Conquest intelligence for RT manufacturers: see which facilities buy your competitors

The territory blind spot

An RT accessory sales rep knows which accounts they’re in. They usually know which competitor sold the last order in those accounts — because they asked, or because an invoice came up in a conversation. What they almost never know is where competing products are being purchased in accounts they don’t have a relationship with: the 200-bed community hospital three states over, the freestanding outpatient center that doesn’t have a dedicated procurement director, the federally affiliated facility where purchasing is centralized and a field rep hasn’t been seen in two years.

This is the structural gap in direct-sales-only commercial motions. Territory planning for most RT accessory manufacturers is built on relationships, inbound leads, conference contacts, and the intuition of reps who have worked a region for years. It is a motion that excels at deepening existing account relationships and falls down in one specific place: systematically identifying accounts where a competitor is demonstrably winning business that your company has never bid on.

The commercial term for those accounts is conquest targets — facilities where a competitor has observable purchasing activity and your company has no relationship. Identifying them at scale, prioritized by recency and volume, is the problem conquest intelligence is built to solve.

The territory blind spot, defined precisely: a direct-sales-only commercial motion gives an RT accessories manufacturer strong visibility into the accounts it already serves and limited to zero visibility into accounts buying from a competitor that the manufacturer has never reached. The deficit is not a function of rep effort — it is structural. A rep cannot prioritize a prospect they cannot see. Conquest intelligence built on observed public-sector spend makes those accounts visible: which facilities, in which states, are purchasing from the competitors in your mapping set, ranked by observed volume and recency. That ranked list is what converts territory intuition into a prioritized call list.

What “observed public-sector spend” means — and what it doesn’t

The intelligence corpus underlying the conquest report is built on publicly observable purchasing activity from US healthcare and institutional facilities — purchase signals that appear in public-sector procurement data, not in buyer-submitted invoices or private commercial transaction records. The distinction matters for two reasons: scope and integrity.

On scope: public-sector purchasing activity includes hospitals, cancer centers, academic medical centers, and federally affiliated RT facilities that participate in public procurement systems. This is a large and representative slice of the US RT accessories market — particularly the institutional and government-affiliated segments where GPO and contract purchasing is most prevalent.

On integrity: privately submitted buyer invoices are structurally excluded from what manufacturers see. The platform’s data architecture enforces this at the database layer — every row in the competitive-intel corpus carries a flag that distinguishes public-sector observations from buyer-upload-sourced data, and manufacturer-facing intelligence reads only the public-sector layer. A facility that uploaded an invoice to the buyer-side analyzer never appears in any manufacturer’s conquest report by name, spend, or observation count.

What the corpus shows is demand, not negotiated commercial pricing: which facilities, in which states, are purchasing competing products and at what observed volume. It does not show private contract prices. No single-number competitor price points are published anywhere in the conquest report.

What “observed public-sector spend” means for an RT accessories manufacturer:the intelligence reflects publicly observable purchasing activity at US healthcare facilities — hospitals, cancer centers, academic medical centers, and federally affiliated RT departments — not private commercial invoices or internally submitted buyer data. The buyer-upload exclusion is enforced at the database layer: privately submitted invoices are structurally separated from the manufacturer-facing corpus, so a hospital that used the buyer-side analyzer is never reflected in any manufacturer’s conquest report by name or spend. What the corpus surfaces is purchase signals — which facilities are buying from which competitor brands, ranked by observed volume. It is a demand map, not a pricing benchmark.

The engine underneath: equivalence mapping that compounds

Raw purchase observations are the floor, not the product. What turns an observation into a conquest signal is the cross-vendor equivalence engine: a curated map of which products across the RT accessory market are clinically interchangeable — thermoplastic masks to thermoplastic masks, SBRT immobilization to SBRT immobilization, QA arrays to QA arrays. Every equivalence class in the map is confirmed by human curation before it drives anything; the engine never fuzzy-matches your catalog against a competitor’s. When your conquest report says a facility buys a competitor product in a category you serve, that statement rides on a confirmed equivalence, not a keyword overlap.

This is also why the picture compounds. OncoSource is not a data vendor selling a static file — it is the intelligence layer of a transaction platform where RT buyers analyze quotes, compare clinically equivalent options, and purchase. Every new vendor catalog mapped into the equivalence engine and every new observation that enters the corpus makes the market picture denser: more categories covered, more facilities visible, fresher recency on the signals you act on. Public procurement sources refresh on their own cadence — typically weeks to months — and the platform states that plainly; what compounds continuously is the mapped, curated layer on top and the breadth of the market it covers.

Why the equivalence engine is the moat, not the data file:anyone can buy public procurement data. The work that makes it commercially usable — resolving free-text line descriptions to real products, mapping those products into confirmed cross-vendor equivalence classes, and scoping the result to one manufacturer’s competitor set — is the engine, and it compounds with every catalog and observation added to the platform. A manufacturer’s conquest report gets sharper over time without the manufacturer doing anything, because the map underneath it keeps growing. And the trust boundary holds throughout: buyer-submitted private invoices are structurally excluded from every manufacturer-facing deliverable.

Facility-level competitor purchase signals

The core layer of the conquest report is a ranked list of facilities with observable purchasing activity for the competitors in your mapping set. For each observation, the report shows the facility name, the state, the competitor product category, and the observed volume and recency — ranked from highest-signal to lowest across your full competitor set.

This is the layer that maps directly onto territory planning. It does not tell you “your competitors are strong in the Northeast” — a directional claim your reps already have an intuition about. It tells you that a specific set of facilities in a specific set of states had observable purchasing activity for products in your competitor mapping set in the past 90 days, ranked by volume. The rep assigned to that territory can filter the list to their states, sort by recency, and identify which of those facilities they have an existing relationship with — and, more importantly, which they don’t.

The facilities with no existing relationship and high observed competitor volume are the conquest priority list. That is the actionable output: not a market-share estimate, but a specific set of named institutions where a competitor is winning business and your team has never competed.

What the facility-level purchase signals surface: for each competitor brand in your mapping set, the conquest report lists the facilities with observable purchasing activity — name, state, observed volume, and recency — ranked from highest signal to lowest. The commercial application is direct: a rep filters the list to their territory, identifies which high-signal facilities they already serve (deepen) versus which have no existing relationship (conquest priority). The accounts with the largest observed competitor volume and no existing relationship are the highest-value outbound targets — the ones where a competitor has demonstrably earned the business, and your company has not yet competed. This layer converts a market-share intuition into a specific, ranked, workable call list.

Demand-ranked catalog gaps

The second layer of the conquest report is distinct from the target-account list and answers a different question. Catalog gaps are competitor products that buyers are demonstrably purchasing — with observable public-sector demand — but that have no equivalent in your product catalog.

The gaps are ranked by observed demand: volume, facility count, and recency. A gap at the top of the list is a competitor product that many facilities are buying frequently, with no equivalent offering from your company available to those buyers. A gap at the bottom of the list is a niche SKU with a small observed footprint.

For a VP of Commercial Operations or a head of product, this layer is more useful than the target-account list as a portfolio prioritization tool. The question it answers is not “who do I call first?” but “what should we build, source, or add to the catalog next?” — grounded in actual observed purchasing behavior rather than sales team intuition about what buyers want.

Catalog gaps as a portfolio signal: demand-ranked catalog gaps are competitor products with observable public-sector purchasing demand and no equivalent in your catalog — ranked by volume, facility count, and recency of observed activity. The highest-ranked gaps represent the largest observed demand pools your catalog does not currently address. For commercial ops and product leadership, this layer answers a question the target-account list does not: not which facilities to call, but which product categories and SKU gaps are causing the most competitive loss in the observed market. That is the data input to a portfolio expansion or partnership conversation grounded in actual purchasing behavior rather than competitive intuition.

From report to pipeline: the Monday territory meeting

The conquest report and the target-account CSV are designed to fit into an existing commercial workflow, not to replace it. The intended use is straightforward: a commercial leader — VP of Sales or Regional Sales Director — imports the CSV into their CRM or territory planning tool, filters by territory, and layers it against the existing account list.

The accounts already in the CRM that also appear in the conquest target list are accounts where the team knows there is a competitor relationship and can plan accordingly. The accounts on the conquest list that do not appear in the CRM at all are net-new prospects with observable competitor purchasing activity — and those are the accounts worth discussing in a Monday territory review. The rep knows there is documented demand for the product category. They know which competitor brand is observed. They know the approximate volume rank relative to other facilities in the territory.

That is a materially different starting point than a cold prospecting list or a territory map drawn from conference attendee data. The commercial team is not guessing that there might be a buying opportunity — they are working from evidence that a purchasing relationship with a competitor already exists, and they are deciding how to enter the conversation.

The Monday territory meeting use case: import the conquest CSV, filter by territory, and compare against the existing CRM account list. The overlap — accounts already in the CRM that also appear on the conquest target list — tells you where the team knows about a competitor relationship. The gap — conquest-target accounts not in the CRM — tells you where the team has never competed but competitor purchasing is observable. Those gap accounts are the highest-priority net-new outbound targets for the period. The rep enters each call with two pieces of context an unassisted cold prospect list cannot provide: documented evidence that the product category is actively purchased at this facility, and a volume rank that tells them how significant the observed purchasing activity is relative to the territory.

The new-observation digest: fresh signals, honestly delivered

The branded conquest report is a monthly deliverable. Between monthly drops, entitled manufacturer partners receive a new-observation digest: an email summary of fresh competitor purchase signals that entered the corpus since the previous digest — new facilities with first-observed activity, or facilities with materially increased purchase volume in the most recent window. The platform checks weekly, and the digest only sends when there is genuinely something new in your competitor set. An empty week produces no email — by design. A digest in your inbox always means fresh signal, never a re-dressed snapshot.

The digest is scoped to your competitor set only and carries the same framing rules as the report: observed public-sector spend, facility-level signals, no source names, no single-number price points. It is designed to be read in under five minutes — a concise set of new data points the commercial team can act on before the next full report cycle.

For a commercial team with a fast outbound cadence, the digest means that a net-new facility with high observed competitor purchasing activity can be on a rep’s call list within days of the observation entering the corpus — rather than waiting for the next monthly report to surface it. Territory intelligence operates on a rolling view of market activity rather than a 30-day snapshot.

The digest as a velocity layer:the monthly conquest report is the baseline — a full-picture view of facility-level competitor activity across your mapping set. The new-observation digest adds a velocity layer: fresh signals — new facilities or materially increased competitor purchasing volume — delivered between report cycles so the commercial team is not waiting 30 days to act on a new market observation. Both deliverables are scoped to your competitor set only, carry the same observed-public-sector-spend framing, and require no manual query or dashboard access — they arrive in the relevant stakeholder’s inbox on the platform’s delivery schedule. The commercial team has a rolling view of where competitor purchasing is happening in their market, not a static snapshot.

Request a sample conquest report for your category

OncoSource produces a sample conquest report for a small number of manufacturer partners at a time — scoped to their actual competitor set and product mapping, delivered as a branded PDF with the facility-level signals, demand-ranked gap analysis, and mapping coverage relevant to their category. A discovery conversation covers your product lines and competitor set, what a conquest report would look like for your specific category, and what the full entitled intelligence product includes.

The conversation is 30 minutes, commercial, and specific. No demo theater — it is an operator-to-operator conversation about your category, your competitors, and what observed public-sector purchasing signals look like for both.

Frequently asked questions

The questions manufacturer VPs of Sales and Commercial Ops leads most often ask about the conquest-intelligence product. Each answer is self-contained.

OncoSource is an AI-powered procurement and market-intelligence platform for US radiation oncology. All intelligence claims on this page reflect the live conquest-intelligence product: observed public-sector spend only, no buyer-submitted invoice data, competitor brands in the entitled supplier’s own mapping set only, no savings claims, no single-number competitor price points.

Published July 6, 2026.