Medtech sales
Territory plans with named targets and volumes — not heat maps.
A shaded county map tells a rep nothing about Monday morning. RepVector returns the clinicians and facilities themselves, ranked by the procedure and spend volume that predicts whether a call is worth making.
Questions you can answer
Rank clinicians by procedure volume, specialty, and HCPCS code, with allowed and paid amounts.
Which facilities in my territory have the financial capacity for capital equipment?
Who in this territory is already receiving payments from my competitors?
Build a Q3 call list for the Phoenix metro, ranked, with a reason per name.
The datasets behind it
Selected at runtime against your question, each with a stated reason. Anything a source cannot cover at your geography is reported as a gap, not filled in.
Physician utilization by provider and service
Named clinicians with service counts, HCPCS-level detail, beneficiary counts, and allowed and paid amounts — the closest public proxy to procedure volume that exists.
HCRIS hospital cost reports
Facility-level beds, total costs, margin, and uncompensated care. The capital-equipment qualification question answered from the hospital's own filing.
Open Payments
Industry transfers of value to named clinicians — who your competitors are already paying, in what amounts, for what.
Medicare Part B services and DRG discharges
Service-line and inpatient volume to size the procedure base of a facility or metro before you assign a rep to it.
NPPES and CMS Provider of Services
The denominator: every enrolled clinician and facility in the territory, so the ranked list is drawn from the full population rather than the ones already in your CRM.
Find → Enrich → Understand → Score
Four stages between your question and a call list you can defend.
01
Find
Ask in plain language. The AI reads the intent, resolves the place you named down to county and FIPS, and pulls the datasets that actually apply from the public catalog — no query syntax, no source picking. What comes back is the whole target universe for that market, not a sample.
02
Enrich
Each target is taken past the registry row. RepVector reads the organisation's own website for services, locations, phone numbers, and named decision-makers, and attaches the page every fact came from. If a fact isn't published, it says "not published" — it is never inferred.
03
Understand
Capabilities are lined up against competing providers to expose gaps and whitespace, and each target is re-read over time so you can see what changed — a new location, a new service line, a decision-maker who left — with the evidence URL beside it.
04
Score
Everything folds into one 0–100 fit score per name: published volume, payer mix, opportunity gap, web completeness, whether a named contact was found, and how recently the target changed. The breakdown is shown on the row, not hidden behind a black box.
What you get
What lands in the dashboard
One run produces the whole picture for a market — the names, the people at them, the gaps worth calling about, and the proof behind every figure.
A ranked call list with people on it
Organisation, address, phone, and — where the site publishes one — a named decision-maker with their title and the page it was read from.
Tiers with a stated reason per name
Tier 1, 2 and 3 targets, each carrying one line explaining why it ranked there and the source row that line came from.
A 0–100 fit score you can open
Volume, payer mix, opportunity gap, web completeness, named contact and change recency, each shown as its own contribution.
Charts that drill down
Volume, payer mix, capacity and population widgets — click any figure to see the rows, geography, vintage and query behind it.
A competitive matrix and a one-pager
Your targets against competing providers by capability, with whitespace highlighted, plus a cited one-page positioning summary as PDF.
A market plan, sequenced
A week-by-week territory plan built from the ranked list — who to see first, in what order, and the evidence behind the sequence.
Change alerts on the market
Saved markets are re-checked, so you get a digest of the providers, capabilities and locations that moved since your last run.
Exports that keep the receipts
CSV, Excel and a full PDF build report, each carrying query, parameters, geography, vintage, capture time and citation URL into whatever CRM you run.
Then hand it off
Export the ranked territory as CSV or JSON with the query parameters, vintage, and reasoning in the file header, then load it into whatever CRM the team already runs. Quota assignment and quarterly reviews read off the same denominator.
RepVector doesn't log calls or manage pipeline. Here's where we stop.
Every number on the page traces to a published CMS file with a stated year. That matters the first time a rep pushes back on their territory assignment — the ranking is arguable, but the volumes underneath it are not.
Build the list for one county and see whether the names are right.
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