Compare modes and presets
Switch between no compare, previous period, last year and last quarter with fast date presets like 7D, 30D, 90D, YTD and quarter views.
Prev period - YoY - QoQ
marql turns daily trade data into a comparison-ready analytics surface for every location: revenue trends, margin movement, plan versus actual, same-store growth, payment mix and store ranking without exporting to spreadsheets first.
Demo workspace
Sample workspace
Compare modes
Prev period / YoY / QoQ
Planning model
Plan vs actual live
Store scope
8 locations
Sample workspace
Analytics
Period comparison
Revenue vs previous period
Revenue for period
€2.53M
139% of the plan that is loaded
Target
€1.83M
Five of six stores have a plan loaded
Transactions
59,510
Across all stores
Avg Items / Check
2.53
Transaction quality signal
Payment Mix
Total €2.53M
Cash
€567.5k
Card
€1.57M
Online
€392.7k
Inside the Analytics module
The public page mirrors the live account structure: compare modes, time presets, revenue and margin lenses, payment mix, ranking table and AI context tied to the rest of operations.
Switch between no compare, previous period, last year and last quarter with fast date presets like 7D, 30D, 90D, YTD and quarter views.
Prev period - YoY - QoQ
Revenue and margin movement are read as trends, not static totals, so management can see whether the network is accelerating or drifting.
Revenue - margin - LFL
Beyond topline revenue, the screen shows payment mix, transactions and average basket quality to explain how sales composition is changing.
Cash - card - online
Store-level ranking combines revenue, plan, transactions and average check in one export-ready table for weekly review.
Store - plan - avg check
A change in gross margin is split into the four things that can cause it — price, cost of goods, volume and mix — and the four add back to the change exactly, with the products behind each one named. The same decomposition drives the answer when you ask the question in words.
Price - cost - volume - mix
City Center
Westside
North Park
Harbour
Old Town
Riverside
Review workflow
The homepage Analytics card gives a fast trend cue. The full page shows how operators compare periods, benchmark stores, read transaction quality and move into the right follow-up module.
The card signals whether revenue and margin are improving versus the previous period before anyone opens a heavier report.
Management selects previous period, last year or last quarter depending on the review moment and then narrows the time preset.
The ranking table shows who is actually driving the network result, which stores are ahead of plan and where transaction quality is slipping.
From the trend surface, teams move into P&L, Products, Loyalty or marql AI depending on whether the issue is margin, assortment, retention or explanation.
Review lenses
Compare frame, time preset and lens switch together so weekly reviews stay inside one operating screen.
Revenue
Read topline movement, target attainment and transaction count without leaving the analytics surface.
Margin & Losses
Inspect where commercial performance is being compressed before finance closes the month.
Ranking
Benchmark stores against each other and isolate outperformers versus stores that need attention.
P&L
Jump from trend reading into profitability when the question changes from growth to margin quality.
Forecast
Estimate where the current run-rate points before the end of the reporting period.
Connected context
Teams start in Dashboard or Today, use Analytics to understand structural movement, then move into P&L, Products, Loyalty or marql AI to explain and act on the change.
Analytics FAQ
It is an operating analytics layer for multi-location teams. marql focuses on revenue, margin, plan attainment, ranking and store diagnostics that operators need every week. Teams can still export data, but the core review logic already lives in the product.
That is one question, and it is answered as a decomposition rather than an opinion. The change in gross margin is split into a price effect, a cost-of-goods effect, a volume effect and a mix effect, and the four add back to the change exactly — so there is no unexplained remainder to argue about. Each effect names the products behind it, so 'costs' becomes a list of suppliers and SKUs rather than a word. Ask it in plain language and the answer comes from the same decomposition the screen shows.
Yes. The live module supports no comparison, previous period, last year and last quarter, plus quick presets like 7D, 30D, 90D, YTD and quarter views.
Yes. The analytics layer is designed for same-store growth reading, so management can separate network expansion from underlying store performance.
Yes. The live module includes export for store-level ranking tables, while keeping the main comparison and review flow inside the product.
Analytics explains where the network is drifting. P&L shows whether that movement translates into profit pressure, and marql AI reads the same metrics so teams can ask follow-up questions in their own words and jump into the right screen.
We connect a sample of your POS and planning data, then show your first analytics review surface with your own locations, targets and comparison periods.