SOV 7-Day Fixed Pricing Simulator

Date: 2026-05-14 Baseline: Trailing 12 months of chargeable SOV activity (sadb_sov_daily_biddings, status = 4, non_chargeable = false) Source: ClickHouse

This simulator estimates the platform-wide SOV revenue impact of replacing the current daily-bid system with a fixed 7-day package. Adjust the per-category base price, city multipliers, conversion mechanic, and adoption assumptions to explore scenarios live.

Note

Current model recap. Today, SOV is sold as a daily bid (median 30 SAR/day, very tight distribution). Median campaign runs 2 days, mean 3.1 days — so most listings spend 60–90 SAR per campaign. Across the trailing 12 months, this generated ~3.76M SAR from ~34.8k campaigns. (Stored in ClickHouse as halalahs; this page displays everything in SAR.)

How the mechanics work

• Ceil-blocks — Every existing campaign is re-priced as ceil(days / 7) 7-day blocks. Assumes 100% retention and that buyers willingly round up.
• One 7-day buy per campaign — Each existing campaign becomes exactly one 7-day purchase. Models a simplification where users buy the package once per intent.
• Adoption + uplift — Apply an adoption % (what fraction of current campaigns convert at all) and an optional new-buyer uplift % (extra buyers attracted by simpler pricing). Built on top of one of the two base mechanics above.

Loading simulator…

Assumptions & caveats

• All amounts on this page are in SAR. ClickHouse stores budget in halalahs (1 SAR = 100 halalahs), so the embedded baseline divides by 100. User-entered category prices and city multipliers are interpreted as SAR.
• Baseline counts only chargeable campaigns (status = 4, non_chargeable = false) — free/internal promotions are excluded.
• Campaign duration is summed by sov_campaign_id across calendar days; gaps in a campaign are treated as paused days and not double-counted.
• The ceil-blocks mechanic assumes a buyer who currently runs 8 days would buy two 7-day packages. In reality some will downsize to one. The adoption mechanic is the lever for that.
• City multipliers apply to all categories uniformly. Realistic pricing would differentiate further (e.g. Riyadh apartments vs Riyadh land) — extend the model if that becomes important.
• The simulation is a static re-pricing of the T12M campaign mix. It does not model second-order effects: bid competition disappearing, listings hiding behind cheaper SOV, or supply-side reaction.
• “Other cities” rolls up ~90 long-tail cities holding ~5% of revenue.

Source query

WITH campaigns AS (
  SELECT
    sov_campaign_id,
    any(listing_category) AS listing_category,
    any(city_id) AS city_id,
    count() AS days_active,
    sum(budget) AS total_spend
  FROM sadb_sov_daily_biddings FINAL
  WHERE _peerdb_is_deleted = 0
    AND status = 4
    AND non_chargeable = false
    AND toDate(start_datetime) >= today() - INTERVAL 365 DAY
  GROUP BY sov_campaign_id
),
classified AS (
  SELECT
    listing_category,
    multiIf(
      city_id = 21, 'riyadh',
      city_id = 66, 'jeddah',
      city_id = 12, 'khobar',
      city_id = 18, 'dammam',
      city_id = 41, 'madinah',
      city_id = 94, 'mecca',
      'other'
    ) AS city_tier,
    days_active,
    total_spend
  FROM campaigns
)
SELECT
  listing_category,
  city_tier,
  count() AS campaigns,
  sum(days_active) AS days,
  round(sum(total_spend) / 100, 2) AS revenue_sar,  -- halalahs → SAR
  sum(ceil(days_active / 7)) AS blocks_7d
FROM classified
GROUP BY listing_category, city_tier
ORDER BY listing_category, city_tier;