Home Sales Data · 12-Month Review

Cancellations, not category mix, are what's costing you

9,999 orders across 5 office-furniture categories, 24 Sep 2023 – 23 Sep 2024. This dashboard traces where revenue actually comes from — and where it's leaking.

$2.86MCompleted revenue
$1.44MCancelled order value
33.0%Cancellation rate
78%Of revenue from new customers
Summary · Answer first

One in three orders cancels — evenly, everywhere — while the business leans almost entirely on first-time buyers.

Completed orders brought in $2.86M, but another $1.44M of order value was cancelled — and cancelled orders are, on average, the same size as completed ones ($438 vs $426). This isn't a handful of bad orders; the 33% cancellation rate is nearly identical across every product category, payment method, shipping type and month in the data. At the same time, new customers generate 78% of all revenue — repeat business is thin. Category mix (chairs vs desks vs storage) explains far less of the story than these two structural issues.

33% cancellation rate, uniform across every segment Only 22% of revenue comes from returning customers 2 of 5 categories carry 66% of revenue
01
Revenue over time · Completed orders

Revenue is flat all year — no growth, no collapse

Monthly revenue holds in a narrow $214K–$272K band for the eleven full months on record. There's no seasonal ramp and no downward slide — the trend line alone won't explain the business's problems.

Monthly completed revenue
USD · Sep'23 and Sep'24 are partial calendar months (data starts/ends mid-month)
Highlighted Insights

Jan'24 is the high point at $271.9K; Dec'23 the low point among full months at $214.4K — a swing of just 27%, not a real seasonal pattern.

The Sep'23 and Sep'24 bars look like dips — they're actually partial months (7 and 23 days of data respectively). Don't read them as decline.

Because revenue is stable, the case for action sits in who cancels and who returns — not in chasing a trend that isn't moving.

02
Order status · Where does the 33% show up?

Cancellations aren't a category problem — they're everyone's problem

If cancellations were concentrated in one product, payment method, or month, that would point straight at a fix. They aren't — the rate sits in a tight 30–35% band no matter how you slice it.

Cancellation rate by product category
% of orders cancelled
Cancellation rate by month
% of orders cancelled, all 13 months
Highlighted Insights

Category cancellation rates range only 32.3%–33.4% — a spread of 1.1 points. Whatever is driving cancellations, it isn't specific to chairs, desks, bookshelves or storage cabinets.

Monthly rates range 30.5%–34.7% with no trend up or down — this has been a steady operating condition for the full year, not a one-off event.

Real dollars at stake: cancelled orders carry $1,444,778 of recorded order value — equal to 50% of completed revenue. Cancelled orders average $438 vs $426 for completed ones, so this isn't small orders falling away; it's proportionally-sized business walking out the door.
03
Revenue by category & SKU

Two categories carry 66% of revenue — and one SKU looks broken

Office Chairs and Office Desks lead, which is a normal furniture mix. The more useful finding is a SKU-level data problem sitting inside the "chairs" category.

Revenue share by category
% of completed revenue, 4 core categories
Revenue by SKU
USD, 5 core SKUs (order counts are near-identical, ~1,300–1,380 each)
Highlighted Insights

Office Chair (34.8%) and Office Desk (31.7%) together account for 66% of revenue — Bookshelf and Storage Cabinet split the remaining third fairly evenly.

CHR101 ("Office Chair") has almost the same order count as CHR102 (1,329 vs 1,328) but generated $28.0K vs $965.7K — 97% less. Its recorded unit cost averages $3.90 against a $488 catalogue price, which points to a data entry or export error, not real underperformance. Treat CHR101 revenue as unreliable until the source system is checked.

04
New vs returning customers

The business runs on first-time buyers, not repeat ones

Of 6,128 unique customers, new-customer orders outnumber returning-customer orders more than 3 to 1 — and revenue splits the same way.

Completed revenue: new vs returning customers
USD and % share
Highlighted Insights

New customers generated $2.23M (78%) of completed revenue; returning customers only $624K (22%) — despite returning customers already being proven buyers who should be cheaper to sell to again.

Cancellation rate is identical for new (33.0%) and returning (32.8%) customers — repeat buyers cancel just as often, so loyalty isn't buying you reliability either.

Checked age and gender as possible explanations: per-customer average spend is flat across age bands ($449–$495) and near-identical by gender. Demographics aren't the lever here — retention mechanics are.

Dx
Root-causing the 33% cancellation rate

Confirm → Isolate → Explain

Cancellations are the single biggest lever in this data. Here's how far the data can take us toward a cause.

STEP 1 · CONFIRM

Is 33% really a problem?

"Is this just normal churn?"

3,295 of 9,999 orders (33.0%) are cancelled, carrying $1.44M of order value — equal to half of completed revenue. That's large enough to matter regardless of industry norms.

Confirmed: material and worth investigating.
STEP 2 · ISOLATE

Is it one segment or all of them?

"Is it a bad product, channel, or month?"

Rate by category: 32.3–33.4%. By payment method: 30.7–35.2%. By shipping type: 31.9–33.8%. By month: 30.5–34.7%. Every cut lands in the same narrow band.

Ruled out: product, payment method, shipping type, month, and customer tenure.
STEP 3 · EXPLAIN

So what's actually causing it?

"What's left to check?"

The dataset has no cancellation-reason field (stockout, payment failure, changed mind, delivery issue). With every business dimension ruled out, the cause is most likely operational or systemic — outside what this data can see.

Data gap: reason codes are needed to go further.
Cancellation rate across every segment cut
% cancelled · dashed line = overall rate (33.0%) · every bar sits within ~3 points of it
△ No root cause identified — data gap, not a dead end

Every plausible business explanation (category, payment, shipping, month, customer tenure) has been ruled out — cancellations are evenly spread, which itself is the finding: this points to something structural (checkout flow, inventory promising, fulfillment SLAs) rather than a specific weak product or channel. Recommendation: add a cancellation-reason field at the point of cancellation before the next review cycle.

Summary

Four things to remember

01

Cancellations are structural, not selective

33% cancel rate, uniform across category, payment, shipping and month. $1.44M in order value lost — half of completed revenue.

02

Retention is the quiet second problem

78% of revenue comes from first-time buyers. Returning customers cancel at the same rate as new ones, so tenure isn't building reliability either.

03

Revenue mix is healthy, not a concern

Chairs and desks carry 66% of revenue — normal for a furniture line. Trend is flat, not declining.

04

One data fix is overdue

CHR101's pricing data looks broken (avg cost $3.90 vs $488 catalogue price) — worth checking at the source before it's used in any other report.

Recommended next steps

  1. Add a cancellation-reason field at checkout/cancellation so Step 3 of the diagnosis above can actually be answered next quarter.
  2. Audit the checkout and fulfillment flow — since cancellations aren't tied to any one product or channel, the fix is more likely a shared step (payment confirmation, stock promising, delivery ETA) than a merchandising change.
  3. Build a repeat-purchase play (post-purchase email, loyalty discount, reorder reminder) — returning customers are only 22% of revenue despite being the cheapest segment to sell to.
  4. Fix the CHR101 pricing/cost feed at the source system before this SKU is used in any inventory or margin analysis.