New companion engine · Demand Signals

Find demand before claims do.

The Demand Signals Engine extends the Medigy Opportunity Atlas with a marketing-activation layer. It converts unconventional, compliance-safe data — search intent, environmental triggers, foot traffic, public-health surveillance, retail proxies, and more — into ready-to-run campaigns for hospitals, health systems, physician groups, and the agencies that serve them. Get ahead of demand instead of explaining it after the quarter closes.

Book a 30-min demo See the original Opportunity Atlas

30+

compliant data sources

0–90 days

earlier than claims data

60–90 days

to agency activation

What it is

Signals → cohorts → service lines → campaigns.

Claims data tells you what already happened. The Demand Signals Engine tells you what's about to happen — at the cohort and DMA level, in time to bid, build creative, and send.

Every source is filtered through a single test: can it, directly or indirectly, drive a marketing or advertising action? If not, it's excluded. Every source clears HIPAA, CCPA, and Google/Meta ad-policy rules before it ships.

The output is the same artifact your team already trusts from the Opportunity Atlas: an Opportunity Card — but built around a marketing trigger, not a reimbursement code.

Claims data is the rear-view mirror — accurate, late, and useful only for explaining what already happened. The Demand Signals Engine is the windshield. It tells a staffing firm where to recruit physical therapists before the referrals stack up, and a telehealth provider where to bid flu-season search before the season peaks.

Time-to-signal advantage

How early you see demand vs claims data.

0–7 days

Real-time triggers

AQI, weather, traffic collisions, syndromic surveillance, transit ridership, OpenTable cancellations.

7–30 days

Leading indicators

School absenteeism, search query velocity, OTC sales, appointment-wait scrapes, foot-traffic shifts.

30–90+ days

Strategic signals

Autocomplete drift, podcast trends, WARN filings, RN job postings, construction permits, wearable cohort shifts.

Signal categories

Eleven channels we mine for demand.

Search & intent

Symptom queries, condition exploration, provider discovery.

Social & community

Forum velocity, public posts, engagement around conditions.

Local incident & environmental

Air quality, pollen, accidents, weather-driven exacerbations.

Consumer & retail proxies

OTC sales shifts, grocery SKUs, lifestyle behavior.

Mobility & location (aggregated)

Foot-traffic, transit, DMA-level movement patterns.

Access & availability

Appointment wait times, provider supply, network gaps.

Reviews & patient experience

Yelp/Google velocity, sentiment shifts, complaint themes.

Workplace & employer trends

Job postings, benefit changes, layoff/expansion signals.

Public health datasets

CDC, state DOH, school absenteeism, syndromic surveillance.

Media consumption

Podcast topics, local news, content engagement signals.

Wearable & device aggregates

Anonymized population trends from fitness and health platforms.

The catalog

32 compliant data sources, mapped to a campaign action.

Every source includes its signal type, marketing use, example campaign, accessibility, compliance class, activation path, time advantage vs claims, and an actionability score. Filter to "Contrarian only" to see the unconventional ones agencies rarely use.

Contrarian only

Search & intent

Google Trends — symptom & condition queries by DMA

Signal: Early symptom intent
Use: Build geo-weighted search bidding maps. Allocate paid-search budget to DMAs where condition-related query volume is rising week-over-week.
Example: Cardiology — 4-week lead on 'chest pain at night' query spikes in Phoenix triggers a heart-screening Search + YouTube preroll burst.
Service line: Cardiology, Pulmonology, GI

PublicLow riskDirect activation30–90 days earlier than claimsActionability: High

Compliance note: Aggregated, anonymous query volume. No PHI. Fully aligned with Google Ads policy.

Search & intent

Search autocomplete drift (Google / Bing suggestion APIs)

Contrarian

Signal: Emerging condition vocabulary
Use: Detect novel symptom phrasings (e.g., 'Ozempic face') before they become keyword campaigns. Inform creative copy and SEO content roadmap 6–10 weeks early.
Example: Endocrinology — autocomplete picks up 'GLP-1 muscle loss' two months before query volume; agency ships landing page + Search ad before competitors bid.
Service line: Endocrinology, Weight management, Dermatology

PublicLow riskIndirect activation60–90 days earlierActionability: Medium

Compliance note: Aggregated suggestion data. No user-level signals.

Search & intent

Wikipedia medical pageview velocity

Contrarian

Signal: Public curiosity / post-diagnosis research
Use: Use sustained pageview spikes on condition pages as a leading indicator of diagnosed-but-unsupported cohorts. Layer into programmatic content targeting.
Example: Oncology — sustained 3-week spike on 'triple-negative breast cancer' pageviews in the Carolinas drives a sponsored second-opinion campaign.
Service line: Oncology, Rare disease, Neurology

PublicLow riskIndirect activation30–60 days earlierActionability: Medium

Compliance note: Wikimedia public API. Fully de-identified.

Social & community

Reddit subreddit growth & post velocity

Contrarian

Signal: Active patient cohorts seeking peer guidance
Use: Use subreddit subscriber/post growth as a proxy for cohort size and intensity. Inform Meta interest-targeting seeds and content themes.
Example: Behavioral health — r/ADHD growth in college DMAs feeds a Meta + YouTube creative test for adult ADHD evaluations.
Service line: Behavioral health, Endocrinology, Pain management

PublicLow riskIndirect activation30–60 days earlierActionability: High

Compliance note: Public, aggregated counts. Never target individual users; use community signals to inform creative and seed audiences.

Social & community

Patient-forum & disease-community post velocity (PatientsLikeMe, Inspire, HealthUnlocked)

Signal: Treatment dissatisfaction, switching intent
Use: Detect rising chatter about side effects or treatment failure to time second-opinion campaigns and clinic-acquisition messaging.
Example: Rheumatology — post velocity around biologic side effects spikes; agency runs targeted search + native ads for specialty rheumatology consults.
Service line: Rheumatology, Oncology, Neurology

CommercialModerate riskIndirect activation30–60 days earlierActionability: Medium

Compliance note: Use only aggregated trend data per platform ToS. No scraping of identifiable posts for targeting.

Social & community

TikTok / Instagram hashtag velocity around symptoms & conditions

Contrarian

Signal: Cultural awareness / self-diagnosis trend
Use: Map hashtag growth (#ADHDtok, #PCOS, #longCOVID) by region to tune Meta interest audiences and creative voice.
Example: OB/GYN — #PCOS volume in Atlanta and Houston predicts demand for endocrine-aware women's-health clinics; agency boosts Reels + Search.
Service line: OB/GYN, Behavioral health, Dermatology

CommercialLow riskIndirect activation30–90 days earlierActionability: High

Compliance note: Aggregated, public hashtag metrics. Use insights to inform creative — never to target specific users.

Local incident & environmental

EPA AirNow AQI + NOAA pollen indices

Signal: Acute respiratory exacerbation trigger
Use: Trigger geo-fenced search and display ads when AQI or pollen crosses thresholds. Activate same-day urgent-care and asthma-specialist campaigns.
Example: Pulmonology / Allergy — wildfire smoke in Sacramento triggers within-24hr Google Search 'asthma attack near me' bid increases and Meta carousel ads.
Service line: Pulmonology, ENT/Allergy, Urgent care, Pediatrics

PublicLow riskDirect activation0–7 days earlier (real-time)Actionability: High

Compliance note: Public environmental data. Geo-targeting only — no individual identifiers.

Local incident & environmental

NOAA weather extremes (heat, cold snaps, humidity swings)

Signal: CV/stroke/dehydration exacerbation
Use: Pre-stage cardiology, urgent-care, and hydration messaging in DMAs forecast for heat-dome events 5–7 days out.
Example: Cardiology — Phoenix heat advisory triggers a 7-day pre-positioned Search + Meta heart-symptom-awareness flight.
Service line: Cardiology, Urgent care, Geriatrics

PublicLow riskDirect activation5–14 days lead via forecastActionability: High

Compliance note: NOAA forecasts. Pure geo + temporal targeting.

Local incident & environmental

Municipal 311 complaint feeds (mold, rodents, sewage, noise)

Contrarian

Signal: Environmental health hazard concentration
Use: Identify ZIP-level clusters of housing-related complaints that correlate with asthma, lead exposure, and pediatric ER use. Time community-clinic outreach.
Example: Pediatrics / Pulmonology — rising mold complaints in NYC ZIPs trigger a community-clinic Meta + Spanish-language radio campaign.
Service line: Pediatrics, Pulmonology, Community health

PublicLow riskDirect activation60–90 days earlierActionability: Medium

Compliance note: Open municipal data. ZIP-level aggregation. No PHI.

Local incident & environmental

DOT / city traffic collision feeds

Contrarian

Signal: Trauma & ortho injury intake
Use: Use rolling 30-day collision-count maps to bias geo-fencing for ortho, PT, and accident-injury legal-medical referral campaigns.
Example: Orthopedics / PT — 30-day collision spikes in Houston freeways feed a programmatic display campaign for accident-injury PT clinics.
Service line: Orthopedics, PT/rehab, Pain management, Urgent care

PublicLow riskDirect activation30–60 days earlierActionability: High

Compliance note: Open DOT data. Geo-only.

Consumer & retail proxies

OTC sales scanner data (IRI / NielsenIQ / Circana)

Signal: Self-treatment volume by category
Use: Cohort-level demand modeling: heartburn-OTC SKU spikes by DMA inform GI service-line targeting. Allergy SKU spikes inform ENT.
Example: GI — PPI sales spike in Tampa DMA feeds a 'You shouldn't need Prilosec every day' campaign for GI consult bookings.
Service line: GI, ENT/Allergy, Pain management, Sleep medicine

CommercialLow riskDirect activation30–60 days earlierActionability: High

Compliance note: Aggregated SKU-level data. No identifiable buyers.

Consumer & retail proxies

Grocery loyalty / SKU shifts (low-sodium, gluten-free, sugar-free)

Contrarian

Signal: Diet-driven condition self-management
Use: Aggregated SKU mix changes in a DMA proxy for diabetes, celiac, hypertension self-management cohorts. Feed lookalike seeds.
Example: Endocrinology — sugar-free SKU velocity surge across Dallas suburbs seeds a Meta lookalike for diabetes pre-screening clinics.
Service line: Endocrinology, Cardiology, GI

CommercialModerate riskModeled activation60–90 days earlierActionability: Medium

Compliance note: Use only aggregated, retailer-licensed panels. Never tie purchases to identifiable patients.

Consumer & retail proxies

Aggregated pharmacy fill data (IQVIA, Symphony) — de-identified

Signal: Therapy initiation, switching, abandonment
Use: Use ZIP3-level abandonment rates to time adherence and second-opinion campaigns. Fuel programmatic creative for specialty switches.
Example: Cardiology — statin abandonment ZIP3 clusters in Cleveland seed a 'cholesterol re-check' Search + display campaign for cardiology practices.
Service line: Cardiology, Endocrinology, Behavioral health

CommercialModerate riskModeled activation30–60 days earlierActionability: High

Compliance note: HIPAA-de-identified per Safe Harbor. Use ZIP3+ aggregation; never re-identify.

Mobility & location (aggregated)

Foot-traffic panels (Placer.ai, SafeGraph) — aggregated visit patterns

Signal: Healthcare access behavior, gym/wellness usage
Use: Identify hospital catchment leakage, urgent-care usage shifts, gym attendance drops. Feed catchment maps and OOH/CTV planning.
Example: Health system — urgent-care competitor capturing 18% of evening visits in 3 ZIPs triggers OOH + Connected TV in those ZIPs.
Service line: Hospital systems, Urgent care, Primary care, Cardiology rehab

CommercialModerate riskDirect activation30 days earlierActionability: High

Compliance note: Aggregated panel data, never individual device IDs for ad targeting.

Mobility & location (aggregated)

Public transit ridership dips (MTA, BART, regional APIs)

Contrarian

Signal: Population-level illness wave
Use: Sustained ridership dips combined with school absences = early flu/COVID/RSV wave. Trigger urgent-care and tele-health campaigns.
Example: Urgent care / Tele-health — NYC ridership dip + school absence spike triggers a 5-day flu-symptom Search & SMS push.
Service line: Urgent care, Primary care, Pediatrics, Tele-health

PublicLow riskDirect activation7–21 days earlier than claimsActionability: Medium

Compliance note: Aggregated public ridership counts.

Access & availability

Appointment-wait-time scrapes (Zocdoc public listings, hospital scheduling)

Signal: Specialty supply/demand mismatch
Use: Map specialties with 14+ day waits in a DMA to pitch tele-health alternatives, second-opinion services, or recruit new providers.
Example: Dermatology — 6-week wait in Boston feeds a tele-derm direct-to-consumer Search + Meta campaign.
Service line: Dermatology, Behavioral health, Endocrinology, Orthopedics

DerivedLow riskDirect activationReal-timeActionability: High

Compliance note: Use only public listings; respect ToS. Aggregated, no patient data.

Access & availability

NPI / NPPES provider density vs. population

Signal: Underserved specialty markets
Use: Quantify per-capita specialist supply gaps. Inform recruitment ads, expansion campaigns, and tele-health geo plans.
Example: Cardiology — only 2.1 cardiologists / 100k in rural Mississippi seeds a tele-cardiology consumer-acquisition campaign.
Service line: All specialty service lines

PublicLow riskDirect activationStanding baselineActionability: High

Compliance note: Public NPPES. Provider-level, not patient-level.

Reviews & patient experience

Yelp / Google review velocity & sentiment for local providers

Signal: Competitor weakness / capacity issues
Use: Detect competitor service degradation (rising 1–2 star velocity for wait times) to time competitive conquest campaigns.
Example: Urgent care — competitor Yelp ratings drop in Denver triggers a 'shorter waits, same-day appointments' Search + display flight.
Service line: Urgent care, Primary care, Specialty groups

CommercialLow riskDirect activationReal-timeActionability: High

Compliance note: Public reviews, aggregated. Respect platform ToS — no scraping in violation.

Reviews & patient experience

Review-content theme extraction (NLP on public reviews)

Contrarian

Signal: Patient-experience friction points
Use: Surface recurring themes ('parking', 'billing surprises', 'rude front desk') to inform messaging and creative for the client's clinic.
Example: OB/GYN — 'rushed visits' theme dominant for top-3 competitors → 'unhurried OB visits' creative direction in Meta and CTV.
Service line: OB/GYN, Orthopedics, Dental, Aesthetics

DerivedLow riskIndirect activationStandingActionability: Medium

Compliance note: NLP over public review text. No PHI.

Workplace & employer trends

Indeed / LinkedIn job-posting density (RN, MA, scribe, oncology nurse)

Contrarian

Signal: Service-line expansion or contraction by competitor
Use: Track competitor staffing surges (e.g., oncology RN postings) to predict service-line launches and pre-empt with conquest campaigns.
Example: Oncology — competitor health system posts 40 oncology RN roles in Charlotte → agency runs 'established cancer-care team' campaign before competitor opens.
Service line: All service lines (competitive intel)

PublicLow riskIndirect activation60–120 days earlierActionability: High

Compliance note: Public job postings.

Workplace & employer trends

WARN Act layoff notices + BLS mass-layoff data

Contrarian

Signal: Coverage transition / COBRA / behavioral health spike
Use: Predict surges in COBRA enrollment, behavioral-health demand, and Marketplace coverage shopping. Time payer-funded outreach and ACA enrollment campaigns.
Example: Behavioral health — large WARN filing in Pittsburgh triggers a 6-week tele-therapy + EAP Meta + Search push.
Service line: Behavioral health, Primary care, Marketplace plans

PublicLow riskDirect activation30–60 days earlierActionability: High

Compliance note: State labor department public filings.

Workplace & employer trends

Employer benefits-design changes (Mercer / KFF surveys, public 5500 filings)

Signal: Self-funded plan benefit shifts (HDHP, COE programs)
Use: Map employers with new HDHP / Centers of Excellence carve-outs to time direct-to-employer campaigns and steerage.
Example: Orthopedics — large self-funded employer adds COE program for joint replacements; agency runs employer-targeted LinkedIn + email.
Service line: Orthopedics, Cardiology, Bariatrics, Oncology

PublicLow riskDirect activation60–90 days earlierActionability: Medium

Compliance note: Form 5500 + survey data. Employer-level.

Public health datasets

School absenteeism dashboards (state/district)

Contrarian

Signal: Pediatric / community illness wave
Use: Real-time leading indicator (5–10 days) of flu/strep/RSV waves. Trigger pediatric urgent-care and pharmacy flu-shot campaigns.
Example: Urgent care — Pittsburgh district absences cross 8% triggers a same-week pediatric urgent-care Search + radio flight.
Service line: Pediatrics, Urgent care, Primary care, Pharmacy

PublicLow riskDirect activation7–21 days earlierActionability: High

Compliance note: District-level aggregated data.

Public health datasets

CDC NSSP / state syndromic ED surveillance feeds

Signal: Symptom-cluster epidemic curve
Use: Detect respiratory, GI, mental-health ED visit surges by region. Drive same-week tele-health and urgent-care media plans.
Example: Tele-health — RSV ED visits spike in Phoenix triggers tele-pediatrics SMS + Search ad surge.
Service line: Urgent care, Tele-health, Pediatrics, Behavioral health

PublicLow riskDirect activation7–14 days earlierActionability: High

Compliance note: Aggregated, region-level public health surveillance.

Media consumption

Podcast-topic trends (Listen Notes, Podscribe, Spotify charts)

Contrarian

Signal: Cultural rise of conditions / treatments
Use: Use podcast topic surges (Ozempic, perimenopause, ADHD) to time content marketing, podcast sponsorships, and creative themes.
Example: Women's health — perimenopause podcast surge → sponsored mid-rolls and content campaign for women's-health clinics.
Service line: OB/GYN, Behavioral health, Endocrinology

CommercialLow riskIndirect activation60–90 days earlierActionability: Medium

Compliance note: Aggregated topic-level metrics.

Media consumption

Local news health-story velocity (NewsAPI, GDELT)

Signal: Geo-bound condition awareness
Use: Time campaigns to ride local news cycles (cancer-cluster coverage, Medicaid changes) without ambulance-chasing tone.
Example: Oncology — Cleveland news coverage of breast-cancer screening grant drives agency to amplify screening campaign that week.
Service line: Oncology, Primary care, Cardiology

PublicLow riskIndirect activationReal-timeActionability: Medium

Compliance note: Public news feeds.

Wearable & device aggregates

Fitness-platform aggregated trends (Strava Metro, Apple Mobility)

Contrarian

Signal: Activity-level shifts / sedentary cohorts
Use: Aggregated DMA-level activity drops feed cardiac-risk, weight-loss, and joint-replacement campaign geo-targeting.
Example: Bariatrics — sustained activity drop in suburban Detroit ZIPs feeds a Meta + CTV bariatric-info-session campaign.
Service line: Bariatrics, Cardiology, Orthopedics, PT

PublicLow riskModeled activation60–90 days earlierActionability: Medium

Compliance note: Fully aggregated, anonymized, opt-in panel.

Wearable & device aggregates

Aggregated sleep-tracking trends (Oura/Whoop research releases)

Contrarian

Signal: Population sleep-quality shifts
Use: Use regional sleep-quality declines as a soft proxy for stress, behavioral health, and sleep-clinic demand. Inform creative themes and audience seeds.
Example: Sleep medicine / Behavioral health — published regional sleep-quality drops feed a 'reset your sleep' Meta + Search creative test.
Service line: Sleep medicine, Behavioral health

PublicLow riskIndirect activationStandingActionability: Low

Compliance note: Use only published aggregate research releases.

Workplace & employer trends

Building/construction permits for medical buildings

Contrarian

Signal: Competitor capacity coming online
Use: Predict competitor clinic openings 6–12 months out. Pre-empt with brand and acquisition campaigns in those ZIPs.
Example: Hospital system — competitor breaks ground on ASC in Raleigh suburb; agency runs 12-month brand awareness flight to lock catchment.
Service line: Hospital systems, ASCs, Specialty groups

PublicLow riskIndirect activation180+ days earlierActionability: Medium

Compliance note: Public permit data.

Public health datasets

Library health-book checkout patterns (where published)

Contrarian

Signal: Self-education demand for chronic / new diagnoses
Use: Soft proxy for diagnosed cohorts seeking more info. Inform content themes and community outreach.
Example: Endocrinology — diabetes-cookbook checkout spikes in Tulsa branches feed community diabetes-education campaign.
Service line: Endocrinology, Cardiology, Oncology

PublicLow riskIndirect activation60–90 days earlierActionability: Low

Compliance note: Aggregated public stats only.

Local incident & environmental

OpenTable / Resy cancellation surges

Contrarian

Signal: Population-level illness or weather event
Use: Sudden cancellation spikes in a city correlate with respiratory illness waves and severe weather. Co-trigger urgent-care and tele-health pushes.
Example: Urgent care — Boston Saturday cancellation spike + flu-related queries → emergency tele-health + urgent-care SEM push.
Service line: Urgent care, Tele-health, Primary care

CommercialLow riskIndirect activation0–7 daysActionability: Low

Compliance note: Aggregated, city-level.

Consumer & retail proxies

Gym membership churn (chain-level / aggregated)

Contrarian

Signal: Lifestyle disengagement / injury-driven dropoff
Use: Q2 churn surges in specific DMAs feed orthopedic, weight-management, and PT campaign geo-targeting.
Example: Orthopedics / PT — chain-level Q1→Q2 churn spike in Charlotte feeds 'why your knee hurts after running' Meta + Search creative.
Service line: Orthopedics, PT, Bariatrics

CommercialLow riskModeled activation30–60 days earlierActionability: Medium

Compliance note: Aggregated chain-level data only.

Top 10 marketing-ready sources

Deployable inside an agency in 60–90 days.

Compliant, easy to activate, highly relevant to healthcare demand, and tied to live campaign channels.

01
Google Trends — symptom & condition queries by DMA
Early symptom intent · 30–90 days earlier than claims
02
EPA AirNow AQI + NOAA pollen indices
Acute respiratory exacerbation trigger · 0–7 days earlier (real-time)
03
School absenteeism dashboards (state/district)
Pediatric / community illness wave · 7–21 days earlier
04
Appointment-wait-time scrapes (Zocdoc public listings, hospital scheduling)
Specialty supply/demand mismatch · Real-time
05
Yelp / Google review velocity & sentiment for local providers
Competitor weakness / capacity issues · Real-time
06
Indeed / LinkedIn job-posting density (RN, MA, scribe, oncology nurse)
Service-line expansion or contraction by competitor · 60–120 days earlier
07
WARN Act layoff notices + BLS mass-layoff data
Coverage transition / COBRA / behavioral health spike · 30–60 days earlier
08
OTC sales scanner data (IRI / NielsenIQ / Circana)
Self-treatment volume by category · 30–60 days earlier
09
Foot-traffic panels (Placer.ai, SafeGraph) — aggregated visit patterns
Healthcare access behavior, gym/wellness usage · 30 days earlier
10
CDC NSSP / state syndromic ED surveillance feeds
Symptom-cluster epidemic curve · 7–14 days earlier

Signal-to-campaign mapping

How a signal becomes a campaign.

Signal cluster

Service line

Campaign

Channels

AQI + pollen + school absences

Pulmonology, ENT/Allergy, Urgent care, Pediatrics

24-hr-trigger geo-fenced 'breathing trouble?' search and display

Google SearchMetaProgrammatic display

OTC PPI sales + GI symptom queries

GI consult-booking funnel with 'you shouldn't need this every day' creative

Google SearchMetaCRM email nurture

Statin abandonment + cardiology query rise

Cardiology

Second-opinion / cholesterol re-check funnel by ZIP3

Google SearchProgrammatic displayCRM

Subreddit + TikTok + autocomplete drift

Behavioral health, Endocrinology, OB/GYN

Lookalike + interest creative test on Meta with new vocabulary

MetaTikTokYouTube

Traffic collisions + appointment wait scrapes

Orthopedics, PT, Pain

Programmatic geo-fenced PT/ortho injury campaign

Programmatic displayCTVGoogle Search

Competitor RN postings + construction permits

Oncology, Cardiology, ASC

Pre-emptive brand + acquisition flight in catchment

CTVOOHProgrammaticLinkedIn

WARN filings + behavioral-health forum velocity

Behavioral health, Primary care

Tele-therapy + Marketplace enrollment push

MetaGoogle SearchSMS / CRM

Foot-traffic leakage + Yelp degradation

Urgent care, Primary care

Conquest 'shorter waits' search + display in leakage ZIPs

Google SearchMetaOOH

Provider-density gap + tele-health intent

Dermatology, Endocrinology, Cardiology

DTC tele-specialty acquisition funnel

Google SearchMetaYouTube

Wearable activity drop + bariatric query rise

Bariatrics, Cardiology, PT

Info-session and consult-booking campaign

MetaCTVCRM email

MVP for Medigy Opportunity Atlas

What ships first.

Eight core data sources, a normalization layer, and an Opportunity Card output that drops directly into an agency's planning workflow.

Workflow

signalcohortservice linecampaign

Core MVP sources

Google Trends — symptom & condition queries by DMA — Early symptom intent
EPA AirNow AQI + NOAA pollen indices — Acute respiratory exacerbation trigger
School absenteeism dashboards (state/district) — Pediatric / community illness wave
Appointment-wait-time scrapes (Zocdoc public listings, hospital scheduling) — Specialty supply/demand mismatch
Yelp / Google review velocity & sentiment for local providers — Competitor weakness / capacity issues
OTC sales scanner data (IRI / NielsenIQ / Circana) — Self-treatment volume by category
Foot-traffic panels (Placer.ai, SafeGraph) — aggregated visit patterns — Healthcare access behavior, gym/wellness usage
Indeed / LinkedIn job-posting density (RN, MA, scribe, oncology nurse) — Service-line expansion or contraction by competitor

Output: Opportunity Card

Demand signal · Tier 1SIG-2024-1042

Orthopedics — knee-replacement intent surge, Tampa DMA.

Signal: Search query 'knee replacement near me' +47% WoW; Q2 gym-churn spike in 6 ZIPs.
Cohort: ~38k addressable adults 55+ in 6 ZIPs with elective-eligible coverage profile.
Channels: Google Search, Meta Reels, CTV, CRM warm-list email.
Activation: 14-day flight; $48k recommended budget; expected booking lift 22–31%.

Advertising activation model

Where the signals land.

For each platform, we mark what is direct, what is inferred, and what is modeled — so compliance and media teams know exactly how a signal flows into a campaign.

Google Ads

Direct: Geo-targeting by DMA/ZIP, keyword bidding from search-intent signals.
Inferred: Creative & landing-page tailoring from autocomplete drift and review themes.
Modeled: Custom-segment audiences from cohort-level signal blends.

Meta (Facebook / Instagram)

Direct: Geo + interest targeting; Reels/feed creative scheduling against trigger events.
Inferred: Interest-seed expansion from Reddit, TikTok, podcast trends.
Modeled: Lookalikes built from compliant first-party seeds informed by signal cohorts.

Programmatic / DSP / CTV

Direct: Geo-fenced flights triggered by AQI, collisions, school-absence thresholds.
Inferred: Contextual placements aligned to local news velocity.
Modeled: Cohort scoring layered into DMP segments and CTV audience packages.

CRM / Email / SMS

Direct: Suppression + send-time triggers from environmental and surveillance signals.
Inferred: Creative themes from review NLP and forum sentiment.
Modeled: Propensity models scoring existing CRM against signal-blended cohorts.

Compliance & defensibility

Built to pass hospital compliance review.

De-identified or aggregated by default

Every signal we ingest is at the cohort, ZIP3, or DMA grain. No PHI is used to target individuals — ever.

Targeting avoids PHI misuse

We never tie identifiable health data to ad audiences. Activation is via geo, contextual, interest, and modeled segments — all consistent with Google and Meta health-targeting rules.

Explainable to a compliance team

Each source ships with its data lineage, refresh cadence, aggregation thresholds, and an in-plain-English compliance note for hospital legal review.

Aligned with platform ad policies

We pre-screen every activation path against Google, Meta, and major DSP health-ads policies. If a path can't run, the signal is reclassified as 'Indirect' or 'Inferred'.

Trust converts

De-identification and aggregation aren't just legal hygiene — they're a marketing asset. Hospitals, payers, and patients engage faster with partners who can show their math, name their thresholds, and explain their lineage in plain English.

See the Demand Signals Engine run against your service line.

30 minutes. We'll point it at the specialty, geography, or competitor you care about — and walk through the campaigns it would build this quarter.

Book a demo intelligence@medigy.com