We extract tuition costs, acceptance rates, diversity metrics, faculty statistics, and extracurricular profiles from Private School Review. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for School Profile objects from privateschoolreview.com. All fields typed and schema-versioned.
"school_id": "psr_8492", "name": "Phillips Exeter Academy", "city": "Exeter", "state": "NH", "zip_code": "03833", "grades_offered": "9-12", "religious_affiliation": "Nonsectarian", "school_type": "Boarding"
| # | school_id | name | street_address | city | state | zip_code |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Admissions & Tuition objects from privateschoolreview.com. All fields typed and schema-versioned.
"school_id": "psr_8492", "tuition_day": 45120, "tuition_boarding": 61120, "acceptance_rate": 15, "application_deadline": "Jan 15", "financial_aid_pct": 48, "total_endowment": 1300000000
| # | school_id | tuition_day | tuition_boarding | acceptance_rate | application_deadline | financial_aid_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Academics & Faculty objects from privateschoolreview.com. All fields typed and schema-versioned.
"school_id": "psr_8492", "student_teacher_ratio": "5:1", "average_class_size": 12, "faculty_count": 218, "faculty_advanced_degrees_pct": 82, "ap_courses_count": 0, "ib_program_offered": false
| # | school_id | student_teacher_ratio | average_class_size | faculty_count | faculty_advanced_degrees_pct | ap_courses_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Student Body objects from privateschoolreview.com. All fields typed and schema-versioned.
"school_id": "psr_8492", "total_students": 1085, "boarding_pct": 80, "international_pct": 11, "students_of_color_pct": 47, "average_sat_score": 1450, "average_act_score": 32
| # | school_id | total_students | boarding_pct | international_pct | students_of_color_pct | male_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Extracurriculars & Reviews objects from privateschoolreview.com. All fields typed and schema-versioned.
"school_id": "psr_8492", "sports_count": 22, "sports_list": "['Basketball', 'Crew', 'Cross Country', 'Ice Hockey']", "clubs_count": 140, "review_count": 47, "average_rating": 4.6, "top_review_text": "Exceptional Harkness method teaching."
| # | school_id | sports_count | sports_list | clubs_count | clubs_list | review_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our scraper maps the entire Private School Review directory, traversing state and county levels to extract deep institutional profiles, financial data, and demographic statistics.
Extract day and boarding tuition fees, financial aid percentages, and endowment figures to build accurate pricing models.
Capture acceptance rates, application deadlines, and interview requirements for every listed institution.
Retrieve student-teacher ratios, average class sizes, and faculty advanced degree percentages.
Track international student percentages, students of colour ratios, and gender distribution across the student body.
Extract AP course lists, IB program availability, and average SAT/ACT scores for graduating cohorts.
Compile comprehensive lists of athletic programs and extracurricular clubs offered at each campus.
Scrape parent, student, and alumni reviews, including star ratings and full text commentary.
Extract precise addresses, county assignments, and religious affiliations for geographic analysis.
Monitor year-over-year changes in tuition costs and demographic shifts through scheduled pipeline runs.
Brief in. Clean data out.
Provide target states, counties, or specific school URLs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, and directory traversal logic for privateschoolreview.com.
Schema validation, missing value checks, and data normalisation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Extracting data from broad directories requires systematic traversal and normalisation. We handle the complexity of inconsistent data fields and geographic routing.
Private School Review organises listings geographically. Our crawlers systematically traverse the state, county, and city directory trees to ensure zero missed listings across the entire US database.
Not all schools provide complete data. We implement strict schema normalisation, mapping missing tuition fields or unlisted AP courses to explicit null values rather than breaking the pipeline.
Aggressive directory scraping triggers rate limits. We use US-based residential ISP proxies with realistic request timing to maintain continuous extraction without IP bans.
For annual tuition updates, we maintain a hash index of last-seen values per school. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
School reviews are paginated. Our pipeline traverses all review pages to extract the complete historical feedback corpus, not just the front-page highlights.
Integrate comprehensive school profiles, demographic data, and academic offerings into school discovery applications.
Correlate private school availability, tuition costs, and quality metrics with local housing market valuations.
Analyse tuition trends, endowment growth, and demographic shifts across independent education sectors.
Build internal databases of acceptance rates, average test scores, and application deadlines for student placement.
Independent schools track regional competitor tuition rates, faculty ratios, and facility offerings.
Analyse financial aid percentages and endowment sizes to model regional accessibility to private education.
"Private School Review aggregates the most critical demographic and financial data for independent education, but extracting it requires systematic directory traversal."
Directory sites present unique challenges: inconsistent field availability, complex pagination across states, and aggressive rate limiting. DataFlirt manages the proxy rotation, state traversal, and schema normalisation so you receive clean, queryable data in your warehouse.
Everything supported by our privateschoolreview.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration, deduplication, and retry logic. Playwright handles JavaScript rendering and interaction flows where required.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request to prevent directory traversal blocking.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About privateschoolreview.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible under applicable law. DataFlirt targets only public demographic, financial, and academic data. We do not extract personal data or circumvent authentication walls. Clients should review the site's ToS and consult legal counsel for specific use cases.
Private schools report data inconsistently. Our schema normalisation ensures that missing fields, such as endowment figures or specific AP courses, are returned as explicit nulls rather than breaking your downstream ingestion.
Yes. We can configure the traversal logic to target specific states, counties, or zip code radii, reducing extraction time and focusing on your exact geographic requirements.
School data typically changes on an annual cycle. We recommend quarterly or annual pipeline runs to capture tuition adjustments and new enrollment statistics, though monthly runs are available for review monitoring.
Yes. We traverse all paginated review endpoints to extract the full text, star rating, and reviewer type for every school listing.
Our smallest packages start at a defined state or regional list with quarterly delivery. For full national directory extraction, we price based on volume and delivery frequency.
Absolutely. We provide a sample run of up to 100 schools as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full national directory export or continuous tracking of tuition changes across specific states — we scope, build, and operate the pipeline. Tell us what you need.
