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Blog›E-commerce

Know Which Products Are Actually Making You Money

Revenue tells you what sold. Product mix analysis tells you which SKUs are worth promoting, which are quietly cannibalising margins, and which products customers almost always buy together.

Try AnalityQa AI AI free →See live examples
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The problem

  • →High-revenue SKUs often have thin margins — but without a profitability-per-SKU view, resources get allocated to the wrong products.
  • →New product launches erode sales from existing lines without anyone noticing the cannibalization until the damage is done.
  • →Bundle and cross-sell opportunities sit hidden in order data — most teams never have time to mine frequently-bought-together patterns.
  • →Margin mix shifts over time as discounts, promotions, and cost changes hit different SKUs unevenly, but there is no systematic way to track it.

Why the usual approach breaks down

Shopify does not surface SKU-level profitability

Shopify reports show revenue and units sold per product but do not calculate gross margin, contribution, or return-adjusted profit. Getting to those numbers requires joining your order data with a separate cost file — a step most teams skip because there is no automated way to do it inside Shopify.

Cannibalization is invisible without a cross-SKU view

Detecting that a new SKU is pulling sales from an existing one requires comparing weekly sales trends across related products simultaneously — a multi-series analysis that Shopify's built-in reports cannot produce without exporting and rebuilding in Excel.

Frequently-bought-together analysis requires SQL set operations

Finding product pairs that appear together in the same order involves a self-join on the order line-items table — the kind of SQL that most e-commerce teams cannot write and that takes an analyst an afternoon to get right for the first time.

Margin mix calculations break when discounts are applied unevenly

When a promotion applies a percentage discount to selected SKUs, the effective margin per SKU changes for that period. Tracking how margin mix shifts across months requires weighting revenue and cost together in a way that Excel pivots consistently get wrong when discounts are recorded as separate line items.

How AnalityQa AI AI solves it

Upload your data — or connect it live — and ask in plain English.

01

Upload your order line-items and cost data in one session

Drop your Shopify order export alongside a cost CSV — or simply include a cost column in your product file — and AnalityQa AI AI joins them automatically. You can immediately ask profitability questions at the SKU, category, or brand level without writing a single formula.

02

Get a profitability quadrant across your entire catalogue

Ask 'Plot all SKUs by gross margin percentage versus units sold' and AnalityQa AI AI builds a scatter chart that places every SKU into a high-margin/high-volume, high-margin/low-volume, low-margin/high-volume, or low-margin/low-volume quadrant — giving you an immediate view of where to focus.

03

Surface frequently-bought-together pairs automatically

Type 'Which product pairs appear together most often in the same order?' and the system runs the co-occurrence analysis on your order data without requiring you to understand the underlying self-join. Results include pair frequency and the share of orders containing each pair.

04

Detect cannibalization with side-by-side trend charts

Ask 'Show me weekly unit sales for SKU A and SKU B over the last 6 months' and overlay the two lines. If a new product launch coincides with a drop in a related SKU, the chart makes the relationship visible immediately — no manual comparison required.

05

Track how margin mix shifts across months and promotions

Ask 'How has average gross margin across all orders changed month over month this year?' and AnalityQa AI AI weights each order by its actual line-item margins, accounting for discounts in your data. You can filter to specific categories or campaigns to isolate the effect of a promotion.

You askedGenerated in 4.2s

"Show me a profitability quadrant — gross margin percentage versus units sold — for all SKUs last quarter."

Total

12,840+9.2%

Average

324+4.1%

Top segment

38%+2pp

Scatter chart: SKU profitability quadrant — margin % vs. units sold

Last 12 mo

Table: frequently bought-together pairs — co-occurrence count and order share

Line chart: weekly unit sales by top 5 SKUs — 6-month trend

A dashboard built in AnalityQa AI — from question to chart, no SQL.

Real examples

Paste your data. Ask. Ship.

You

Show me a profitability quadrant — gross margin percentage versus units sold — for all SKUs last quarter.

AI

AnalityQa AI AI calculates gross margin per SKU using your revenue and cost columns, then plots each SKU on a scatter chart with margin on the Y axis and units sold on the X axis, divided into four quadrants at the median of each dimension.

Scatter chart: SKU profitability quadrant — margin % vs. units sold
You

Which product pairs are most frequently bought together in the same order?

AI

The system performs a co-occurrence analysis on your order line-items, counting how many distinct orders contain each product pair, then returns the top pairs ranked by co-occurrence frequency and as a share of all orders.

Table: frequently bought-together pairs — co-occurrence count and order share
You

Plot weekly unit sales for my top 5 revenue SKUs over the last 6 months to check for cannibalization.

AI

AnalityQa AI AI identifies your top 5 SKUs by total revenue in the period, aggregates weekly unit sales for each, and overlays them on a multi-line chart so you can visually assess whether one SKU's growth correlates with a decline in another.

Line chart: weekly unit sales by top 5 SKUs — 6-month trend
You

How has our weighted average gross margin changed month over month this year, and which category is dragging it down?

AI

The system computes order-weighted gross margin for each month, then breaks the contribution to margin by product category so you can see which category's mix shift is responsible for any decline.

Line chart: weighted avg gross margin by month + stacked bar: margin contribution by category
You

Which SKUs have declining revenue but strong margins — candidates to promote more aggressively?

AI

AnalityQa AI AI identifies SKUs where revenue has trended down over the last three months but gross margin percentage remains above the catalogue median, returning them as a ranked list with revenue trend and margin figures.

Table: high-margin, declining-revenue SKUs — promotion candidates

What teams get out of it

✓Teams reallocate ad spend toward high-margin, high-volume SKUs within days of their first product mix analysis.
✓Cannibalization from a new product launch is caught within the first two weeks rather than after a full quarter of lost margin.
✓Bundle recommendations derived from frequently-bought-together data increase average order value without requiring engineering work.
✓Monthly margin-mix reviews replace ad-hoc Excel audits, giving leadership a consistent view of portfolio health.

Frequently asked questions

Does AnalityQa AI AI work with Shopify and WooCommerce exports?+

Yes. You can upload the standard CSV exports from both platforms. AnalityQa AI AI infers column types automatically, so whether your export labels a column 'Lineitem price' (Shopify) or 'order_total' (WooCommerce), the system maps it correctly without manual configuration.

Do I need to include cost data, or can I work with revenue only?+

You can work with revenue-only data — the analysis will focus on volume, revenue share, and trend. To get gross margin and profitability quadrant views, you need a cost column in your product file or a separate cost CSV. AnalityQa AI AI will prompt you if a cost column is needed for a specific query.

Can I analyse product mix across multiple stores or sales channels?+

Yes. Upload separate exports for each store or channel in the same session. You can query across all of them combined or filter to a specific source within the conversation — for example, 'Show me the profitability quadrant for the UK store only.'

How does AnalityQa AI AI handle variants — do they roll up to the parent product or stay separate?+

By default, analysis is at the variant (SKU) level, which gives the most precise view. If you want to roll up to the parent product, say so in your query — for example, 'Group all variants into their parent product for this analysis' — and the system aggregates accordingly.

Is my product and order data stored securely?+

Data is encrypted in transit and at rest and isolated per tenant. You can delete your uploaded data at any time from account settings.

Do I need data or SQL skills to run a product mix analysis?+

No. Every analysis — profitability quadrant, frequently-bought-together, cannibalization detection — is triggered by plain-English questions. If you want to refine a result, follow up in the same conversation and the query updates automatically.

What plan covers product mix analysis with multiple files?+

Multi-file sessions — for example, joining your order export with a cost file — require the Pro plan. The Pro plan also adds dashboard pinning so you can share a live product-mix dashboard with your team. The Starter plan handles single-file, single-session analysis.

Related guides

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E-commerce Sales Analysis Without the Spreadsheet Chaos

E-commerce

Stop Guessing on Inventory: Know What to Reorder and When

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