Source Group Mix by Fiscal Year

Definition

The share of persons whose first engagement touch came from each source group, broken out by fiscal year. Shows whether the mix of channels reaching new prospects is shifting over time.

Summary

This page answers the question raised by the cohort conversion curve page: why is FY2025 a weaker cohort?

The no-engagement-touch share tells the story. FY2024 was an unusually well-tracked year — only 41.8% of the cohort had no recorded engagement, vs. 62.9% in FY2023. FY2025 reverted to 59.6%, and the total funnel grew from 38K to 55K persons. The growth came almost entirely from the no-engagement-touch population, which more than doubled in absolute terms (16K → 33K). High-quality channels grew only modestly. The FY2025 application rate dropped because the denominator was inflated by low-quality, untracked prospects — most likely name buys or imported lists.

Among touched persons only, organic search share has grown every year — 27.7% in FY2023, 35.3% in FY2024, 41.0% in FY2025 — which is the brand strength signal discussed on the organic search page.

Source Group	FY2023	FY2024	FY2025
no engagement touch	25,530 (62.9%)	16,013 (41.8%)	33,205 (59.6%)
direct / unknown	9,246 (22.8%)	12,696 (33.2%)	10,843 (19.5%)
organic search	4,157 (10.2%)	7,864 (20.5%)	9,252 (16.6%)
paid / carnegie	1,061 (2.6%)	401 (1.0%)	510 (0.9%)
email	276 (0.7%)	305 (0.8%)	395 (0.7%)
organic social	116 (0.3%)	473 (1.2%)	329 (0.6%)
paid display	51 (0.1%)	205 (0.5%)	543 (1.0%)
paid social	—	152 (0.4%)	411 (0.7%)
paid search	9 (0.0%)	101 (0.3%)	189 (0.3%)
other / small groups	118 (0.3%)	67 (0.2%)	71 (0.1%)
Total	40,564	38,277	55,748

Key Insight

FY2025’s lower application rate is explained by funnel composition, not a collapse in high-quality demand. The no-engagement-touch population more than doubled year over year, inflating the denominator without adding applicants. Among persons with recorded engagement, organic search share grew to 41% — the highest on record. The FY2025 cohort has a quality problem concentrated in the untracked segment, not a brand or channel performance problem.

Why This Is Important

An application rate can hold steady even as the underlying channel mix shifts dramatically — and that shift has real implications. If organic search share is growing, that reflects increasing brand strength and lower cost-per-acquisition. If paid share is growing, application volume is becoming more dependent on continued spend.

This view also surfaces whether the composition of the funnel is changing in ways that explain application rate trends. A cohort that arrived primarily through organic search will likely convert differently than one that arrived primarily through paid display — even if their total volumes are similar.

Methodology

Source group classification uses the same CASE logic as the first-touch application rate page. Persons with no recorded engagement touch are counted separately as no engagement touch. Share is calculated as a percentage of total persons in each fiscal year cohort.

Only FY2023–2025 are included as complete-year cohorts with reliable pipeline data.

Query

WITH first_touch AS (
  SELECT
    person_id,
    utm_source,
    utm_medium,
    ROW_NUMBER() OVER (
      PARTITION BY person_id
      ORDER BY touched_at ASC
    ) AS rn
  FROM person_touches
  WHERE touch_category = 'engagement'
),

source_groups AS (
  SELECT
    person_id,
    CASE
      WHEN lower(utm_source) IN ('google', 'bing', 'yahoo', 'yahoo!', 'duckduckgo', 'ecosia', 'yandex', '360.cn', 'baidu')
        AND lower(utm_medium) IN ('organic', 'organic_search', 'search')
        THEN 'organic search'
      WHEN lower(utm_source) IN ('google', 'bing')
        AND lower(utm_medium) IN ('cpc', 'paid', 'paid_search', 'ppc')
        THEN 'paid search'
      WHEN lower(utm_source) IN ('googlead', 'mediately')
        OR lower(utm_medium) IN ('mediately', 'display', 'lightbox', 'banner')
        THEN 'paid display'
      WHEN lower(utm_source) IN ('carnegie-digital', 'carnegie', 'carnegie_digital')
        AND lower(utm_medium) IN ('ppc', 'paid-social', 'paid_social', 'cpc', 'display', 'lightbox', 'discovery', 'custom-content', 'video')
        THEN 'paid / carnegie'
      WHEN lower(utm_source) IN ('facebook', 'instagram', 'linkedin', 'youtube', 'tiktok', 'snapchat', 'twitter', 'reddit', 'meta')
        AND lower(utm_medium) IN ('paid', 'paid-social', 'paid_social', 'cpc')
        THEN 'paid social'
      WHEN lower(utm_source) IN ('facebook', 'instagram', 'linkedin', 'youtube', 'tiktok', 'snapchat', 'twitter', 'reddit')
        OR lower(utm_medium) IN ('social')
        THEN 'organic social'
      WHEN lower(utm_source) IN ('slate', 'gmail', 'miami-matters', 'mass_mailer', 'inbound-email', 'notifier', 'email', 'newsletter')
        OR lower(utm_medium) IN ('email')
        THEN 'email'
      WHEN lower(utm_source) IN ('nrccua', 'encoura', 'collegeboard', 'cappex', 'niche', 'niche.com', 'qs', 'usnews_studentconnect', 'hotcoursesinternational', 'idp', 'ziprecruiter')
        THEN 'vendor / purchased list'
      WHEN lower(utm_source) IN ('chatgpt.com', 'perplexity', 'claude', 'gemini', 'copilot.com')
        THEN 'ai referral'
      WHEN utm_source IS NULL OR utm_source = '' OR utm_source = '(none)'
        THEN 'direct / unknown'
      ELSE 'other'
    END AS source_group
  FROM first_touch
  WHERE rn = 1
),

labeled AS (
  SELECT
    pd.person_id,
    pd.fiscal_year,
    COALESCE(sg.source_group, 'no engagement touch') AS source_group
  FROM persons_dashboard pd
  LEFT JOIN source_groups sg ON pd.person_id = sg.person_id
  WHERE pd.fiscal_year IN ('2023', '2024', '2025')
),

totals AS (
  SELECT fiscal_year, COUNT(*) AS total_persons
  FROM labeled
  GROUP BY fiscal_year
)

SELECT
  l.fiscal_year,
  l.source_group,
  COUNT(*) AS people,
  t.total_persons,
  ROUND(COUNT(*) * 100.0 / t.total_persons, 1) AS pct_of_cohort
FROM labeled l
JOIN totals t ON l.fiscal_year = t.fiscal_year
GROUP BY l.fiscal_year, l.source_group, t.total_persons
ORDER BY l.fiscal_year, people DESC;