and see if it fits your workflow. When you're ready to scale, paid plans start at just $3/month.

High Views, No Sales? Reseller Diagnosis Framework (2026): Fix Conversion Bottlenecks Without Blind Discounts

A listing with high views and no sale is not a visibility problem.

It is a conversion problem.

That distinction matters because the wrong fix is expensive. Most sellers react by dropping price immediately. Sometimes that helps; often it just reduces margin on inventory that still won’t convert.

This guide gives you a systematic way to diagnose what is actually blocking the sale.

Understand the Pattern Before You Change Anything

When a listing gets traffic but doesn’t close, one of these is usually true:

Price friction — buyer interest exists, but value-per-dollar feels weak.
Trust friction — buyers hesitate because condition/risk is unclear.
Offer friction — buyer wants flexibility, but your offer path is weak.
Platform-fit friction — item has demand, but demand isn’t strongest on this platform.

You need to identify which one is dominant before editing.

If your listing gets almost no impressions at all, use eBay Listing Has No Views? Fix Playbook (2026).

Diagnostic Ladder: The 4-Step Conversion Check

Step 1: Price-position check

Use sold comps in matching condition. Do not compare your “very good” item to “new with tags” outcomes.

Use:

Step 2: Trust clarity check

Ask:

Are defects explicitly shown and described?
Are photos detailed enough to reduce uncertainty?
Is shipping speed/handling clearly stated?

Step 3: Offer-path check

Ask:

Is Best Offer enabled where it should be?
Are your thresholds realistic for listing age?
Are counters consistent and fast?

Use:

Step 4: Platform-fit check

Sometimes item-market fit is fine, but channel-market fit is weak.

Check cross-platform economics and expected velocity:

Platform Fee Comparison Tool

Conversion Friction Type A: Price Friction

Price friction happens when buyers see your listing but perceive better value elsewhere.

Signs

steady views, low watchers
watchers exist, no offers
messages that imply “too high” without saying it directly

Fix

Use a 3-price structure:

Anchor price (what you list at)
Target close price (realistic win zone)
Hard floor (never go below)

Calculate floor from net economics, not gut feel:

Floor = COGS + fees + shipping/supplies + risk reserve + minimum profit

Use Break-Even Price Calculator to avoid fake margin.

Conversion Friction Type B: Trust Friction

If buyers can’t confidently assess condition/risk, they delay or leave.

Common trust blockers

blurry lead photo
missing flaw documentation
vague condition language (“good used”)
unclear shipping timelines
no size/dim/spec specificity

Fix sequence

Replace lead photo with strongest angle and true color accuracy.
Add 2–4 defect photos where relevant.
Rewrite condition section with precise language.
Clarify handling and packaging expectations.

For specifics depth, see eBay Item Specifics Optimization Guide (2026).

Conversion Friction Type C: Offer Friction

Some buyers will not buy without negotiation room, especially in non-commodity categories.

Signs

watchers increase, but direct buys stay low
occasional low offers, weak close rate
price edits alone don’t move conversion

Fix

Implement structured offer thresholds:

auto-decline below floor band
auto-accept near target close zone
one or two counter steps in mid-band

See full framework: eBay Best Offer Strategy for Resellers (2026).

Conversion Friction Type D: Platform-Fit Friction

A listing can be objectively good and still underperform on one channel.

Example pattern

item gets views on Platform A but weak conversion
same item type sells faster on Platform B with different buyer profile

Fix

Before discounting aggressively, run channel economics:

fee structure by platform
shipping model differences
expected return risk by category/platform

Use Platform Fee Comparison Tool.

Numeric Example 1: High Views, No Sales (Price + Trust Combined)

Starting state

Item: used camera lens

Metrics after 7 days:

views: 186
watchers: 7
offers: 0
messages: 3 (all asked about fungus/haze clarity)

Problem diagnosis

Price was slightly above comp median
Trust friction high due to unclear optical condition photos

Action

Added backlit glass photos and close-ups of mount/body wear
Rewrote condition section with explicit no-fungus/no-haze note and sample-shot mention
Adjusted list from 279.99 to 264.99

Result pattern (next 5 days)

views: +102
watchers: +5
offers: 2
close at 249.00

Net preserved because change addressed trust first, then measured price alignment.

Numeric Example 2: Offer Friction vs Blind Markdown

Starting state

Item: branded outerwear

After 6 days:

views: 142
watchers: 12
no sale

Seller option A (blind markdown):

drop from 89.99 to 69.99
immediate sale possible, but margin compression severe

Seller option B (structured offer path):

keep list at 89.99
auto-accept 78+
counter band 66–77
auto-decline below 60

Outcome in scenario:

offer at 68 countered to 74, accepted

Difference in realized gross vs blind markdown: $4.01 At volume, that compounds materially.

7-Day Conversion Repair Sprint

Day 1: classify friction type

Pick primary bottleneck: price, trust, offer, platform fit.

Day 2: trust optimization

photo pass
specifics pass
condition language rewrite

Day 3: pricing architecture

floor calc
target close zone
anchor reset if needed

Day 4: offer logic implementation

thresholds and counter ladder

Day 5: relist/refresh where needed

title refinement
category check

Day 6: platform fit check

compare net and expected velocity across channels

Day 7: review

Track:

views-to-watchers
watchers-to-offers
offers-to-close
net vs floor

If one metric improves but close rate still stalls, your dominant friction diagnosis is likely wrong—reclassify and rerun.

What to Stop Doing Immediately

Dropping price before checking trust and specifics.
Comparing your used-condition listing against best-condition comps.
Treating watchers as committed buyers.
Running one static offer policy across all categories.
Ignoring return-risk reserve when accepting lower offers.

Operational SOP for Teams

If multiple people touch listings, standardize this mini-playbook:

Analyst role: friction diagnosis + comp review
Editor role: listing quality updates (photos/specifics/description)
Pricing role: threshold updates and offer ladder rules
Reviewer role: 7-day metric review and close-out decision

This prevents random, contradictory edits that hide cause/effect.

Tools and Next Action

Run this stack in order:

Then apply the framework to your top 15 high-view, no-sale listings this week.

If lowballs are your dominant issue, continue with:

Too Many Lowball Offers? Reseller Strategy (2026)

The win condition is not just “more sales.” It is more profitable closes with lower decision fatigue.