Rent vs Booking Apartment User Overlap

Date: 2026-02-16 Analysis Period: Nov 17, 2025 – Feb 16, 2026 (limited by sadb_user_listing_event_logs retention) Data Source: sadb_user_listing_event_logs (logged-in user views only)

Executive Summary

This analysis examines the overlap between logged-in users who view Apartments for Rent (category 1, monthly rental listings) and Apartments for Booking (category 101, short-term bookable units). The goal is to understand whether these are distinct audiences or the same users exploring both options.

Key Findings

Metric	Value
Apartment for Rent viewers	701,882
Apartment for Booking viewers	67,363
Overlap (viewed both)	53,316
% of booking viewers who also view rent	79.2%
% of rent viewers who also view bookings	7.6%

The booking audience is largely a subset of the rent audience. Nearly 4 in 5 users who browse bookable apartments also browse traditional rental listings, while booking is a niche interest for rent viewers.

User Segments

Segment	Users	% of Total
Rent Only	648,566	90.6%
Both (Overlap)	53,316	7.4%
Booking Only	14,047	2.0%

Only ~14K users exclusively browse booking apartments without also looking at rental listings. The “booking-only” audience is very small.

Overlap by City

City	Rent Users	Booking Users	Overlap	% Booking→Rent	% Rent→Booking
الرياض (Riyadh)	410,981	37,100	27,509	74.1%	6.7%
جدة (Jeddah)	133,697	11,848	7,580	64.0%	5.7%
الخبر (Khobar)	68,277	5,892	3,041	51.6%	4.5%
الدمام (Dammam)	79,402	4,948	3,475	70.2%	4.4%
المدينة المنورة (Madinah)	31,578	3,378	1,767	52.3%	5.6%
بريدة (Buraydah)	16,259	2,538	1,051	41.4%	6.5%
مكة المكرمة (Makkah)	22,499	1,754	957	54.6%	4.3%
الطائف (Taif)	9,160	1,111	458	41.2%	5.0%
ابها (Abha)	11,844	904	497	55.0%	4.2%
الهفوف (Hofuf)	13,872	752	535	71.1%	3.9%

Notable patterns:

Riyadh dominates booking demand with 55% of all booking viewers
Al Jubail has the highest overlap rate at 75.1% — suggesting booking supply doesn’t meet demand there
Buraydah and Taif have the lowest overlap (~41%) — indicating more distinct booking-focused audiences, likely driven by tourism/recreation

User Journey Direction

Among the 53,316 overlap users, which category did they explore first?

Journey	Users	%
Rent first → then Booking	27,440	51.5%
Same day	16,480	30.9%
Booking first → then Rent	9,396	17.6%

Over half of overlap users start with rental browsing and later discover bookings. This suggests bookings are a secondary consideration for most users — they come to Aqar for rentals and then explore short-term options.

Engagement Depth by Segment

Metric	Rent Only	Both	Booking Only
Users	648,566	53,316	14,047
Avg views	81.3	170.1	32.7
Avg phone actions	2.04	4.00	0.57
Avg WhatsApp actions	3.35	6.29	0.72
Avg 30s+ sessions	21.27	42.63	8.80
% making any contact	37.9%	51.5%	57.1%

Key observations:

Overlap users are power users — 2x the views, 2x the contact actions, and 2x the session depth vs rent-only users
Booking-only users have the highest contact rate (57.1%) but lowest absolute engagement — they tend to be purpose-driven with fewer but more targeted views
Overlap users are the most valuable segment with both high volume and high conversion

Engagement Patterns Among Overlap Users

Pattern	Users	%	Avg Rent Views	Avg Booking Views
Heavy Rent, Light Booking	32,682	61.3%	118.5	2.6
Light Both	13,995	26.2%	4.2	2.4
Heavy Both (10+ each)	5,200	9.8%	170.2	26.3
Light Rent, Heavy Booking	1,439	2.7%	4.1	21.9

61% of overlap users are primarily rental browsers who casually explore bookings (averaging just 2.6 booking views). Only ~10% are deeply engaged with both categories.

Weekly Trends

Week	Rent Viewers	Booking Viewers	Booking as % of Rent
Nov 16, 2025	117,284	9,601	8.2%
Nov 23	138,489	12,162	8.8%
Nov 30	144,133	11,281	7.8%
Dec 7	138,844	9,900	7.1%
Dec 14	139,538	5,987	4.3%
Dec 21	148,454	5,591	3.8%
Dec 28	144,660	4,993	3.5%
Jan 4, 2026	142,787	4,720	3.3%
Jan 11	145,447	4,207	2.9%
Jan 18	155,522	4,649	3.0%
Jan 25	150,487	4,515	3.0%
Feb 1	147,406	5,999	4.1%
Feb 8	143,402	4,953	3.5%

Notable: Booking viewership peaked in late November 2025 and declined through January — this could be seasonal (post-holiday travel demand) or related to supply changes.

Booking Conversion Rates by Segment

Note on booking status classification: CLOSED_NOT_PAID represents a booking attempt where payment was never completed. These are counted as attempted bookings, not actual bookings. Only CONFIRMED and COMPLETED are counted as actual bookings.

Full Funnel: View → Attempt → Booking

Stage	Overlap	Booking Only
Booking listing viewers	53,713	14,114
Attempted booking (CLOSED_NOT_PAID)	1,530 (2.85%)	586 (4.15%)
Actual booking (CONFIRMED/COMPLETED)	176 (0.33%)	89 (0.63%)
Attempt → Booking conversion	11.5%	15.2%

Booking-only users convert at ~2x the rate at every stage of the funnel. They are 1.5x more likely to attempt a booking (4.15% vs 2.85%), and among those who attempt, they are 1.3x more likely to successfully complete payment (15.2% vs 11.5%).

Booking Attempts vs Actual Bookings

The vast majority of booking interactions are attempted bookings that fail at payment:

Metric	Total	Overlap	Booking Only	Other*
Attempted bookings (CLOSED_NOT_PAID)	2,722 users	1,530 (56%)	586 (22%)	606 (22%)
Actual bookings (CONFIRMED/COMPLETED)	332 users	176 (53%)	89 (27%)	67 (20%)

*Other = users with rent-only views or no booking category views in event logs

For every user who successfully books, roughly 8 users attempt but fail at payment. This ratio is consistent across segments, making the payment funnel the single largest conversion bottleneck.

Conversion by City

City	Segment	Viewers	Attempters	Bookers
الرياض (Riyadh)	Overlap	27,646	865 (3.1%)	127 (0.46%)
	Booking Only	9,651	321 (3.3%)	60 (0.62%)
جدة (Jeddah)	Overlap	7,608	277 (3.6%)	20 (0.26%)
	Booking Only	4,291	109 (2.5%)	15 (0.35%)
الدمام (Dammam)	Overlap	3,491	89 (2.5%)	2 (0.06%)
	Booking Only	1,475	16 (1.1%)	3 (0.20%)
المدينة المنورة (Madinah)	Overlap	1,776	86 (4.8%)	9 (0.51%)
	Booking Only	1,635	48 (2.9%)	4 (0.24%)
الخبر (Khobar)	Overlap	3,054	84 (2.8%)	8 (0.26%)
	Booking Only	2,872	27 (0.9%)	3 (0.10%)

Riyadh dominates with 70%+ of all booking attempts and completions. The booking-only advantage in actual booking rate is consistent in Riyadh (0.62% vs 0.46%) and Jeddah (0.35% vs 0.26%).

Implications

Cross-sell opportunity is real but asymmetric — 79% of booking users already browse rentals, but only 7.6% of rental users explore bookings. There’s a large untapped pool of rental browsers who could be surfaced booking options.
Overlap users are the most engaged and valuable — they view 2x more listings and make 2x more contacts. Identifying and nurturing this segment could drive significant engagement gains.
Most overlap is casual — 61% of overlap users are heavy rental browsers who glance at bookings (avg 2.6 views). Better booking discovery within the rental journey could convert these casual explorers.
Booking-only users are purpose-driven — small audience (14K) but highest contact rate (57.1%). These users know what they want and convert efficiently.
City-level variation matters — tourism/recreation cities (Buraydah, Taif) have more distinct booking audiences, while business cities (Riyadh, Dammam) show higher overlap, suggesting different use cases.
Booking-only users convert at 2x the rate — 0.63% vs 0.33% successful booking rate. They’re purpose-driven and more prepared to complete transactions.
Payment failure is the #1 conversion blocker — for every successful booking, ~8 users attempt but fail at payment (CLOSED_NOT_PAID). Fixing the payment funnel would have a far greater impact on bookings than improving discovery or user targeting.

SQL Queries Used

User segment counts

SELECT
  CASE
    WHEN viewed_rent
    AND viewed_booking THEN 'Both'
    WHEN viewed_rent THEN 'Rent Only'
    ELSE 'Booking Only'
  END as segment,
  count() as users
FROM
  (
    SELECT
      user_id,
      countIf (category = 1) > 0 as viewed_rent,
      countIf (category = 101) > 0 as viewed_booking
    FROM
      sadb_user_listing_event_logs
    WHERE
    type
      = 'view'
      AND category IN (1, 101)
      AND toDate(createdAt) >= '2024-01-01'
      AND user_id > 0
      AND _peerdb_is_deleted = 0
    GROUP BY
      user_id
  )
GROUP BY
  segment

Per-city overlap

SELECT
  city_name,
  countIf (
    viewed_rent
    AND viewed_booking
  ) as overlap_users,
  countIf (viewed_rent) as total_rent_users,
  countIf (viewed_booking) as total_booking_users,
  round(
    countIf (
      viewed_rent
      AND viewed_booking
    ) / countIf (viewed_booking) * 100,
    1
  ) as pct_booking_also_rent
FROM
  (
    SELECT
      e.user_id,
      e.city_id,
      countIf (e.category = 1) > 0 as viewed_rent,
      countIf (e.category = 101) > 0 as viewed_booking
    FROM
      sadb_user_listing_event_logs e
    WHERE
      e.type = 'view'
      AND e.category IN (1, 101)
      AND toDate(e.createdAt) >= '2024-01-01'
      AND e.user_id > 0
      AND e._peerdb_is_deleted = 0
    GROUP BY
      e.user_id,
      e.city_id
  ) sub
  JOIN (
    SELECT DISTINCT
      city_id,
      city_name
    FROM
      sadb_districts FINAL
    WHERE
      _peerdb_is_deleted = 0
  ) cities ON sub.city_id = cities.city_id
GROUP BY
  city_name
HAVING
  total_booking_users > 100
ORDER BY
  total_booking_users DESC

Booking conversion by segment

-- Attempted bookings = CLOSED_NOT_PAID (payment never completed)
-- Actual bookings = CONFIRMED or COMPLETED only
-- Step 1: classify bookers/attempters by their viewer segment
SELECT
  CASE
    WHEN viewed_rent
    AND viewed_booking THEN 'Overlap'
    WHEN viewed_booking THEN 'Booking Only'
    WHEN viewed_rent THEN 'Rent Only'
    ELSE 'No booking category views'
  END as segment,
  count() as users
FROM
  (
    SELECT
      b.user_id,
      countIf (
        e.category = 1
        AND e.type = 'view'
      ) > 0 as viewed_rent,
      countIf (
        e.category = 101
        AND e.type = 'view'
      ) > 0 as viewed_booking
    FROM
      (
        SELECT DISTINCT
          user_id
        FROM
          sadb_daily_renting_listing_bookings
        WHERE
          _peerdb_is_deleted = 0
          AND user_id > 0
          AND status IN ('CONFIRMED', 'COMPLETED') -- or 'CLOSED_NOT_PAID' for attempts
          AND toDate(createdAt) >= '2025-11-17'
      ) b
      LEFT JOIN sadb_user_listing_event_logs e ON b.user_id = e.user_id
      AND e._peerdb_is_deleted = 0
    GROUP BY
      b.user_id
  )
GROUP BY
  segment
  -- Step 2: compute rates using viewer segment counts as denominators

Journey direction

SELECT
  CASE
    WHEN first_rent < first_booking THEN 'Rent first → Booking'
    WHEN first_booking < first_rent THEN 'Booking first → Rent'
    ELSE 'Same day'
  END as journey_direction,
  count() as users
FROM
  (
    SELECT
      user_id,
      minIf (toDate(createdAt), category = 1) as first_rent,
      minIf (toDate(createdAt), category = 101) as first_booking
    FROM
      sadb_user_listing_event_logs
    WHERE
    type
      = 'view'
      AND category IN (1, 101)
      AND toDate(createdAt) >= '2024-01-01'
      AND user_id > 0
      AND _peerdb_is_deleted = 0
    GROUP BY
      user_id
    HAVING
      countIf (category = 1) > 0
      AND countIf (category = 101) > 0
  )
GROUP BY
  journey_direction