Introduction

iOS market share in India is smaller than Android, but users tend to have higher average revenue per user (ARPU) and lifetime value, which makes paid acquisition on the App Store cost-effective when campaigns are properly targeted.

This article covers what Apple Search Ads offers in India, how to build keyword-driven campaigns, real bid and budget examples, and a 30- to 90-day testing timeline you can run tomorrow. It explains auction mechanics, keyword match types, creative sets, and measurement using common mobile attribution platforms. If you manage user acquisition, product growth, or ad operations, you will get checklists, sample calculations, and tools to reduce wasted spend and increase installs that convert.

Read on for step-by-step setup, benchmark figures and formulas for cost per install (CPI) and return on ad spend (ROAS), and a practical testing plan you can implement using App Store Connect, Apple Search Ads Advanced, and common attribution tools.

What Apple Search Ads is and How It Works

Apple Search Ads (ASA) is a search advertising product that places your app at the top of App Store search results. There are two main product tiers: Basic and Advanced. Basic is simplified and price-per-install (PPI) driven, while Advanced uses an auction model where you set cost-per-tap (CPT) bids and control keywords, ad groups, and audiences.

iOS user base in India concentrates in metro and tier-1 cities and in higher income brackets, so ARPU can be multiple times the national average for Android. That changes how you should pick keywords and set bids.

Auction mechanics in Advanced:

• You choose keywords and match types: broad, exact, and search match (Apple’s automatic matching).
• Bids are cost-per-tap, not cost-per-install. You pay when a user taps your ad.
• Apple uses relevance and bid to determine placement; higher relevance reduces effective CPT.
• You can set demographics and device filters through audience refinements.

Key performance metrics to track:

• Tap-through rate (TTR): taps divided by impressions.
• Tap-to-install conversion: installs divided by taps.
• Cost per install (CPI): CPT divided by conversion rate, or total spend divided by installs.
• Return on ad spend (ROAS) and lifetime value (LTV): measured with attribution providers like Adjust or AppsFlyer.

Example numbers for planning:

• If average CPT in India for a category is INR 8 and tap-to-install conversion is 25 percent, estimated CPI = INR 8 / 0.25 = INR 32.
• With a first-week LTV of INR 100, estimated payback exists if CPI < INR 100.

These mechanics make Apple Search Ads a highly measurable, keyword-driven acquisition channel that often yields higher-quality users than many programmatic channels.

Apple Search Ads India - Market Strategy and Keyword Tactics

Treat Apple Search Ads India as a keyword marketplace where urban, high-ARPU users are the primary inventory. Keyword choice must balance relevance, search volume, and bid competitiveness.

Audience and market considerations:

• iOS users in India skew to metro areas and premium device users. Prioritize keywords and categories that map to monetizable behaviors like subscriptions, e-commerce, education, travel, or fintech.
• Local language searches are rising, but English still dominates App Store queries among iOS users in India. Test localized keywords in Hindi, Tamil, or regional languages only after you have baseline English performance.
• Seasonality matters: festival periods like Diwali, wedding season, and major sporting events can spike search queries for certain categories.

Keyword selection process:

1. Start with store listing and competitor analysis. Export keywords from App Store Connect and tools like Sensor Tower or App Annie to get search volume estimates.
2. Build keyword buckets: brand, competitor, category, intent, feature, and long-tail. 3. Prioritize keywords by projected LTV-adjusted bid. Example calculation:

• Expected first-week LTV = INR 120
• Target payback ratio = 0.5 (spend must be <= 50% of first-week LTV)
• Max CPI = INR 120 * 0.5 = INR 60
• If historical tap-to-install = 30%, max CPT = 0.3 * INR 60 = INR 18

Match types and strategy:

• Exact match for high-intent keywords like “tax filing app” or “fitness tracker” yields lower wasted spend and higher conversion rates.
• Broad match and Search Match for discovery and volume expansion, paired with negative keywords to block irrelevant searches.
• Regularly run Search Match for new keyword discovery and then add high-performing queries as exact-match keywords with controlled bids.

Bid and budget setting:

• Start with conservative CPTs and increase based on conversion and ROAS. For example, begin with CPT = INR 6-12 for non-brand keywords, monitor conversion, and iterate.
• Daily budget suggestion for a test cohort: INR 1,000-5,000 per campaign for 30 days to gather meaningful data. Scale winners by 2x-3x when 7-day ROAS is positive.

Creative and listing alignment:

• Use Creative Sets in ASA Advanced to test screenshots and app preview variants tied to specific keywords.
• Update App Store metadata and Custom Product Pages to align with top-performing keywords to improve relevance and reduce effective CPT.

Examples:

• A food delivery app targeting “food delivery near me” might run exact-match bids at CPT INR 10, expect tap-to-install 20 percent, and CPI INR 50. With promo codes and first-order LTV of INR 200, this is profitable.
• An education app targeting “GMAT prep” may see lower volume but higher ARPU; CPT INR 25 with conversion 30 percent yields CPI INR 83, which fits ARPU = INR 300.

How to Set Up, Optimize, and Scale Campaigns

This section gives a step-by-step playbook from account setup to scale. Plan your first 30 days for exploration and the next 60 days for optimization and scaling.

Account setup checklist:

• Create or use an Apple ID with access to App Store Connect and Apple Search Ads.
• Link Apple Search Ads to App Store Connect to enable attribution and creative assets.
• Connect an attribution provider like Adjust, AppsFlyer, or Branch for post-install event tracking and ROAS measurement.

Initial campaign structure:

• Campaign 1: Brand keywords (exact match) - low CPT, high conversion, control bids tightly.
• Campaign 2: Competitor keywords (exact & broad) - moderate CPT, monitor legal/brand policies.
• Campaign 3: Generic/category keywords (exact & broad) - test volume and creatives.
• Campaign 4: Discovery using Search Match and broad match with negative keywords - for expansion.

30-day testing timeline:

• Days 1-7: Run brand and a mix of exact and Search Match for category keywords. Daily budget low but stable to gather impressions.
• Days 8-15: Add creative sets and Custom Product Pages. Start attribution event wiring for first-purchase or subscription.
• Days 16-30: Pause broad queries that produce low conversion. Shift budget to keywords with CPI below your target.

Optimization levers:

• Keywords: raise bid by 10-20 percent on top performers, pause low-converters daily, add negatives for poor queries.
• Creative: test 2-3 screenshot variants per Creative Set. Implement winners in App Store listing after 7-14 days if lift is consistent.
• Audience refinements: target device type (iPhone models), age brackets, or customer types relevant to your app. Example: target iPhone 12+ users for a high-graphics game.
• Scheduling: use dayparting if your app sees time-of-day spikes. For example, educational apps may convert better in evenings.

Sample scaling rule:

• If a keyword delivers CPI <= Target CPI and minimum 100 taps in 14 days, increase daily budget by 50 percent and CPT by 10 percent. Re-evaluate after 7 days.

Example math:

• Daily budget = INR 3,000, CPT = INR 10, expected taps = 300, expected installs at 25 percent = 75 installs, daily CPI = INR 3,000 / 75 = INR 40.
• If target CPI is INR 60 and 7-day ARPU is INR 150, scale by 2x.

Reporting and attribution:

• Track installs, cost, revenue events, and ROAS in AppsFlyer or Adjust.
• Use cohort analysis (D0, D7, D30) to determine payback period.
• Export ASA search term reports weekly and add high-performing terms as exact-match keywords.

Measurement, Budgets, and Scaling Timelines

Good measurement and disciplined budgeting separate profitable ASA programs from wasted spend. This section covers budgets, forecast formulas, and a 90-day scale plan.

Budgeting rules:

• Use a test budget that provides statistical significance. Rule of thumb: aim for 300-500 taps per keyword bucket during the test phase.
• Minimum recommended spend for a meaningful test in India: INR 30,000-75,000 over 30 days for one product line, split across brand, competitor, and category campaigns.
• Allocate budget as 20/30/50 across brand/competitor/category in initial phase, then reallocate to winners.

CPI and ROAS forecasting:

• Formula for CPI: CPI = Total spend / Installs.
• Formula for estimated CPI from CPT and conversion rate: CPI = CPT / (tap-to-install conversion rate).
• Sample forecast:
• CPT = INR 12
• Tap-to-install = 30 percent
• CPI = INR 40
• If average revenue per paying user (ARPPU) first 7 days = INR 120 and conversion to paying user = 10 percent, expected revenue per install in D7 = INR 12, so ROAS D7 = 12 / 40 = 0.3.
• Use D30 or LTV estimates to determine break-even.

Scaling timeline (90 days):

• Phase 1 (0-30 days): Discovery and baseline. Gather keyword performance, creative lifts, and conversion rates.
• Phase 2 (31-60 days): Optimize winners, test audience refinements, and implement Custom Product Pages for top keywords.
• Phase 3 (61-90 days): Scale winning campaigns by 2x-5x, expand to new keyword clusters, and lock in bidding strategies based on LTV cohort data.

Control and risk management:

• Cap bids and daily budgets per campaign to avoid runaway spend. Set an alert for spend rate and CPI deviation of +/- 25 percent.
• Use negative keyword lists to prevent irrelevant queries. Update weekly.
• If a campaign shows deteriorating conversion rates or rising CPT with stagnant installs, reduce bids by 20 percent and re-evaluate creatives.

Examples to illustrate:

• Gaming app: Test budget INR 50,000 over 30 days. Results show category keywords CPT INR 15, tap-to-install 20 percent, CPI INR 75. If D30 LTV = INR 500 and target CAC payback = 30 percent of LTV, max acceptable CPI = INR 150. Campaign is profitable and scaled.
• Fintech app: Brand keyword CPT INR 4, conversion 40 percent, CPI INR 10. Scale immediately while optimizing compliance and landing flows for KYC.

Tools and Resources

This list focuses on concrete platforms you will use and indicative pricing where available.

• Apple Search Ads Advanced and Basic

• Availability: ASA is available in India on both Basic and Advanced tiers.

• Pricing model: Basic is price-per-install, automated. Advanced is cost-per-tap auction. Apple charges based on taps for Advanced.

• Note: No public minimum spend for Advanced, but test budgets are recommended.

• App Store Connect

• Usage: Link ASA, manage app metadata, upload builds, and create Custom Product Pages.

• Pricing: Free with Apple Developer Program membership (USD 99/year).

• Attribution platforms

• AppsFlyer: market leader, pricing starts at several thousand USD per year for enterprise; free tier for small apps occasionally available.

• Adjust: enterprise pricing; strong cohort and fraud protection features.

• Branch: deep linking and attribution, more accessible pricing for startups.

• Use any provider to measure ROAS and LTV beyond first install.

• Keyword and competitive intelligence

• Sensor Tower: keyword research and volume estimates, subscription tiers typically start around a few hundred USD per month.

• App Annie (now data.ai): market data and competitor analysis, paid product.

• MobileAction: keyword intelligence with lower-cost tiers; useful for ASO and keyword discovery.

• Analytics and crash reporting

• Firebase: free analytics, events, funnels, and remote config. Good for Android and complementary to iOS reporting.

• Mixpanel and Amplitude: event analytics and retention cohorts, paid plans available.

• Creative and A/B testing

• SplitMetrics and StoreMaven: Custom Product Page and store listing A/B testing; pricing varies by project.

Practical tip: Use the attribution provider integration with ASA to import postback events, and set up ROAS and LTV dashboards that automatically pull ASA spend.

Common Mistakes and How to Avoid Them

1. Treating India like the US market

• Mistake: Using US bid benchmarks and keyword lists.
• Fix: Adjust CPTs and keywords for local search behavior. Focus on metro cities and price sensitivity. Run a local test.

2. Not linking attribution or failing to track revenue events

• Mistake: Measuring installs only and scaling on vanity metrics.
• Fix: Integrate AppsFlyer or Adjust on day one and track at least one revenue event, subscription start, or first purchase.

3. Ignoring brand keywords

• Mistake: Pausing brand keywords because they seem organic.
• Fix: Brand keywords are often lowest CPI and highest conversion. Protect them with exact-match bids and monitor cannibalization.

4. Over-reliance on broad match without negatives

• Mistake: Letting broad matching consume budget with irrelevant taps.
• Fix: Add negative keywords weekly. Use Search Term report to add contaminants as negatives.

5. Scaling before proving LTV

• Mistake: Doubling budget after a short run without D7 or D30 LTV data.
• Fix: Wait for D7 and ideally D30 cohorts. Use your payback period threshold to scale.

Frequently Asked Questions

How Much Should I Budget for Apple Search Ads in India?

Start with INR 30,000-75,000 over 30 days for a single app to generate statistically meaningful data across brand, competitor, and category keywords. Adjust based on category CPCs and required sample sizes.

What are Typical CPT and CPI Ranges in India?

Typical cost-per-tap (CPT) ranges widely by category. Expect CPT from INR 4-30; for high-intent finance or productivity keywords it can be higher. Estimate CPI by dividing CPT by tap-to-install conversion rate; example: CPT INR 10 with 25 percent conversion gives CPI INR 40.

Should I Use Basic or Advanced Apple Search Ads?

Use Basic if you want automated, CPI-based campaigns with minimal management. Use Advanced for granular control over keywords, bids, creative sets, and audience refinements. Advanced is recommended for growth teams optimizing ROAS.

How Do I Choose Between Keyword Match Types?

Use exact match for high-intent, high-ROI keywords. Use broad match and Search Match for discovery and expansion. Add negatives to broad and Search Match to prevent irrelevant taps.

How Long Before I Can Scale a Campaign?

Wait for clean D7 LTV data and stability in CPI and conversion rates, typically 30-45 days. If D7 ROAS is positive and D30 looks strong, scale over the next 30-45 days.

What Attribution Tool Should I Use?

AppsFlyer and Adjust are the most common for enterprise-grade attribution in India. Branch is a strong choice for deep linking and lighter attribution requirements. Choose based on integration needs and budget.

Next Steps

1. Link accounts and enable tracking

• Link Apple Search Ads to App Store Connect and integrate an attribution provider (AppsFlyer, Adjust, or Branch) to capture installs and revenue events.

2. Run a 30-day pilot

• Allocate INR 30,000-75,000 across brand, competitor, and category campaigns. Use exact match and Search Match. Collect taps, installs, and conversion data.

3. Calculate CPI and payback

• Compute CPI from CPT and tap-to-install conversion. Compare to D7 and D30 LTV to determine scale readiness.

4. Optimize and scale

• Move winning keywords to higher bids, expand creative sets, and increase budgets by 2x-5x only after D7 or D30 signals indicate positive ROAS.

Checklist summary:

• Link ASA and App Store Connect
• Integrate attribution and revenue events
• Create 4 campaign buckets: brand, competitor, category, discovery
• Run 30-day test with defined CPT and budget caps
• Use Search Term reports weekly and update negatives
• Evaluate D7 and D30 LTV before scaling

Further Reading

• Apple Search Ads New Countries Guide
• Apple Search Ads Keyword Tool Guide
• Apple Search Ads Low Volume Terms Guide
• Apple Search Ads Reporting API Guide