Bookings Supply & Demand Dynamics 2025

Date: 2026-01-20 Analysis Period: January - December 2025 Data Sources: sadb_listings, sadb_daily_renting_listing_bookings, sadb_daily_renting_listing_register, sadb_user_listing_views

Executive Summary

This analysis examines the supply-demand dynamics of Aqar’s daily rental (bookings) marketplace throughout 2025, focusing on inventory growth, demand patterns, and market equilibrium.

Key Metrics (2025)

Metric	Value	Trend
Total Bookings	22,052	+76% vs H2 2024
Gross Merchandise Value	SAR 5.15M	+103% vs 2024
Active Inventory (Dec)	7,481 listings	+39% from Jul
View-to-Booking Rate	0.52% avg	Stable
Nights Booked (2025)	263,787	-

Market Health Indicators

Indicator	Status	Assessment
Supply Growth	Strong	+39% inventory growth H2 2025
Demand Growth	Strong	Bookings peaked at 2,530 in September
Conversion Rate	Improving	0.70% in December (best month)
Market Balance	Riyadh-heavy	60% of bookings in one city

1. Supply Analysis

1.1 Inventory Growth

The bookings inventory grew significantly throughout 2025, with the availability register showing:

Month	Active Listings	Available Nights	Total Registered	Availability Rate
Jul 2025	5,391	75,816	89,543	84.7%
Aug 2025	5,896	145,138	173,240	83.8%
Sep 2025	6,366	160,711	184,342	87.2%
Oct 2025	6,838	176,695	205,247	86.1%
Nov 2025	7,129	174,108	209,905	83.0%
Dec 2025	7,481	191,446	226,905	84.4%

Growth Rate: +38.8% in active listings from July to December 2025

SELECT
  toStartOfMonth(toDate(r.day_date)) AS MONTH,
  count(DISTINCT r.listing_id) AS listings_in_inventory,
  countIf (r.availability = 1) AS available_nights,
  count(*) AS total_nights_registered,
  round(
    countIf (r.availability = 1) * 100.0 / count(*),
    2
  ) AS availability_rate
FROM
  sadb_daily_renting_listing_register r FINAL
WHERE
  r._peerdb_is_deleted = 0
  AND toYear(r.day_date) = 2025
GROUP BY
  MONTH
ORDER BY
  MONTH

1.2 New Listings by Category

Month	Apartments	Studios	Chalets	Villas	Tents	Farms
Jan 2025	514	182	58	22	9	3
Feb 2025	354	129	52	11	6	0
Mar 2025	371	142	124	6	1	4
Apr 2025	352	130	68	6	3	2
May 2025	339	118	58	4	0	5
Jun 2025	380	136	61	6	1	2
Jul 2025	346	150	44	11	4	2
Aug 2025	276	86	57	2	3	1
Sep 2025	302	106	44	9	5	2
Oct 2025	312	103	40	10	5	1
Nov 2025	178	56	33	8	9	4
Dec 2025	204	75	48	4	17	2

Key Finding: New supply slowed significantly in November (289 total) but recovered in December (352). Apartment and Studio categories dominate supply growth consistently.

1.3 Supply Retention

Not all new listings remain active. Here’s the survival rate:

Month Created	New Listings	Still Active	Retention Rate
Jan 2025	788	143	18.1%
Feb 2025	552	138	25.0%
Mar 2025	648	204	31.5%
Apr 2025	562	223	39.7%
May 2025	526	183	34.8%
Jun 2025	586	258	44.0%
Jul 2025	559	244	43.6%
Aug 2025	425	186	43.8%
Sep 2025	469	260	55.4%
Oct 2025	471	298	63.3%
Nov 2025	289	177	61.2%
Dec 2025	352	231	65.6%

Key Finding: Retention improves for newer listings (natural decay). Early 2025 cohorts show ~25-40% retention after 6+ months.

1.4 YoY Supply Comparison

Period	2024 New Listings	2025 New Listings	YoY Change
Q1	1,125	1,988	+76.7%
Q2	2,534	1,674	-34.0%
Q3	3,199	1,453	-54.6%
Q4	2,126	1,112	-47.7%

Key Finding: 2025 saw a significant slowdown in new supply compared to 2024’s rapid growth phase. This suggests market maturation or saturation in key areas.

2. Demand Analysis

2.1 Monthly Booking Trends

Month	Total Bookings	Completed	Canceled	Cancel Rate	GMV (SAR)	Avg Value
Jan	1,021	181	72	7.1%	288,761	283
Feb	1,385	190	55	4.0%	406,618	294
Mar	2,076	175	107	5.2%	309,869	149
Apr	1,673	208	83	5.0%	470,556	281
May	1,711	215	64	3.7%	429,145	251
Jun	1,612	178	52	3.2%	466,640	289
Jul	2,352	242	84	3.6%	541,447	230
Aug	2,246	223	69	3.1%	404,828	180
Sep	2,530	164	48	1.9%	330,478	131
Oct	1,606	162	58	3.6%	350,730	218
Nov	2,345	244	210	9.0%	817,301	349
Dec	1,495	145	58	3.9%	337,853	226

Seasonality Patterns:

Peak Months: July (2,352), September (2,530), November (2,345)
Trough Months: January (1,021), December (1,495)
Best GMV Month: November (SAR 817K) - likely driven by National Day events

2.2 Stay Duration Analysis (Nights Booked)

Month	Bookings	Total Nights	Unique Listings	Avg Stay
Jan	1,123	8,392	626	7.5
Feb	1,183	12,054	595	10.2
Mar	1,810	17,470	825	9.7
Apr	1,720	19,733	836	11.5
May	1,465	18,333	783	12.5
Jun	1,628	20,537	864	12.6
Jul	2,213	27,187	1,066	12.3
Aug	2,256	26,184	1,073	11.6
Sep	2,142	37,739	1,048	17.6
Oct	1,860	34,444	1,002	18.5
Nov	2,101	22,751	1,101	10.8
Dec	1,465	18,963	852	12.9

Key Finding: September and October have the longest average stays (17-18 nights), suggesting corporate/relocation demand in these months.

2.3 Booking Category Performance

Category	Bookings	Completed	GMV (SAR)	Avg Value	Avg Stay
Apartment	13,231	1,402	3,890,348	294	14.8 nights
Studio	5,169	694	929,132	180	13.0 nights
Chalet	3,172	197	226,279	71	2.3 nights
Villa	321	15	90,345	281	10.7 nights
Tent	128	15	12,107	95	1.8 nights
Farm	28	4	6,016	215	2.1 nights

Key Finding: Apartments and Studios dominate with 84% of bookings and 93% of GMV. Chalets have high volume but very short stays (weekend use case).

3. Supply-Demand Balance

3.1 Views-to-Booking Funnel

Month	Views	Bookings	Conversion	Listings Viewed	Listings Booked
Jan	228,246	1,021	0.45%	3,894	537
Feb	281,024	1,385	0.49%	3,229	655
Mar	316,525	2,076	0.66%	3,535	837
Apr	346,826	1,673	0.48%	3,687	819
May	360,351	1,711	0.47%	3,782	855
Jun	391,390	1,612	0.41%	3,977	860
Jul	461,396	2,352	0.51%	4,272	1,085
Aug	466,982	2,246	0.48%	4,333	1,073
Sep	369,521	2,530	0.68%	4,300	1,130
Oct	345,753	1,606	0.46%	4,424	902
Nov	362,229	2,345	0.65%	4,507	1,173
Dec	213,840	1,495	0.70%	4,387	834

Key Finding: December achieved the highest conversion rate (0.70%) despite lowest views, indicating more qualified traffic during holiday season.

WITH
  monthly_views AS (
    SELECT
      toStartOfMonth(toDate(v.createdAt)) AS MONTH,
      count(*) AS views,
      count(DISTINCT v.listing_id) AS listings_viewed
    FROM
      sadb_user_listing_views v FINAL
      JOIN sadb_listings l FINAL ON v.listing_id = l.id
    WHERE
      l.daily_rentable = 1
      AND v._peerdb_is_deleted = 0
      AND l._peerdb_is_deleted = 0
      AND toYear(v.createdAt) = 2025
    GROUP BY
      MONTH
  ),
  monthly_bookings AS (
    SELECT
      toStartOfMonth(toDate(b.createdAt)) AS MONTH,
      count(*) AS bookings,
      count(DISTINCT b.listing_id) AS listings_booked,
      round(sum(b.total_amount), 0) AS gmv
    FROM
      sadb_daily_renting_listing_bookings b FINAL
    WHERE
      b._peerdb_is_deleted = 0
      AND toYear(b.createdAt) = 2025
    GROUP BY
      MONTH
  )
SELECT
  v.month,
  v.views,
  b.bookings,
  round(b.bookings * 100.0 / v.views, 2) AS view_to_booking_rate,
  b.gmv
FROM
  monthly_views v
  JOIN monthly_bookings b ON v.month = b.month
ORDER BY
  v.month

3.2 City-Level Supply-Demand

City	Active Listings	Bookings	GMV (SAR)	Booked Listings	Utilization	Bookings/Listing
Riyadh	2,024	13,311	4,032,354	2,559	126.4%	6.6
Jeddah	596	3,665	524,557	692	116.1%	6.1
Khobar	126	812	117,761	166	131.7%	6.4
Dammam	110	812	116,846	139	126.4%	7.4
Madinah	101	661	116,038	148	146.5%	6.5
Abha	80	494	59,768	84	105.0%	6.2
Taif	100	473	47,089	100	100.0%	4.7
Diriyah	18	132	38,949	25	138.9%	7.3
Buraydah	38	362	35,798	71	186.8%	9.5
Bahah	20	90	9,030	20	100.0%	4.5

Key Findings:

Riyadh dominates: 60% of all bookings, 78% of GMV
Undersupplied markets: Buraydah (9.5 bookings/listing), Dammam (7.4), Diriyah (7.3)
Oversupplied markets: Taif (4.7), Bahah (4.5)

Note: Utilization >100% means bookings came from listings that have since become inactive.

3.3 Pricing by Category

Category	Avg Daily Price	Median Price	P25	P75
Hall	SAR 5,447	SAR 9,358	SAR 66	SAR 9,358
Farm	SAR 4,122	SAR 1,101	SAR 771	SAR 2,202
Villa	SAR 3,509	SAR 1,046	SAR 720	SAR 1,651
Chalet	SAR 2,031	SAR 840	SAR 550	SAR 1,320
Apartment	SAR 1,058	SAR 371	SAR 275	SAR 550
Studio	SAR 956	SAR 275	SAR 210	SAR 330
Tent	SAR 910	SAR 716	SAR 440	SAR 1,101

4. User Behavior Patterns

4.1 Repeat Booker Analysis

Booking Frequency	Users	% of Users
1 booking	9,303	71.2%
2 bookings	2,071	15.8%
3-5 bookings	1,338	10.2%
6+ bookings	358	2.7%

Key Finding: 28.8% of users are repeat bookers, indicating moderate retention. Power users (6+ bookings) represent high-value segment to nurture.

4.2 Weekend vs Weekday Patterns

Start Day Type	Bookings	Avg Value	Avg Stay
Weekday Start	14,493	SAR 232	13.2 nights
Weekend Start (Thu-Fri)	6,599	SAR 208	11.9 nights

Key Finding: Weekday bookings have higher value (+12%) and longer stays, indicating business/relocation use cases. Weekend bookings are leisure-focused.

4.3 Cancellation Patterns

Month	Cancel Rate	Canceled by Host	Canceled by Guest
Jan	7.1%	-	-
Feb	4.0%	-	-
Mar	5.2%	-	-
Apr	5.0%	-	-
May	3.7%	-	-
Jun	3.2%	-	-
Jul	3.6%	-	-
Aug	3.1%	-	-
Sep	1.9%	-	-
Oct	3.6%	-	-
Nov	9.0%	-	-
Dec	3.9%	-	-

Key Finding: November had an unusually high cancellation rate (9.0%), likely due to National Day booking conflicts or speculative bookings.

5. Key Insights & Recommendations

Supply Side

Inventory growth is healthy (+39% H2 2025), but new listing creation slowed vs 2024
Retention needs work - only 25-40% of listings remain active after 6 months
Geographic concentration risk - Riyadh has 60%+ of activity

Demand Side

Clear seasonality - Summer (Jul-Aug) and late autumn (Nov) are peak periods
Long-stay segment is growing - September/October saw 17-18 night average stays
Conversion improving - December hit 0.70% view-to-booking rate

Market Balance

Undersupplied cities: Buraydah, Dammam, Diriyah need more inventory
Oversupplied cities: Taif, Bahah may have excess capacity
Riyadh is critical - 78% of GMV, must maintain supply quality

Recommended Actions

Priority	Action	Rationale
High	Acquire supply in Buraydah	9.5 bookings/listing indicates unmet demand
High	Improve listing retention	25-40% survival rate leaves value on table
Medium	Diversify outside Riyadh	78% GMV concentration is business risk
Medium	Target long-stay segment	Sep/Oct shows corporate relocation demand
Low	Investigate November cancellations	9% cancel rate is 3x normal

Appendix: SQL Queries

Monthly Supply Growth

SELECT
  toStartOfMonth(toDate(FROM_UNIXTIME(l.create_time))) AS created_month,
  c.name_en AS category,
  count(DISTINCT l.id) AS new_listings,
  countIf (
    l.status IN (0, 4)
    AND l.published = 1
    AND l.hidden = 0
  ) AS still_active
FROM
  sadb_listings l FINAL
  JOIN sadb_categories c FINAL ON l.category = c.category_id
WHERE
  l.daily_rentable = 1
  AND l._peerdb_is_deleted = 0
  AND toYear(FROM_UNIXTIME(l.create_time)) = 2025
GROUP BY
  created_month,
  c.name_en
ORDER BY
  created_month,
  new_listings DESC

City Supply-Demand Balance

WITH
  supply AS (
    SELECT
      d.city_name,
      count(DISTINCT l.id) AS total_listings,
      countIf (
        l.status IN (0, 4)
        AND l.published = 1
        AND l.hidden = 0
      ) AS active_listings
    FROM
      sadb_listings l FINAL
      JOIN sadb_districts d FINAL ON l.district_id = d.district_id
    WHERE
      l.daily_rentable = 1
      AND l._peerdb_is_deleted = 0
    GROUP BY
      d.city_name
  ),
  demand AS (
    SELECT
      d.city_name,
      count(*) AS total_bookings,
      round(sum(b.total_amount), 0) AS gmv,
      count(DISTINCT b.listing_id) AS listings_with_bookings
    FROM
      sadb_daily_renting_listing_bookings b FINAL
      JOIN sadb_listings l FINAL ON b.listing_id = l.id
      JOIN sadb_districts d FINAL ON l.district_id = d.district_id
    WHERE
      b._peerdb_is_deleted = 0
      AND l._peerdb_is_deleted = 0
      AND toYear(b.createdAt) = 2025
    GROUP BY
      d.city_name
  )
SELECT
  s.city_name,
  s.active_listings,
  COALESCE(d.total_bookings, 0) AS total_bookings,
  COALESCE(d.gmv, 0) AS total_gmv,
  round(
    COALESCE(d.total_bookings, 0) * 1.0 / s.active_listings,
    1
  ) AS bookings_per_listing
FROM
  supply s
  LEFT JOIN demand d ON s.city_name = d.city_name
WHERE
  s.active_listings > 10
ORDER BY
  total_gmv DESC