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August 2025 - August 2026
Detailed observation of presented data
Israel’s cost-per-purchase trajectory told a story of momentum and sharp swings: lower than the global benchmark across the year, with an early autumn peak, a dramatic Q4 drop, a shallow winter trough, and a volatile spring rebound. This analysis is based on $3B worth of advertising data from our dataset, which provides strong directional benchmarks. This analysis explores ad performance trends for All industries available in Israel compared to the global benchmark.
For All industries in Israel, median cost per purchase averaged about 32.2 over the 12-month window (Jul 2025–Jun 2026). The Israeli series began at 39.62 in July 2025 and closed at 30.59 in June 2026, a net decline of roughly 23% from start to finish. The high point was 47.41 in October 2025; the low was 16.49 in May 2026. That peak-to-trough swing represents a roughly 65% fall from October to May.
Month-to-month moves were large: average absolute change between months was about 8.3 cost units. The single largest monthly swing was October→November (a 44.8% drop, from 47.41 to 26.18). Israel recorded several sharp rebounds (e.g., May→June +85.5%) and mid-season spikes (Aug→Oct climb into the October peak), producing an overall pattern of spikes and corrections rather than a steady trend.
By contrast, the global (baseline) median cost per purchase averaged about 49.9 over the same months, with a narrower range — a high of ~56.0 in March 2026 and a low of ~43.0 in June 2026. Global month-to-month moves averaged about 3.1 cost units, markedly calmer than Israel’s.
The Israeli series showed a classic autumn lift into October followed by an abrupt Q4 softening in November. November’s drop was followed by a partial recovery in December, a winter trough across January–February, then a spring recovery spike in March and volatile declines into April–May before a late rebound in June. May stood out as the softest month (16.49), interrupting a pattern of alternating rebounds and pullbacks.
The global pattern was more rhythmic: a build into a March peak and a gradual pullback toward June. Where the global rhythm suggested a single seasonal pulse into late winter, Israel’s rhythm was punctuated by steeper, less predictable swings across Q4 and late spring.
Across the year Israel’s median cost per purchase ran about 35% below the global median (32.2 vs. 49.9). Relative positioning varied: at its narrowest gap Israel was roughly 23% below the global level (periods around Jul–Oct when Israel climbed toward the peak); at its widest, Israel was about 66% below the global peak-to-trough comparison when local costs collapsed into May. Volatility-wise, Israel was roughly 2.7× more volatile than the global benchmark (average monthly absolute move ~8.3 vs ~3.1).
These differences underscore a market with lower average cost-per-purchase but higher month-to-month volatility compared with the global baseline — a pattern visible across All industries in Israel.
Understanding Facebook Ads Cost Per Purchase benchmarks for all industries in Israel helps advertisers compare country-specific ad costs and appraise industry ad performance versus global patterns.
Insights & analysis of Facebook advertising costs
Facebook advertising costs vary based on many factors including industry, target audience, ad placement, and campaign objectives. Different industries see varying ad costs due to market competition, user demographics, and conversion value. For campaigns targeting Israel, advertisers should consider local market factors and user behavior. Different campaign objectives lead to varying costs based on how Facebook optimizes for your specific goals. The data shown represents median values across multiple campaigns, and individual results may vary based on ad quality, audience targeting, and campaign optimization.
We use the median CTR because the underlying distribution of click-through rates is highly skewed, with a small share of campaigns achieving extremely high CTRs. These outliers can inflate a simple average, making it less representative of what most advertisers actually experience. By using the median—which sits at the midpoint of all campaigns—we provide a more rigorous and realistic benchmark that reflects the true underlying data model and helps you set attainable performance expectations.
Note: This data represents industry median values and benchmarks. Your actual costs may vary based on specific targeting, ad creative quality, and campaign optimization.
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All data is sourced from over $3B in Facebook ad spend, collected across thousands of ad accounts that use Superads daily to analyze and improve their campaigns. Every data point is fully anonymized and aggregated—no individual advertiser is ever exposed.
This dataset updates frequently as new ad data flows in. It will only get bigger and better.
Passover (April), Sukkot and Fall holidays (Sept–Oct), Hanukkah (December)
CPM and CPC might rise during Passover as consumers prepare homes and plan meals. Fall holiday cluster may see media consumption fluctuate—consumers often offline during holidays, but prior week advertising demand may peak. Yom HaAtzmaut might spark tourism and leisure engagement. Hanukkah could drive e‑commerce CPMs for toys and electronics.
It depends on your product price and margins. Most brands aim for $10 to $50. For higher-ticket products, a higher CPA may be acceptable as long as you're maintaining a strong return on ad spend.
Higher-priced products typically have a higher CPA because people take longer to convert. That's not necessarily a problem if your margin can support it. You should measure CPA in context with AOV and LTV.
Your AOV may be increasing, which helps maintain ROAS even if CPA rises. You could also be facing higher CPMs, lower conversion rates, or creative fatigue.
Manual bidding can help if you're struggling to stay within target CPA. It's best used by experienced advertisers who can monitor performance and adjust regularly. It gives more control, but also requires more effort.
Increase budget gradually, rotate creative often, and avoid overlapping audiences. Scaling too quickly can lead to audience saturation and rising CPAs.
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