What you're actually looking at
A guided tour of the dashboard, top to bottom — what each view shows and why it matters, before you connect anything. Looking for one specific capability? Browse all features →
Gross Revenue
$1.3M
+10.6% vs prior
Prior: $1.18M
Net Revenue
$1.27M
+10.4% vs prior
Prior: $1.15M
Contribution Margin
$546K
+9.6% vs prior
Prior: $498K
Ad Spend
$118K
−5.2% vs prior
Prior: $125K
Gross Revenue Trend
Last 30 days · Current vs Prior Period
Current — solid · Prior — dashed
Channel Distribution
Current period
Amazon67.0%
$850K
Shopify33.0%
$418K
fees + FX + COGS netted outvs prior period
Illustrative dashboard preview — not live data.
Your morning, right now
Shopify $9,838
Meta Ads $7,038
Amazon $8,520
GA4 ~$8,100
Spreadsheet ?
Five tabs, five numbers, none of them your actual profit.
With Sellrics
Net profit, last 30 days
$15,200
▲ 8.9% vs prior — after fees, FX, COGS, and ad spend
One number, reconciled to your bank account.
01
The one number — Revenue P&L
- What you see
- Gross revenue stepped down to contribution margin and net profit in a single waterfall, across every channel you have connected, with week-over-week and month-over-month growth.
- Why it matters
- Shopify Analytics and Amazon Seller Central each show revenue, and neither subtracts the other side or your ad spend. This is the number that reconciles to what actually landed in your bank account.
02
Channel comparison
- What you see
- Amazon versus Shopify side by side — sessions, conversion rate, average order value, revenue, and Amazon buy-box tracking — over the same date range.
- Why it matters
- The channel with the most revenue is often not the one with the most margin. Seeing traffic quality and order economics per channel tells you where the next dollar of effort or ad spend should go.
03
Product & SKU margin
- What you see
- Every SKU ranked by contribution margin, with its return rate, units, revenue, and a SKU-by-channel matrix showing where each product sells and at what margin.
- Why it matters
- A topline bestseller can be a near-breakeven product once returns and marketplace fees are netted out. Ranking by margin, not revenue, tells you what to reorder, what to promote, and what to quietly discontinue.
04
Returns & fees
- What you see
- Returns broken down by reason and by SKU, the margin impact of those returns, and a fee breakdown that separates payment fees, referral fees, fulfilment fees, and FX cost.
- Why it matters
- Returns and fees are where thin-margin categories actually lose money. Knowing that one SKU or one reason code drives most of it turns a vague "returns are high" into a fix.
05
Inventory signals
- What you see
- Per-SKU reorder and overstock flags based on recent sales velocity, plus an at-risk list of SKUs that will stock out before a typical resupply window, with the dollar impact of each.
- Why it matters
- Stocking out of a profitable SKU during a peak is lost margin you never see in a report. Overstock on a slow mover is cash frozen on a shelf. Both show up here before they hurt.
06
Marketing & attribution
- What you see
- Ad spend from Meta, Google, and GA4 tied to the SKUs that actually converted — ROAS, CAC, and MER per campaign, a creative and keyword breakdown, and a per-channel health audit.
- Why it matters
- Platform-reported ROAS double-counts and flatters. Tying spend to real orders and to fee-aware margin tells you which campaigns fund the business and which just move the topline.
07
Forecasting & what-if
- What you see
- Revenue and per-SKU projections with a confidence range, plus a what-if simulator that holds everything fixed except the levers you name (ad budget, price, return rate).
- What the numbers mean
- A forecast projects a metric forward from its own history and seasonality; the band is the plausible range, not a guarantee. A what-if re-runs the model with one input changed so you can see the effect on cash and margin before you commit.
- Why it matters
- Reorder quantities, ad budgets, and cash planning are all bets on next month. Seeing the range — and testing a change before making it — replaces a gut number with a defensible one.
08
Live alerts & the signal engine
- What you see
- A feed of anomaly-detection alerts plus a prescriptive signal engine (a 10-rule set) that surfaces specific actions — not just "revenue is down" but which channel, SKU, or campaign moved and what to do about it.
- Why it matters
- Most founders find problems days late, by noticing a bank balance. Alerts move that to the same day, with enough context to act instead of investigate.
09
Ask your data
- What you see
- A suite of AI tools exposed over MCP that answer questions against your real numbers — including root-cause analysis for a drop and the forecasts and what-ifs from the view above, in plain language.
- Why it matters
- The questions that matter rarely fit a fixed dashboard tile. Asking "why did margin drop last week" or "what happens to cash if I cut Meta 20%" keeps analysis at the speed of the decision.
10
Every number has a completeness flag
- What you see
- A small flag on each metric that tells you when an input is missing or estimated — COGS not loaded for a SKU, fees estimated rather than settled, an ad platform not connected.
- What the numbers mean
- A complete metric uses only measured inputs. An incomplete one is still shown, but marked, so you know the margin figure is directional until you finish connecting or loading data.
- Why it matters
- A confidently wrong number is worse than a labelled-incomplete one. Sellrics would rather show you "incomplete" than a figure that will not match your accountant.
Want the full list in one place? See every view →