ProfitLensConsulting
Get started1,999 USD999 USD

How it works

No step waits for a consultant. The system guides you from raw data to traceable recommendations.

  1. Step 1

    01Upload data

    Upload transaction data as CSV, text or Excel using ordinary exports. Files are stored encrypted in Microsoft Azure in Sweden, within the EU.

  2. Step 2

    02Confirm columns

    The system suggests what each column means. You review and confirm the mapping.

  3. Step 3

    03Quality control

    Data is checked automatically. Serious errors stop the run; smaller deviations are documented.

  4. Step 4

    04Deterministic analysis

    The engine calculates findings and potential. Every figure is traceable.

  5. Step 5

    05AI interviews

    Send personal links to key people. Intelligent chatbots gather business context while analysis runs. Unlike a booked meeting, respondents can pause at any point and continue later using the same link - no calendars to align.

  6. Step 6

    06Report and results chat

    Findings and interviews become a report, dashboard, presentation and workshop pack. An AI chatbot explains results and discusses initiatives.

What you need

  • Transaction data at order-line or invoice level.
  • Someone who can confirm what the columns mean.
  • Optional: people who can answer AI interviews about the business.

Fixed product, fixed price

The standard analysis costs 999 USD excluding tax. A workshop pack is included. A consultant-led workshop or executive presentation can be added.

Is your data good enough?

The most common blocker is not your data – it almost always suffices. What is needed is a raw, line-level export from your ERP. In short:

Real names are not required

If customer or product names feel sensitive, feel free to mask them – replace them with your own codes such as "Customer A" or "Product 12". The only requirement is that the masking is consistent: the same customer must always carry the same masked name, throughout the file and in every sheet. Otherwise the rows cannot be linked and the right conclusions cannot be drawn. Just tell us in the mapping step which columns are masked.

  • One row per item sold – invoice or order lines, not a pivot table or summary.
  • One full year – a calendar year or the rolling last 12 months – so a year of seasonality and pricing effects is visible.
  • Each row shows when, to whom, which product, how many and at what price.
  • Unit cost if available – without it we show price but not margin.
  • Raw data straight from the system beats processed files. Columns may be named anything – we help you map them.
  • Excel or CSV, up to 100 MB per file. Multiple sheets are fine. Larger datasets can be split into several files, e.g. one year per file, and merged with Extend history.
Show the detailed data request

Feel free to send the request to your controller or system administrator – it specifies exactly how the file should look.

DATA REQUEST – input for pricing analysis (ProfitLens)

1. SCOPE
- Transaction data at line level: each row should correspond to a single invoice line or order line (line item), not a whole order or a summary. An order containing five different items is delivered as five separate rows.
- Period: one full year – a calendar year or the rolling last 12 months up to the last closed month. Two years enable year-over-year comparison, and four complete quarters give rolling twelve-month values. Feel free to update every quarter: new files can extend the history or replace a previous period, and every analysis is saved as a version so progress can be tracked over time.
- All sales within the unit to be analysed. If anything is excluded (entity, country, channel, internal sales) – state what and why.
- For larger groups: analyse one coherent business unit, division or market per analysis, with consistent currency and pricing logic.
- No aggregation, no pivot tables, no subtotals or section headers.

2. FIELDS PER ROW
- Date (REQUIRED) – Transaction date (YYYY-MM-DD). Alternatively year and month as two separate columns.
- Customer number (REQUIRED) – Unique key per customer, consistent throughout the file.
- Customer name (optional) – The customer's name.
- Item number (REQUIRED) – Unique key per product, consistent throughout the file.
- Product name (optional) – The product's name.
- Quantity (REQUIRED) – Units sold on the line. Negative value for credit notes/returns.
- Unit price (REQUIRED) – Net price after discount, in the file's currency. State if it is gross.
- Unit cost (recommended) – Standard cost, purchase price or full cost – state which.
- Amount (optional) – Line total (quantity × price).
- Currency (recommended) – Currency code per row, or state that the whole file is in one currency.
- Discount (optional) – As amount or percent – state which. Back-end rebates in their own column.
- List price (optional) – Gross price before discount, if available.
- Customer segment (recommended) – E.g. industry, size or channel. May be delivered as a separate sheet.
- Sales rep (recommended) – Responsible salesperson or sales code.

3. FORMAT
- Excel (.xlsx) or CSV (UTF-8). Max 100 MB per file. Larger datasets are split by period (e.g. one year per file); each file is uploaded separately and merged with the previous one via Extend history. For datasets over 100,000 rows, CSV is recommended first – it cuts file size substantially and handles hundreds of thousands of rows without hitting the file limit.
- Exactly one header row at the top of each sheet. No merged cells, no empty columns between fields.
- Column names may be your system's own – we map them in the next step.
- Dates as real dates (YYYY-MM-DD). If only year and month exist, deliver them as two separate columns.
- Numbers as numbers, not text. No thousands separators, no currency symbols in cells. One consistent decimal separator.
- Negative amounts with a minus sign, not parentheses.
- Credit lines and returns must be included and flagged (own column or negative quantity).

4. PRICE AND COST
- State clearly whether the price is gross (list price) or net after discount. Never mix in the same column.
- If both list and net price exist: deliver both as separate columns.
- Discount as amount or percent – state which. Back-end rebates and annual bonuses in their own columns if they exist.
- Unit cost: state which cost it is (standard cost, latest purchase price, average full cost) and when it was last updated.
- Currency: a column with currency code, or confirmation that the whole file is in one currency.

5. KEYS AND MASTER DATA
- Customer number and item number must be the same keys throughout the file.
- Real names are not required. Customers and products may be masked (e.g. "Customer A"), but the masking must be consistent: the same customer/product must always carry the same masked name throughout the file and in all sheets. State which columns are masked.
- If customer segment, region, channel or sales rep lives in a separate register – deliver it as its own sheet with the customer number as key.
- If cost or invoiced outcome sits in another system – deliver it as its own sheet and state which key links it to the transactions.

6. OTHER
- The better the data, the sharper the analysis — but the file does not need cleaning. Empty fields, duplicates and odd values are handled and reported in our quality control.
- Feel free to add a short note about known data limitations (system migration, incomplete period, reused item numbers).