See how your purchase costs compare. Explore ecommerce conversion cost benchmarks by industry, region, and campaign type
July 2025 - July 2026
Detailed observation of presented data
The headline: India’s Cost Per Purchase profile in 2025–early 2026 ran well below the global benchmark for most of the year, then erupted into an extreme outlier in April 2026. 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 in India compared to the global benchmark.
COST_PER_PURCHASE in India started very low in June 2025 at roughly 3.92 and finished at a striking 193.81 in April 2026. Across the 11-month window (Jun 2025–Apr 2026) the India series averaged about 34.9, versus a global baseline average of roughly 50.5 — about 31% lower on average. Still, that average masks dramatic swings: the month-to-month low was 3.13 in July 2025 and the peak was 193.81 in April 2026.
Key movements: a quiet start (June–July under 4), a steady lift through October and a notable November bump to ~34.48. After a winter dip (December–January back toward mid-teens), February rose to ~41.26, March eased to ~16.39, then April jumped more than tenfold from March (+~1,083% month-over-month) to 193.8. Over the full span, India’s COST_PER_PURCHASE rose roughly 4,845% from its June 2025 base to the April 2026 peak.
Volatility was pronounced. Average absolute monthly change in value was about 28.1 (currency units), versus about 2.7 for the global benchmark — roughly a 10x difference. Measured in percent, India’s average absolute month-to-month swing was ~181%, compared with ~5% for the baseline, underlining how choppier India’s cost dynamics were across the year.
The rhythm shows a low-cost summer (June–July), a progressive increase through Q3 and into Q4, peaking in November for the India series before a classic year-end-to-Q1 softening in December–January. February saw a rebound toward the baseline, March cooled again, and April produced an anomalous spike unlike any other month in the sample. The baseline trace is far steadier: the global series sits mostly in the high-40s to mid-50s range with modest seasonal lifts in late Q4 and small Q1 bumps and dips, while India’s pattern reads as bursts and troughs punctuated by one extreme outlier.
India trailed the global COST_PER_PURCHASE for most months — dramatically so early on. In June–July 2025 India was over 90% below the global benchmark. At its narrowest gap, India was roughly 18% below the baseline in February 2026. At its widest, April 2026 flipped the story: India’s cost was nearly 3x the global baseline (about +292% relative to the benchmark). In short, “below average” described the majority of months, but an extreme April 2026 outlier made the year’s distribution heavily skewed. This contrast highlights significant country-specific ad costs variability compared to the steady global CPM/CTR and CPC trends embedded in the baseline.
Understanding Facebook Ads Cost Per Purchase benchmarks for all industries in India gives a clear view of how country-specific ad costs and industry ad performance can diverge from global CPM analysis, CPC trends, and CTR performance expectations.
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 India, 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.
October (Diwali), Late November (Black Friday/Cyber Monday), December (Christmas), July–August (Raksha Bandhan, Ganesh Chaturthi)
CPMs might spike significantly during Diwali, especially in electronics, apparel, jewellery, and gifts. Black Friday/Cyber Monday and December could drive elevated ad competition. State-specific festivals might see regional campaign spikes. Bank closures during holidays may push online shopping to cluster in end-of-week periods.
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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