No trend data yet — upload a second period to compare.
Customer priority matrix
Leakage as % of annual spend vs spend — bubble size = leakage $; click to drill down
My team
Team revenue breakdown
Sorted by leakage, highest first
Rep coaching matrix
Y axis = achieved vs floor %; above 0% = pricing above floor; click a rep to drill down
Leakage breakdown
Leakage by product
Products with recoverable leakage, sorted highest first
Price scatter
Each dot = one customer. Line = 40th-pct floor. Columns = spend tier.
Full tables
Full customer data
Click any row to see a product-by-product breakdown
Customer▲▼
State▲▼
Class▲▼
Rep▲▼
Annual spend▲▼
Status▲▼
Net leakage▲▼
Abs. leakage▲▼
Renewal date▲▼
Contract length▲▼
Last price rise▲▼
Floor prices
Cluster × product benchmarks — adjust floors and targets as needed
Floor prices load when you switch to this view.
Rep performance
Click any row to see a customer breakdown
Rep▲▼
Accounts▲▼
Revenue on book▲▼
Leakage $▲▼
% Below floor▲▼
% At/above target▲▼
How it works
The maths behind your floors, targets, and leakage numbers.
1 — Peer clusters
When you upload your data, you choose which customer attributes to use as dimensions — for example, State, Industry, or Spend Band.
RightPrice takes the cartesian product of all dimension values to create peer clusters.
Each customer is assigned to exactly one cluster based on their attribute values.
Example: if you configure State (NSW / VIC / QLD) and Job type (Commercial / Residential), you get 6 clusters.
Each cluster's pricing is computed independently, so a NSW Commercial customer is only benchmarked against other NSW Commercial customers.
2 — Floor and target prices
For each cluster × product combination, RightPrice collects all historical unit prices paid.
It then computes two percentile benchmarks:
Floor — never sell below
40th percentile
60% of your peers already achieve this price or better. Selling below it means you're in the bottom 40%.
Stretch target
60th percentile
40% of your peers already achieve this price or better. Hitting it puts a rep in the top tier.
Both lines are visible on the peer scatter chart in the rep price-lookup view.
3 — Leakage
Leakage is the recoverable margin lost when a customer is priced below the floor:
leakage = max(0, floor − avg_price) × qty
Leakage is zero for any customer priced at or above the floor — even if they're below the stretch target.
🔒 Full methodology in the app
Available in the full app
4 — Aggregation fallback
A percentile is only meaningful with enough data points.
If a cluster × product combination has fewer than 10 transactions, RightPrice automatically
aggregates up to a broader grouping — for example, dropping one dimension — until it finds at least 10 data points.
When aggregation is used, a small badge on the pricing table indicates the floor came from a broader peer group.
🔒 Full methodology in the app
Available in the full app
My book
Your accounts sorted by recoverable leakage — biggest opportunities first. Click any row to see the product breakdown.
Price lookup
Pick the customer's profile and product. RightPrice returns the floor and target your peers are already achieving.
Floor · never sell below
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Stretch target
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Where peers price this product
Each dot = one customer. Red line = floor (40th pct). Green dashed = stretch target.
Upload client data
CSV or Excel with transaction data. Set up column mapping and clusters below, then drop your file to run analysis.
📂
Drop file here, or click to browse
CSV or Excel (.xlsx) · Set up column mapping below before first upload
Aligning data…
0%
Customers
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Transactions
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Products
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Total leakage
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Step 1 — Map your columns
Drop a file above first to detect columns, then assign each to a RightPrice field. Required: customer_id, product_id, price, qty.
Drop a CSV or Excel file above to detect columns.
Step 2 — Define customer clusters
Toggle dimensions on to use them. Select multiple value chips then "Merge selected" to group them into one bucket. Clusters = every combination across active dimensions.
Period analysis
Transaction date column detected — choose how to group periods for the leakage trend.
Group by:
Cluster preview
Users
Manage who can access the dashboard.
Add user
Companies
Each company has its own data, managers, and reps. Upload data per company from the Upload tab.