Unaided Awareness Proxy

Definition

The share of touched persons whose first engagement was either organic search or direct/unknown traffic — channels where the prospect initiated contact without a paid or outbound prompt. This is a proxy for unaided awareness: the portion of the funnel that arrived because they already knew or sought out the institution.

Summary

Fiscal Year	Touched Persons	Unaided Persons	Unaided Share of Touched	Total Applicants	Unaided Applicants	Unaided Share of Applicants
FY2023	15,034	13,403	89.2%	3,927	3,703	94.3%
FY2024	22,264	20,560	92.3%	5,602	5,178	92.4%
FY2025	22,543	20,095	89.1%	4,813	4,392	91.3%

More than 89% of touched persons in every year arrived through unaided channels — organic search or direct/unknown. The share peaked in FY2024 at 92.3% of touched persons and 92.4% of applicants, then pulled back slightly in FY2025 to 89.1% and 91.3% respectively. Absolute unaided prospect volume grew substantially from FY2023 to FY2024 (13,403 → 20,560) and held steady in FY2025 (20,095).

Caution

The direct / unknown bucket — persons with no UTM attribution — is the dominant component of this metric. Traffic without UTM parameters includes direct navigation and bookmarks, but can also include organic social clicks, email clients that strip parameters, and any paid or referred traffic from campaigns that weren’t tagged. The metric reflects channel attribution quality as much as true unaided behavior. Improving UTM tagging coverage would shift some volume from direct / unknown into paid or referral buckets.

Key Insight

The paid channel footprint in this funnel is narrow. Even in FY2024 — the peak year for paid media investment — over 92% of applicants traced back to organic search or unattributed direct traffic. Paid channels (paid search, paid display, paid/carnegie, paid social) collectively account for less than 10% of applicants in any year.

This does not mean paid media has no value — the estimated incremental applications and paid media time to application analyses show it does lift conversion. But it does mean the institution’s applicant pipeline is structurally dependent on brand strength and organic demand, not paid acquisition. Maintaining or growing the unaided share is the highest-leverage brand objective.

Why This Is Important

Unaided awareness is one of the strongest indicators of brand health in higher ed. Students who arrive through organic search or direct navigation have already formed enough awareness and intent to act without being prompted. Growing this share over time means the brand is doing more of the recruitment work, reducing dependence on paid spend.

For board presentations, a rising unaided awareness proxy answers the question: is our brand getting stronger, or are we just buying more applicants? It also provides a risk frame — if unaided awareness is flat or declining while paid share grows, the institution is becoming more exposed to budget risk.

Note

This metric is calculated on touched persons only, excluding the no-engagement-touch population. Including untracked persons would dilute the signal with list imports and name buys that have no meaningful channel attribution.

Methodology

Persons are classified by first-touch source group using the same logic as the first-touch application rate page. The unaided share is (organic search + direct/unknown) / total touched persons for each fiscal year. Both the overall unaided share and the applicant-only unaided share are reported — the latter is the stronger brand signal.

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
),

cohort AS (
  SELECT
    pd.person_id,
    pd.fiscal_year,
    pd.applied,
    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')
)

SELECT
  fiscal_year,
  COUNT(CASE WHEN source_group != 'no engagement touch' THEN 1 END) AS touched_persons,
  SUM(CASE WHEN applied = 'Yes' THEN 1 ELSE 0 END) AS total_applicants,

  SUM(CASE WHEN source_group IN ('organic search', 'direct / unknown') THEN 1 ELSE 0 END) AS unaided_persons,
  SUM(CASE WHEN applied = 'Yes' AND source_group IN ('organic search', 'direct / unknown') THEN 1 ELSE 0 END) AS unaided_applicants,

  ROUND(
    SUM(CASE WHEN source_group IN ('organic search', 'direct / unknown') THEN 1 ELSE 0 END) * 100.0
    / NULLIF(COUNT(CASE WHEN source_group != 'no engagement touch' THEN 1 END), 0),
    1
  ) AS unaided_share_of_touched,

  ROUND(
    SUM(CASE WHEN applied = 'Yes' AND source_group IN ('organic search', 'direct / unknown') THEN 1 ELSE 0 END) * 100.0
    / NULLIF(SUM(CASE WHEN applied = 'Yes' THEN 1 ELSE 0 END), 0),
    1
  ) AS unaided_share_of_applicants

FROM cohort
GROUP BY fiscal_year
ORDER BY fiscal_year;