The short answer
- check_circleEcommerce price trackers such as Prisync and Price2Spy monitor public list prices, so they cannot see the negotiated contract prices, rebates and discounts where a B2B distributor's margin actually leaks.
- check_circleB2B pricing intelligence works on your own transaction data: invoice lines with list price, net price, cost, customer, product and rep, plus off-invoice items such as rebates and freight.
- check_circleMid-market distributors fall into a gap between scraping tools at roughly $100-$400 a month and enterprise price-optimization suites that are quote-only and typically priced as large annual contracts.
- check_circleA trustworthy pricing analysis computes every figure with deterministic queries and shows the query behind it; language models should explain findings, not do the arithmetic.
- check_circleA focused pilot on one dataset can start from Solyio's Build tier at $6,900, while a multi-tenant platform with several analysis agents and role-based access is a larger engagement quoted to scope.
Two different products share one name
"Pricing intelligence" means two unrelated things. For online retailers it means scraping competitors' public prices. For B2B distributors it means analyzing your own realized transaction prices to find where negotiated deals, discounts and rebates are eroding margin. Buying the first when you need the second is the most common mistake in this category.
| Retail price monitoring | B2B transaction pricing analysis | |
|---|---|---|
| Core question | What are competitors charging today? | What are we actually netting, per customer and product? |
| Data source | Competitor websites and marketplaces | Your ERP, invoices, rebate and CRM exports |
| Price visibility | Public list prices | Private, negotiated contract prices |
| Typical output | Price change alerts, repricing rules | Margin leakage reports, discount outliers, win/loss patterns |
| Typical buyer | Ecommerce and marketplace sellers | Distributors, manufacturers, wholesalers |
Why scraping tools break when pricing is contractual
Scraping tools break for distributors because the prices that matter are not public. Your competitors' contract prices for a key account never appear on a website, and neither do yours. A tool that watches list prices is measuring a number your customers do not pay.
- Contract prices are private. Negotiated pricing lives in agreements and ERP price lists, not product pages.
- Catalogs do not match. Distributor SKUs, pack sizes and private labels rarely map cleanly to a competitor's listing.
- The leak is internal. Most margin loss comes from your own discounts, exceptions and rebates — a scraper cannot see any of it.
- Price is not the whole deal. Freight terms, payment terms and minimum order quantities change the real price and are invisible externally.
2026 comparison: scrapers, enterprise suites and custom builds
Distributors are choosing between three kinds of product: inexpensive monitoring tools built for ecommerce, enterprise price-optimization suites built for large manufacturers, and a custom build on their own data. Each fits a different company size and problem.
| Option | Built for | Pricing model | Sees contract prices? | Best fit |
|---|---|---|---|---|
| Prisync | Ecommerce competitor price tracking | Published SaaS tiers, roughly $100-$400/month | No | Online sellers watching public prices |
| Price2Spy | Retail and marketplace monitoring | Published SaaS tiers | No | Retailers tracking many competitor listings |
| Competera | Retail pricing optimization | Quote-based | Partly — own retail data | Mid-to-large retailers |
| Vendavo, PROS, Zilliant | B2B price optimization and management | Quote-based enterprise contracts | Yes | Large manufacturers and distributors with pricing teams |
| Conga and CPQ platforms | Quoting, contracts and approvals | Quote-based | Yes, at quote time | Controlling discounts as deals are priced |
| Custom build on your data | Your specific leakage questions | Fixed-price project plus hosting | Yes | Mid-market distributors with a clear, specific problem |
The mid-market gap
A distributor doing tens or low hundreds of millions in revenue is usually too complex for a $99-a-month scraper and too small to justify an enterprise pricing suite, its implementation project, and the pricing team needed to run it. That gap is where most mid-market distributors end up in spreadsheets.
Spreadsheets are not the problem in themselves. The problem is that one analyst's workbook cannot be rerun reliably every month, audited by finance, or shared with sales leaders without someone breaking a formula.
Where B2B margin actually leaks
Margin leaks in four places, and each one can be surfaced with a specific query against transaction data. Pricing practitioners often describe this as the pocket price waterfall: the steps between list price and what you actually keep.
| Leak | What it looks like | Query that surfaces it |
|---|---|---|
| Below-cost and near-cost sales | Lines sold under or barely above landed cost | Net price minus cost per invoice line, flagged below a margin floor |
| Discount outliers | Similar customers getting very different prices for the same product | Discount distribution by product and customer segment; flag the outer tail |
| Off-invoice erosion | Rebates, free freight and extended terms that never show on the invoice | Allocate rebates, freight and terms cost back to the customer and product |
| Stale contract prices | Agreements not updated after cost increases | Contract price age versus cost change date per SKU |
Discount waterfall analysis
A discount waterfall starts at list price and subtracts every concession — invoice discount, promotional discount, rebate, freight, payment terms — until it reaches pocket price. Standard sales reports stop at invoice price, so everything below that line is commonly invisible to the people setting prices.
Start at list
Take list price per SKU at the time of each sale, not today's list price.
Subtract on-invoice concessions
Contract and promotional discounts that appear on the invoice.
Allocate off-invoice costs
Rebates, free freight, early-payment discounts and returns, allocated back to customer and product.
Compare pocket price to cost
The result shows which customers and products are actually profitable — often a different list from the one by revenue.
Win/loss intelligence without a CRM cleanup project
You can learn why deals are won or lost on price from raw quote and order exports, without first fixing CRM hygiene. Match quotes to subsequent orders; quotes with no order within a set window are treated as lost. Then compare quoted price, discount depth and product mix between won and lost groups.
This is imperfect — some losses have nothing to do with price — but it is usually enough to show whether discounting is actually winning deals or just giving margin away on deals you would have won anyway.
Reference architecture: specialized agents with an audit trail
The architecture that works splits the job into specialized analyses that each run deterministic queries, then uses a language model only to explain and prioritize the results. That is the pattern behind PriceSmurf, a pricing intelligence platform we built.
PriceSmurf runs five specialized agents — Data Quality, Margin Leakage, Opportunity Detection, Value Analysis and Win/Loss — against uploaded Excel or CSV sales data. It is a multi-tenant SaaS with subdomain-based workspaces, owner/admin/member/viewer roles and subscription billing, deployed on Google Cloud Run. Each agent produces a report with charts, sortable tables, the SQL audit queries behind the numbers, and PDF export.
- 1Ingest and validate. A data quality pass checks for missing costs, negative quantities, duplicate lines and unmapped SKUs before any analysis runs.
- 2Compute deterministically. Each analysis is a set of queries whose results are reproducible.
- 3Explain with a model. The language model summarizes findings, ranks them by revenue impact and suggests next actions.
- 4Show the work. Every figure links to the query that produced it.
- 5Isolate tenants. Each workspace's data is separated and access is role-controlled.
Why every number needs a visible query
Pricing findings get acted on only if finance and sales leaders trust them, and they trust numbers they can check. A report that says "$X of margin leakage" with no way to trace it will be argued with in the first meeting and ignored by the second.
Data requirements checklist
Before any build starts, you need an invoice-line export with enough fields to calculate real margin. Missing cost data is the single most common blocker.
- Invoice line: date, invoice number, customer ID, SKU, quantity, unit net price.
- List price per SKU at the time of sale, not only today's price list.
- Unit cost or landed cost per line.
- Customer attributes: segment, region, assigned rep, contract or price list ID.
- Off-invoice items: rebates, freight charged versus absorbed, payment terms, credits and returns.
- For win/loss: quote exports with quote date, quoted price and a customer ID that matches orders.
Adjacent example: financial modeling that sales teams trust
The same principle — transparent, checkable numbers — drove Upgrr, a financial analysis platform we built for sales consultants in the printing equipment industry. It compares the lifetime cost of keeping versus upgrading equipment using Net Present Value modeling and produces client-ready PDF reports. Its case study reports more than 100 consultants generating over 2,000 comparison reports. Different problem, same lesson: people act on numbers they can explain to their own customer.
Build cost and timeline
A focused pilot — one dataset, one or two analyses, a report your pricing lead can use — is the right starting point and can begin from our Build tier at $6,900. A multi-tenant platform with several agents, roles, billing and scheduled refreshes is a larger engagement quoted to scope.
| Phase | Scope | Typical timeline | Pricing |
|---|---|---|---|
| Data review | Assess exports, confirm cost data, define leakage questions | 1-2 weeks | Part of scoping |
| Pilot | One dataset, margin leakage and discount outlier analysis, audited reports | 3-6 weeks | From $6,900 (Build tier) |
| Production tool | Scheduled data refresh, several analyses, roles, PDF exports | 6-12 weeks | Quoted to scope |
| Multi-tenant platform | Workspaces per business unit or customer, billing, admin | 3-6 months | Scale tier, quoted to scope |
Security: keeping deal data out of public models
Pricing analysis can run without your deal data being used to train public models. Use business or API tiers from model providers with training disabled by default, a signed data processing agreement, the shortest available retention, and a processing region that matches your contracts.
Beyond the model provider: send the model aggregated results rather than raw customer-level rows where possible, keep role-based access so reps see only their accounts, and log every report generation. Our cyber security practice reviews this setup before launch on any build handling commercial data.
Build vs buy: five questions
Five questions settle most build-versus-buy decisions in this category in a few minutes.
- 1Is your problem public competitor prices or your own realized prices? Public prices: buy a monitoring tool. Your own: keep reading.
- 2Do you have a pricing team of several people and an enterprise budget? If yes, evaluate the enterprise suites.
- 3Can you export invoice lines with cost? If not, fix that first — no product will work without it.
- 4Is the question specific? "Find below-cost sales and discount outliers" suits a focused build. "Optimize all our pricing" suits a suite and a consultant.
- 5Will people act on the output monthly? If nobody owns the follow-up, neither buying nor building will pay back.
Frequently asked questions
Why don't tools like Prisync or Price2Spy work for B2B distributors?add
They monitor public prices on competitor websites and marketplaces. Distributors mostly sell at negotiated contract prices that are never published, and their biggest margin losses come from their own discounts, rebates and exceptions — none of which a price scraper can see.
What does pricing intelligence software cost in 2026?add
Retail monitoring tools publish plans that commonly run roughly $100-$400 a month. Enterprise B2B price-optimization suites are quote-only and typically sold as large annual contracts with an implementation project. A focused custom build on your own data can start from a fixed-price pilot, with Solyio's Build tier starting at $6,900.
How would we know how much margin is leaking?add
Run a pocket price waterfall on invoice-line data: start at list price, subtract on-invoice discounts, allocate rebates, freight and payment terms, and compare the result to cost. The gap between invoice price and pocket price, and the customers and products with the widest gaps, is where to look first.
Do we need clean CRM data before we can start?add
No. Margin leakage analysis runs on ERP invoice data, which is usually cleaner than CRM data. Win/loss analysis can start from quote and order exports matched on customer ID, with a data quality check flagging problems rather than blocking the project.
Can pricing analysis run without sending our deal data to a public LLM?add
Yes. Use business or API model tiers that do not train on your data, sign a data processing agreement, minimize retention, and send the model aggregated results rather than raw customer rows. For stricter requirements, models can run in a specific cloud region or on your own infrastructure.
How long before we see results?add
A pilot focused on one dataset typically produces its first audited findings within three to six weeks, most of which is spent validating cost data and agreeing definitions. Production tools with scheduled refreshes take longer.
The engineers and architects who build Solyio's client platforms — web, mobile, cloud, and AI automation. Everything here comes out of shipped client work.