Listing Performance Analysis

Date: 2026-01-14 Analysis Period: 2024-01-01 onwards (2025-10-14 to 2026-01-13 for decay analysis)

Correction (2026-09-28): the original queries filtered status = 1 (Deleted) instead of active listings; queries and results below have been re-run.

• sadb_listings.status codes: 0 = Active, 1 = Deleted, 4 = Suspended, 11 = Closed.
• The decay analysis (sections 2 and 3) looks at how listings performed during a past window, so it now uses no status filter. It includes every listing that had daily stats in the window, including ones that have since closed or been deleted. Of the 168,658 listings with stats in the window, 55% are now Deleted, 35% Closed and only about 6% (9,627) currently active (status IN (0, 4) AND published = 1). Filtering to currently active listings would keep only the stale survivors. That subset gets less than half the views (Day 2 avg 10.8) and converts worse (4.3% on Day 2).
• The window is pinned to the original 3 months (2025-10-14 to 2026-01-13) instead of today() - INTERVAL 3 MONTH, so results cover the same period as the original run.
• The original figures cannot be reproduced exactly even with status = 1, because more listings have moved to Deleted since January.
• Section 1 (Time on Market) never used a status filter, so it is unchanged.
• What changed materially: the “first 2 weeks ≈ 50% of contacts” claim drops to ~36%. Absolute views and conversion rates are lower across the board. Makkah no longer has the highest Week 1 conversion; Riyadh does.

Executive Summary

This analysis covers three key aspects of listing performance:

1. Time on Market - How long listings take to close by category/city
2. View Decay - How views decrease as listings age
3. Contact Conversion Decay - How view-to-contact rates change over time

Key Findings

Metric	Finding
Time on Market	Improved 50-60% from early 2024 to late 2025
View Decay	72% drop by Day 90, Day 2 is peak
Conversion Decay	Drops from 7.1% to 4.3% (-39%) over 90 days
Critical Window	First 2 weeks generate ~36% of all contacts

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1. Time on Market Analysis

Overview

Time on market measures days from published_at to close_time for listings that have been closed.

By Category (Median Days)

Category	Closed	Median	P25	P75	P90
Room for Rent	4,594	27	8	80	145
Big Flat for Rent	17,791	34	14	70	121
Apartment for Rent	166,552	39	15	82	144
Villa for Rent	23,256	46	17	98	159
Land for Sale	68,011	89	33	148	235
Big Flat for Sale	20,623	88	37	149	235
Villa for Sale	75,864	88	37	155	249
Apartment for Sale	68,130	104	53	180	269

Insight: Rentals move 2-3x faster than sales

By City (Median Days)

City	Closed	Median	P25	P75
الرياض (Riyadh)	302,701	53	19	111
الظهران (Dhahran)	2,638	58	23	117
الهفوف (Hofuf)	4,208	69	25	127
جدة (Jeddah)	72,524	76	30	143
الدمام (Dammam)	23,352	78	28	151
مكة المكرمة (Makkah)	8,787	94	35	167

Insight: Riyadh is the fastest market

Monthly Cohort Trends

Apartment for Rent (Median Days by Cohort)

Cohort	Riyadh	Jeddah	Dammam
Jan 2024	51	62	57
Jul 2024	39	39	33
Jan 2025	33	37	33
Oct 2025	32	35	30

Trend: Convergence to ~30-35 days across all cities

Villa for Sale (Median Days by Cohort)

Cohort	Riyadh	Jeddah	Dammam
Jan 2024	108	152	141
Jul 2024	94	142	164
Jan 2025	18	60	21
Oct 2025	52	49	30

Trend: Major improvement from 108-152 days to 30-52 days

Query: Time on Market by Category

SELECT
  c.name_en AS category,
  COUNT(*) AS closed_listings,
  ROUND(AVG((l.close_time - l.published_at) / 86400), 1) AS avg_days,
  ROUND(
    median((l.close_time - l.published_at) / 86400),
    1
  ) AS median_days,
  ROUND(
    quantile(0.25) ((l.close_time - l.published_at) / 86400),
    1
  ) AS p25_days,
  ROUND(
    quantile(0.75) ((l.close_time - l.published_at) / 86400),
    1
  ) AS p75_days,
  ROUND(
    quantile(0.90) ((l.close_time - l.published_at) / 86400),
    1
  ) AS p90_days
FROM
  sadb_listings l FINAL
  JOIN sadb_categories c FINAL ON l.category = c.category_id
WHERE
  l.close_time > l.published_at
  AND l.published_at > 0
  AND l._peerdb_is_deleted = 0
  AND (l.close_time - l.published_at) / 86400 BETWEEN 1 AND 730
  AND toDate(l.published_at) >= '2024-01-01'
GROUP BY
  c.name_en
HAVING
  closed_listings >= 100
ORDER BY
  closed_listings DESC

Query: Time on Market by City

SELECT
  d.city_name,
  COUNT(*) AS closed_listings,
  ROUND(AVG((l.close_time - l.published_at) / 86400), 1) AS avg_days,
  ROUND(
    median((l.close_time - l.published_at) / 86400),
    1
  ) AS median_days,
  ROUND(
    quantile(0.25) ((l.close_time - l.published_at) / 86400),
    1
  ) AS p25_days,
  ROUND(
    quantile(0.75) ((l.close_time - l.published_at) / 86400),
    1
  ) AS p75_days
FROM
  sadb_listings l FINAL
  JOIN sadb_districts d FINAL ON l.district_id = d.district_id
WHERE
  l.close_time > l.published_at
  AND l.published_at > 0
  AND l._peerdb_is_deleted = 0
  AND (l.close_time - l.published_at) / 86400 BETWEEN 1 AND 730
  AND toDate(l.published_at) >= '2024-01-01'
GROUP BY
  d.city_name
HAVING
  closed_listings >= 1000
ORDER BY
  closed_listings DESC

Query: Monthly Cohort Analysis by Category + City

SELECT
  toStartOfMonth(toDate(l.published_at)) AS cohort_month,
  c.name_en AS category,
  d.city_name,
  COUNT(*) AS closed_listings,
  ROUND(
    median((l.close_time - l.published_at) / 86400),
    1
  ) AS median_days
FROM
  sadb_listings l FINAL
  JOIN sadb_categories c FINAL ON l.category = c.category_id
  JOIN sadb_districts d FINAL ON l.district_id = d.district_id
WHERE
  l.close_time > l.published_at
  AND l.published_at > 0
  AND l._peerdb_is_deleted = 0
  AND (l.close_time - l.published_at) / 86400 BETWEEN 1 AND 365
  AND toDate(l.published_at) >= '2024-01-01'
  AND c.name_en = 'Apartment for Rent'
  AND d.city_name IN ('الرياض', 'جدة', 'الدمام')
GROUP BY
  cohort_month,
  c.name_en,
  d.city_name
HAVING
  closed_listings >= 50
ORDER BY
  d.city_name,
  cohort_month

---

2. View Decay Analysis

Overview

Views decrease significantly as listings age. Day 2 is typically the peak (not Day 1, due to indexing delays).

Overall View Decay Pattern

Listing Age	Avg Views	Median Views	% of Peak
Day 1	18.5	11	79%
Day 2	23.4	12	100%
Day 3	19.7	10	84%
Day 7	15.9	8	68%
Day 14	13.1	6	56%
Day 30	10.4	5	44%
Day 60	7.8	4	33%
Day 90	6.5	3	28%

View Decay by Category

Category	Week 1	Week 2	Wk 3-4	Mo 2	Mo 3	Decay
Apartment Rent	32.6	25.3	21.1	17.0	14.7	–55%
Villa Rent	20.5	15.3	12.9	10.5	9.3	–55%
Villa Sale	14.6	11.0	9.5	8.1	6.9	–53%
Land Sale	8.6	5.8	4.8	4.1	3.6	–58%
Apartment Sale	6.7	5.5	5.0	4.3	3.6	–46%

View Decay by City

City	Week 1	Week 2	Wk 3-4	Mo 2	Mo 3	Decay
الدمام	23.4	17.3	14.2	10.4	9.0	–62%
الرياض	20.8	15.5	12.7	9.8	7.7	–63%
جدة	14.4	11.4	9.7	7.9	6.6	–54%
مكة	11.6	8.8	7.5	6.0	4.6	–60%

Land Sale still has the steepest view decay among categories. Apartment Sale now decays least (-46%). Makkah no longer has the steepest decay among cities; Riyadh and Dammam do, and Jeddah still decays least.

Query: View Decay by Listing Age

SELECT
  s.day_time - toInt32(l.published_at / 86400) AS listing_age_days,
  COUNT(DISTINCT s.id) AS listings_count,
  SUM(s.views) AS total_views,
  ROUND(AVG(s.views), 2) AS avg_views_per_listing,
  ROUND(median(s.views), 1) AS median_views
FROM
  sadb_stats_listings_stats s FINAL
  JOIN sadb_listings l FINAL ON s.id = l.id
WHERE
  toDate(s.day_time) BETWEEN '2025-10-14' AND '2026-01-13'
  AND l.published_at > 0
  AND s.day_time >= toInt32(l.published_at / 86400)
  AND l._peerdb_is_deleted = 0
  -- no status filter: listings that have since closed or been deleted are included
  AND (s.day_time - toInt32(l.published_at / 86400)) BETWEEN 0 AND 90
GROUP BY
  listing_age_days
ORDER BY
  listing_age_days

Query: View Decay by Category (Bucketed)

SELECT
  c.name_en AS category,
  CASE
    WHEN listing_age_days BETWEEN 0 AND 7 THEN '1. Week 1'
    WHEN listing_age_days BETWEEN 8 AND 14 THEN '2. Week 2'
    WHEN listing_age_days BETWEEN 15 AND 30 THEN '3. Week 3-4'
    WHEN listing_age_days BETWEEN 31 AND 60 THEN '4. Month 2'
    ELSE '5. Month 3'
  END AS age_bucket,
  ROUND(AVG(views), 2) AS avg_views,
  ROUND(median(views), 1) AS median_views
FROM
  (
    SELECT
      s.id,
      l.category,
      s.day_time - toInt32(l.published_at / 86400) AS listing_age_days,
      s.views
    FROM
      sadb_stats_listings_stats s FINAL
      JOIN sadb_listings l FINAL ON s.id = l.id
    WHERE
      toDate(s.day_time) BETWEEN '2025-10-14' AND '2026-01-13'
      AND l.published_at > 0
      AND s.day_time >= toInt32(l.published_at / 86400)
      AND l._peerdb_is_deleted = 0
      -- no status filter: listings that have since closed or been deleted are included
      AND (s.day_time - toInt32(l.published_at / 86400)) BETWEEN 0 AND 90
  ) t
  JOIN sadb_categories c FINAL ON t.category = c.category_id
WHERE
  c.name_en IN (
    'Apartment for Rent',
    'Villa for Sale',
    'Land for Sale',
    'Apartment for Sale',
    'Villa for Rent'
  )
GROUP BY
  c.name_en,
  age_bucket
ORDER BY
  c.name_en,
  age_bucket

---

3. Contact Conversion Decay Analysis

Overview

Conversion rate (contacts / views) also decays over time, but less dramatically than raw views.

Overall Conversion Decay

Listing Age	Avg Views	Avg Contacts	Conversion %
Day 0	16.2	1.75	10.8%
Day 2	23.4	1.65	7.1%
Day 7	15.9	0.90	5.6%
Day 14	13.1	0.71	5.4%
Day 30	10.4	0.52	5.0%
Day 60	7.8	0.35	4.5%
Day 90	6.5	0.28	4.3%

Decay Comparison

Metric	Week 1	Month 3	Decay
Views	18.5 avg	7.0 avg	–62%
Contacts	1.17 avg	0.31 avg	–74%
Conversion %	6.3%	4.4%	–31%

Share of all contacts in the window by listing age: Week 1 23%, Week 2 14%, Weeks 3-4 22%, Month 2 25%, Month 3 17%. The first two weeks generate ~36% of contacts, down from the ~50% originally reported. That is still the most contact-dense period per day of listing age.

Conversion by Category

Category	Week 1	Week 2	Wk 3-4	Mo 2	Mo 3	Decay
Apartment Rent	7.2%	6.5%	6.2%	5.9%	5.8%	–19%
Villa Rent	6.3%	5.6%	5.3%	5.2%	5.3%	–16%
Land Sale	6.7%	4.6%	4.3%	3.8%	3.4%	-49%
Apartment Sale	3.6%	3.5%	3.5%	3.4%	3.3%	–8%
Villa Sale	3.4%	2.7%	2.5%	2.3%	2.2%	-35%

Insight (holds): Rentals maintain conversion better, and Land sales have the steepest decay. Land’s Week 1 rate (6.7%) is now just below Apartment Rent’s (7.2%) rather than tied with it.

Conversion by City

City	Week 1	Week 2	Wk 3-4	Mo 2	Mo 3	Decay
مكة	6.4%	5.9%	5.0%	4.5%	3.8%	–41%
الرياض	6.8%	5.8%	5.5%	5.1%	4.7%	–31%
الدمام	6.1%	5.4%	5.0%	4.5%	4.7%	–23%
جدة	5.8%	5.1%	4.7%	4.4%	4.2%	–28%

Makkah still has the steepest conversion decay, and it now ends lowest at Month 3. Riyadh, not Makkah, has the highest Week 1 conversion. Jeddah has the lowest Week 1 baseline.

Query: Conversion by Listing Age

SELECT
  s.day_time - toInt32(l.published_at / 86400) AS listing_age_days,
  SUM(s.views) AS total_views,
  SUM(s.calls + s.msgs + s.whatsapp) AS total_contacts,
  ROUND(
    100.0 * SUM(s.calls + s.msgs + s.whatsapp) / NULLIF(SUM(s.views), 0),
    2
  ) AS conversion_pct,
  ROUND(AVG(s.views), 1) AS avg_views,
  ROUND(AVG(s.calls + s.msgs + s.whatsapp), 2) AS avg_contacts
FROM
  sadb_stats_listings_stats s FINAL
  JOIN sadb_listings l FINAL ON s.id = l.id
WHERE
  toDate(s.day_time) BETWEEN '2025-10-14' AND '2026-01-13'
  AND l.published_at > 0
  AND s.day_time >= toInt32(l.published_at / 86400)
  AND l._peerdb_is_deleted = 0
  -- no status filter: listings that have since closed or been deleted are included
  AND (s.day_time - toInt32(l.published_at / 86400)) BETWEEN 0 AND 90
GROUP BY
  listing_age_days
ORDER BY
  listing_age_days

Query: Conversion by Category (Bucketed)

SELECT
  c.name_en AS category,
  CASE
    WHEN listing_age_days BETWEEN 0 AND 7 THEN '1. Week 1'
    WHEN listing_age_days BETWEEN 8 AND 14 THEN '2. Week 2'
    WHEN listing_age_days BETWEEN 15 AND 30 THEN '3. Week 3-4'
    WHEN listing_age_days BETWEEN 31 AND 60 THEN '4. Month 2'
    ELSE '5. Month 3'
  END AS age_bucket,
  SUM(views) AS total_views,
  SUM(contacts) AS total_contacts,
  ROUND(100.0 * SUM(contacts) / NULLIF(SUM(views), 0), 2) AS conversion_pct,
  ROUND(AVG(views), 1) AS avg_views,
  ROUND(AVG(contacts), 2) AS avg_contacts
FROM
  (
    SELECT
      s.id,
      l.category,
      s.day_time - toInt32(l.published_at / 86400) AS listing_age_days,
      s.views,
      s.calls + s.msgs + s.whatsapp AS contacts
    FROM
      sadb_stats_listings_stats s FINAL
      JOIN sadb_listings l FINAL ON s.id = l.id
    WHERE
      toDate(s.day_time) BETWEEN '2025-10-14' AND '2026-01-13'
      AND l.published_at > 0
      AND s.day_time >= toInt32(l.published_at / 86400)
      AND l._peerdb_is_deleted = 0
      -- no status filter: listings that have since closed or been deleted are included
      AND (s.day_time - toInt32(l.published_at / 86400)) BETWEEN 0 AND 90
  ) t
  JOIN sadb_categories c FINAL ON t.category = c.category_id
WHERE
  c.name_en IN (
    'Apartment for Rent',
    'Villa for Sale',
    'Land for Sale',
    'Apartment for Sale',
    'Villa for Rent'
  )
GROUP BY
  c.name_en,
  age_bucket
ORDER BY
  c.name_en,
  age_bucket

Query: Conversion by City (Bucketed)

SELECT
  d.city_name,
  CASE
    WHEN listing_age_days BETWEEN 0 AND 7 THEN '1. Week 1'
    WHEN listing_age_days BETWEEN 8 AND 14 THEN '2. Week 2'
    WHEN listing_age_days BETWEEN 15 AND 30 THEN '3. Week 3-4'
    WHEN listing_age_days BETWEEN 31 AND 60 THEN '4. Month 2'
    ELSE '5. Month 3'
  END AS age_bucket,
  SUM(views) AS total_views,
  SUM(contacts) AS total_contacts,
  ROUND(100.0 * SUM(contacts) / NULLIF(SUM(views), 0), 2) AS conversion_pct
FROM
  (
    SELECT
      s.id,
      l.district_id,
      s.day_time - toInt32(l.published_at / 86400) AS listing_age_days,
      s.views,
      s.calls + s.msgs + s.whatsapp AS contacts
    FROM
      sadb_stats_listings_stats s FINAL
      JOIN sadb_listings l FINAL ON s.id = l.id
    WHERE
      toDate(s.day_time) BETWEEN '2025-10-14' AND '2026-01-13'
      AND l.published_at > 0
      AND s.day_time >= toInt32(l.published_at / 86400)
      AND l._peerdb_is_deleted = 0
      -- no status filter: listings that have since closed or been deleted are included
      AND (s.day_time - toInt32(l.published_at / 86400)) BETWEEN 0 AND 90
  ) t
  JOIN sadb_districts d FINAL ON t.district_id = d.district_id
WHERE
  d.city_name IN ('الرياض', 'جدة', 'الدمام', 'مكة المكرمة')
GROUP BY
  d.city_name,
  age_bucket
ORDER BY
  d.city_name,
  age_bucket

---

Business Implications

1. Listing Refresh Strategy

• Listings not converting by Day 30 are getting ~44% of peak traffic
• Consider automated refresh prompts at Day 14 and Day 30

2. Pricing Guidance

• If no contacts by Week 2, listing may be overpriced
• Sales listings (especially land) need pricing attention early

3. Category-Specific Strategies

• Rentals: High volume, maintain conversion - focus on response time
• Land Sales: Urgency-driven buyers - price aggressively early
• Villa Sales: Longer cycle expected - patience but monitor conversion

4. City-Specific Insights

• Riyadh: Fastest market, most competitive - quick response essential
• Makkah: Lowest traffic and fastest conversion decay - capture early (corrected: its Week 1 conversion is not the highest)
• Jeddah: Slower decay but lower baseline - quality over speed

---

Data Notes

• Analysis Period: 2024-01-01 onwards (regulatory changes make earlier data incomparable)
• View/Conversion Analysis: The 3 months to the original run date (2025-10-14 to 2026-01-13). No status filter, so listings that have since closed or been deleted are included (see the correction note).
• Time on Market: Filtered to 1-730 days (excludes outliers)
• day_time format: Days since Unix epoch (not Unix timestamp)
• published_at format: Unix timestamp (seconds)