In small and mid-sized wholesale, purchase price tracking usually works like this: the latest invoice sits somewhere in the inbox, the one before it is in a "Suppliers" folder, the master table lives in the buyer's Excel file, and the truly current version lives in the buyer's head. While you have five suppliers and a hundred SKUs, this holds up. But once you're dealing with dozens of brands and thousands of SKUs, margin starts getting estimated by feel: "I think we bought this at around eight euros." Let's look at what purchase price tracking looks like when prices are pulled from real documents, history is kept for every supplier, and an abnormal price jump is visible the day the invoice arrives rather than a month later in a report.
Where purchase prices actually live
Ask a buyer where to find the price of a specific item, and the answer is almost always a patchwork. Some prices are in the latest invoices in the inbox. Some are in price lists the supplier sends once a quarter, and it's anyone's guess whether the most recent one even arrived. Some are in an Excel file that was compiled by hand once and has been updated on a whim ever since. The rest lives in one particular person's memory.
This setup has three built-in flaws:
- Versions diverge. The spreadsheet says one price, the latest invoice says another, and no one remembers which one is current.
- History never accumulates. A new price list overwrites the old one, and the trend is lost: a year later you can't answer how the cost of an item changed over time.
- Knowledge doesn't transfer. When the buyer leaves, the "price database" walks out the door with them.
Note that the data itself never actually disappeared. Every price is recorded in a document sitting in the inbox or on a drive. The problem isn't missing data — it's that no one lines it all up in a single row.
Why tracking purchase prices "by feel" is dangerous
Margin control in trading comes down to exactly this gap: the selling price is known precisely, the purchase price only "roughly." From there, the familiar loss scenarios play out.
- Selling on an outdated cost. The supplier raised prices in a new invoice, but the customer price list wasn't recalculated for a month or two. All that time, some SKUs went out at a smaller markup than planned — and some at a loss.
- An unnoticed drop. The reverse case is rarer but still costs money: the supplier granted a discount or seasonal terms, yet cost is still calculated at the old price — and you lose out to whoever did recalculate.
- A dispute with no evidence. The supplier billed a price higher than agreed. Without history, you have nothing to argue with: "we thought it was cheaper" isn't an argument. With a three-month-old invoice and a specific price in hand, the conversation goes differently.
What these scenarios share is that the losses never look like an event. No one "lost" money on a specific day — margin quietly drifted across dozens of SKUs, and it only shows up in the numbers after the fact. That's exactly why margin control doesn't start with a sales report; it starts with a reliable purchase price for every single item.
Supplier price history: what it looks like in practice
Supplier price history isn't yet another table you have to keep filling in. It's a series of values for each item of each brand: date, price, currency — plus a link to the document the price came from. That last point is essential. A price without a document is an opinion. A price linked to an invoice from a specific date is a fact you can put in front of a supplier — and in front of yourself, when you're figuring out why margin slipped on a group of items.
Once that series exists, the usual purchasing questions turn from a mini-investigation into a single glance:
- how an item's price changed over the past year;
- when the last increase happened and by what percentage;
- what you were paying for an item before the supplier "updated their terms";
- what currency the deliveries came in, and whether the exchange rate is masking the real price trend.
Doing this by hand across thousands of SKUs is impossible — which is exactly why Excel summaries die off. It only starts to make sense when history is collected automatically, from the documents the business already receives every day.
Where the prices come from: documents, not manual entry
HORUVIA approaches the problem from the inbox. Over IMAP, the system parses incoming supplier email: it sorts messages by brand and document type — invoices, price lists, order confirmations, certificates. Items with prices are extracted from invoices and price lists and stored in the supplier's memory. Scans go through OCR; for files that live in folders on a computer rather than in email, there's a desktop agent that hands documents off to the server. We covered how incoming documents are parsed in detail in our article on parsing incoming invoices.
In the flagship case — importing heavy-duty truck parts and running import operations in Kazakhstan, with live document flow across dozens of brands — prices for hundreds of thousands of SKUs have been accumulated this way. No one keyed them in by hand: every price was already in an invoice or price list, and all that was left was to pull it out and tie it to a date and a source document.
What goes into a supplier's memory
Memory isn't just prices. For each supplier, a connected set of data accumulates:
- the documents themselves — invoices, price lists, order confirmations — with dates and types;
- extracted items with prices and currency;
- certificates with their validity periods.
Crucially, every figure stays linked to its source: open an item and you can see which invoice and which date the value came from. Verification takes a minute — no need to dig through six months of correspondence.
A practical test: the price doubled — what is it?
Here's the test that separates living tracking from a dead spreadsheet. In a new invoice, a familiar item costs twice what it did last time. Possible explanations:
- a genuine increase — the supplier really did raise prices;
- a different pack size or unit of measure — a price per package instead of per piece;
- an error in the document — a typo, a shifted line, a mixed-up part number;
- a different currency or changed delivery terms.
Without history, the question usually never even comes up: the invoice gets paid, because "the supplier sent it, so that's what it is." With history, the anomaly is visible immediately: the new price is compared against past values for the same item, a sharp deviation stands out right there during parsing, and an alert about the invoice lands in Telegram. From there a human decides: opens the source linked to the price, checks the neighboring lines, and writes to the supplier if needed — before payment, not after.
The same mechanism works on less dramatic cases too. A gradual climb in several steps across a whole group of items is even harder to spot by eye than a one-off doubling — but against a backdrop of history it reads as a trend you can take to the supplier for negotiation.
There's an important line of responsibility here. HORUVIA doesn't "fix" the price itself and doesn't make payments: from the invoice, deterministic code builds a payment draft — no generative liberties with the numbers — and a human approves it. The system's job is to make sure the question "why double?" gets asked in time.
Comparing supplier prices without a manual roundup
A separate task is comparing supplier prices, when the same item or interchangeable items are sourced from different manufacturers. Usually that comparison gets pulled together on occasion: before a big order, someone exports the price lists, merges them into a table — and a month later it's already out of date.
When price series accumulate continuously for every supplier, the comparison stops being an evening project. From the history you can see:
- which suppliers raised prices over the year and by how much;
- whose purchasing on a given group is steadier;
- where the gap on the same item is wide enough that the terms are worth re-checking or an explanation worth requesting.
An honest caveat: the system doesn't pick the supplier for you. Price isn't the only factor — there's the settlement currency, prepayment, lead times, reliability, the history of the relationship. But a choice grounded in actual price series rather than impressions is a fundamentally different kind of choice.
What changes in ordering and planning
Accumulated history doesn't only serve control. It underpins the order recommendation: HORUVIA calculates a suggestion accounting for seasonality, ABC classification, and current stock on hand — we walked through how that works in our article on seasonal ordering and ABC analysis. When you know the actual price an item was bought at, markup and turnover are calculated from the real purchase, not from an "average by gut feel."
Around that same supplier memory, the other loops run: the deadline engine reminds you ahead of time about expiring certificates and contracts, "Company Pulse" shows shipments by stage, and the task board keeps supplier tasks in one place. Telegram alerts are built in here too: a supplier's offer with a deadline won't sink into a shared folder, and an email left unanswered resurfaces as a reminder. How these pieces come together into the overall setup of a wholesale company is covered in our overview on wholesale automation.
Where to start
Start not with an "implementation project" but with a single inbox and a few key suppliers. Connect your email over IMAP — and the system will begin sorting messages and pulling prices out of recent invoices; you can deepen the history by handing it your archive of past documents. You don't need to change your accounting system to do this: email stays email, no one takes away the Excel you're used to — a layer simply appears alongside it that remembers every price and every document. For getting started there are onboarding presets by segment — import operations, retail, services, HoReCa, logistics — and for those working in 1C, a basic exchange is provided.
The first few weeks give you a simple success criterion: on the next invoice, the system should show you on its own what changed in prices relative to past deliveries. If it did — the tracking is alive.
You can see how supplier memory works on your own documents in a demo — request one on the home page. To estimate how much time your team spends on manually rounding up prices and what would free up after automation, the calculator helps, and answers to common questions about connecting email and data security are collected in the FAQ.