01
Retail performance overview
One view of how trading is going across stores, brands and categories, with the figures that matter for the week or the month in one place.
Prism · BI & Data Analytics
Qgenx PRISM - Business Intelligence & Data Analytics Tool
Answers to trading questions, from the data you already record.
Prism turns imported and recorded product, store, sales, returns and stock data into pivots, comparisons and merchandise views, so the question is answered in one place. It analyses data you have recorded; it is not a live checkout or a purchasing system.
Standalone · GST-aware where relevant · Pilot before rollout
01 · Import data
02 · Pivot
03 · Compare
04 · Find the gaps
05 · Download
Rows48,210
Stores12
Styles640
StatusData loaded
48,210Rows
- 09:04sales_oct.csvLoaded
- 10:16stock_oct.csvLoaded
- 11:28returns_oct.csvLoaded
Data loaded · illustrative
Brands6
Stores12
PeriodOct
StatusSlice
6Brands
- 09:04Brand A · Store 04₹4.2L
- 10:16Brand A · Store 07₹3.6L
- 11:28Brand B · Store 04₹2.1L
Slice · illustrative
Sales+8%
Margin−1.2 pt
Markdown+2 pt
StatusIllustrative figures
+8%Sales
- 09:04MenswearUp
- 10:16FootwearFlat
- 11:28AccessoriesDown
Illustrative figures · illustrative
Sell-through62%
Cover41d
Broken runs5
StatusGaps
62%Sell-through
- 09:04M · 3 storesRefill
- 10:16L · healthyOK
- 11:28XL · slowReview
Gaps · illustrative
Reports14
Datasets6
FormatCSV
StatusExport
14Reports
- 09:04Stock-to-saleDownload
- 10:16Margin by styleDownload
- 11:28Return ageingDownload
Export · illustrative
Capabilities
What Prism does today.
Each capability is traced to the working product. The panel on the right shows a real label from the screen where it appears.
02
Pivots and period comparisons
Slice the data by store, brand, category or any attribute, then compare one period with another. The comparison shows what moved and by how much.
03
Sales performance analysis
See where sales come from and where they are not coming from, by store, product group and channel, with the same slices available in every view.
04
Inventory health
Stock-to-sale and stock-cover views show which products and groups are moving, and which hold more stock than they sell. Use them to decide what to reorder and what to hold back.
05
Product and assortment performance
Compare style, colour, size, fabric and season performance, so assortment decisions for the next season rest on recorded sales rather than memory.
06
Margin and markdown
See how margin moved between two periods and what markdowns did to it. Margin and markdown sit in one view, so price decisions are read together.
07
Merchandise ranking
Rank styles and compare internal groups by the measures you choose, so strong and slow lines are visible without building a ranking by hand.
08
Size availability and refilling
Spot broken size runs, where one size is out of stock while others still sell, and review refilling by store, so replenishment goes where it is needed.
09
Productivity and space efficiency
Compare how well each store turns its space into sales, so store-level questions use the same data as the rest of the trading view.
10
Ecommerce sales by channel
Sales and channel reporting for online trading, with each marketplace or channel shown separately. Ecommerce data is reported on its own and is not reconciled with retail automatically.
11
Return risk and ageing
Find which products and channels carry return risk, and how old open return items are, so the team can act on them early. The view is by product and by channel.
12
Imports and downloads
Load sales, returns and stock data from CSV files, and download each report or the dataset behind it as a file for the team that needs it.
The business problem
Prism removes these problems.
Three operating problems this product is built for. Each one is answered by a capability on this page.
01 Prism
Management cannot compare stores without building spreadsheets
Pivots and period comparisons across stores and categories.
02 Prism
Size runs break and nobody notices until sales drop
Size availability and refilling review.
03 Prism
Return risk and ageing are invisible
Ecommerce return-risk and ageing views.
The workflow
From first step to finished record.
Five steps, in the order the work happens.
- 01Import data
Load product, store, sales, returns and stock data from CSV. Prism reports on what has been recorded.
- 02Pivot
Open a retail pivot and slice by store, brand, category or period.
- 03Compare
Set two periods side by side and see what moved: sales, stock, margin and markdown.
- 04Find the gaps
See stock cover, sell-through and size availability to find what needs refilling or markdown.
- 05Download
Download the report or the dataset behind it for the team that needs it.
Rows48,210
Stores12
Styles640
StatusData loaded
48,210Rows
- 09:04sales_oct.csvLoaded
- 10:16stock_oct.csvLoaded
- 11:28returns_oct.csvLoaded
Data loaded · illustrative
Brands6
Stores12
PeriodOct
StatusSlice
6Brands
- 09:04Brand A · Store 04₹4.2L
- 10:16Brand A · Store 07₹3.6L
- 11:28Brand B · Store 04₹2.1L
Slice · illustrative
Sales+8%
Margin−1.2 pt
Markdown+2 pt
StatusIllustrative figures
+8%Sales
- 09:04MenswearUp
- 10:16FootwearFlat
- 11:28AccessoriesDown
Illustrative figures · illustrative
Sell-through62%
Cover41d
Broken runs5
StatusGaps
62%Sell-through
- 09:04M · 3 storesRefill
- 10:16L · healthyOK
- 11:28XL · slowReview
Gaps · illustrative
Reports14
Datasets6
FormatCSV
StatusExport
14Reports
- 09:04Stock-to-saleDownload
- 10:16Margin by styleDownload
- 11:28Return ageingDownload
Export · illustrative
Who it is for
Five roles, what changes for each.
Each role has its own job in the product and a clear gain from it.
Merchandising analyst
Pivots sales by store, brand and period.
Comparisons in one click.Buyer
Reads stock cover and sell-through.
Slow lines seen early.Ecommerce manager
Checks channel sales and return risk.
Return risk by product and channel.Finance partner
Reviews margin and markdown together.
Markdown effect visible.Founder
Opens the overview each Monday.
Trading in one screen.Good to know
What we do not claim
Prism analyses data that has been imported or recorded. It is not a live checkout, a purchasing engine or a fulfilment system, and it does not reconcile retail and ecommerce data automatically.
We would rather you hear this in the first conversation than find it later.
Typical first pilot
One team, one location, one month
- A real month imported
- Totals compared with your own reports
- Pivots adjusted to match how you slice
- Downloads reviewed by the analyst
Scenarios
Prism in practice.
Seven situations this product is built for.
Compare two months in a click
Month comparisons took a day of pivots. A period comparison now sits in one view.
- Period comparison
- Any slice
- Download the data
See what is not selling
Slow styles were found at season end. Stock-to-sale and cover views show them while there is still time.
- Stock cover
- Sell-through
- Ranking
Broken size runs noticed
Stores sold out of middle sizes first. The size availability review points out the gaps.
- Size gaps
- Refilling review
- By store
Return risk by channel
Return rates were an overall number. Prism shows return risk and ageing by product and channel.
- Return risk
- Ageing
- Channel view
Margin and markdown together
Margin and discount were reviewed separately. Both sit in one view.
- Margin movement
- Markdown effect
- By category
Monday in one screen
The weekly review was assembled by message. The overview shows trading in one place.
- Overview
- Store ranking
- Fewer spreadsheets
Which styles to refill this week
Refill decisions were made from memory. The size review and the stock-to-sale view list the styles and sizes that need action.
- Refill list
- Stock-to-sale
- Size gaps
Where it fits
Six industries that use it.
Retail ChainsManagement cannot compare stores without building spreadsheetsFashion, Apparel & FootwearSize runs break and nobody notices until sales dropCosmetics & LifestyleSlow-moving lines are found too lateEcommerce & Marketplace SellersReturn risk and ageing are invisibleWholesale & TradingStock cover across trade accounts.Supermarkets & GroceryStore sales and space efficiency.
Prism questions
Quick answers.
One open at a time. The full list has 35 questions.
What is Prism?
Prism is QGenx’s retail and ecommerce reporting product: pivots, comparisons and merchandise views built on data you record or import.
Who is Prism for?
Analysts, merchandisers, channel managers and owners who review trading performance, especially in apparel.
Is Prism real-time?
It analyses data that has been imported or recorded. It is not a live checkout system.
Does Prism replace Power BI or Excel?
It is purpose-built for retail and ecommerce questions, so common views are ready. It does not claim to replace general tools for every use.
Does it need POS?
No. It works from imported data, and can use data from any source in the right format.
Does it make forecasts?
No. It reports on what has happened, with comparisons and gaps.
Is it only for fashion?
Style, colour, size, fabric and season make it strongest for apparel, but the pivots work for other retail.
What can I pivot on?
Store, brand, category, period and other attributes, with comparisons between periods.
What does inventory health show?
Stock-to-sale and cover for products and groups.
How does the margin and markdown view work?
It shows margin movement and the impact of markdowns together.
QGenx demo
See Prism on your own workflow.
Tell us about your current workflow, look at the product closest to the problem, and choose a 30-minute slot. A working walkthrough, not a slide deck.
- 30 minutes
- Your workflow, not ours
- No obligation