Scaling Success with X-ID: A Large-Budget Campaign Case Study

In today’s competitive digital ecosystem, achieving sustainable app growth requires more than just standard media buying — it demands a carefully designed strategy that aligns budget scale with performance optimization. X-ID, a telecommunications and entertainment application, set out to expand its user base rapidly while ensuring cost efficiency and high engagement. With a large advertising budget at stake, the challenge was to balance automation, advanced tracking, and cross-platform integration to deliver measurable impact.

This case study showcases how a data-driven approach, leveraging Google Ads, Firebase, and GA4, translated into over 4.5 million in-app actions, 64,000 new installs, and a conversion rate surpassing 80%. Beyond the numbers, it highlights how meticulous planning, precise implementation, and ongoing optimization turned a high-investment campaign into a scalable success story — strengthening X-ID’s market position and building a sustainable path for future growth.

Client Background

X-ID is a mobile application operating in the telecommunications and entertainment sector. The platform was developed to offer convenient digital services while also enhancing user engagement with entertainment features. At the time of engagement, X-ID sought to expand its user base, improve app visibility, and increase long-term active users in a highly competitive market.

X-ID was developed by a leading telecommunications operator in Asia with the ambition of becoming a “super-app” that integrates entertainment, messaging, and customer service features. By leveraging deep localization, the application offers an interface and content tailored to Khmer culture, enabling it to quickly attract hundreds of thousands of downloads and build a loyal user base.

Supported by the distribution power of a nationwide telecom infrastructure, X-ID has been able to launch promotional campaigns, data incentives, and customer care programs effectively, further accelerating its growth trajectory. More than just an entertainment hub, X-ID represents a strategic digital platform that enhances customer value and strengthens the operator’s market presence in an increasingly competitive digital ecosystem.

Business Challenge

The client faced several critical challenges:

• Despite steady app development, brand awareness was limited compared to larger competitors.
• The client wanted to achieve measurable growth in new app installs while maintaining a sustainable CPA (Cost Per Acquisition).
• They lacked a robust data-driven performance measurement system to track user behavior beyond just installs.
• The business needed insights into user engagement and retention, not only acquisition.

In short, the challenge was not just to scale installs, but to ensure that new users actively engaged with the app, providing long-term value.

Campaign Strategy

A strategic campaign demands precision. Large-Budget Campaign Case Study reveals how tailored planning and execution delivered outstanding growth results.

To tackle these challenges, I designed a comprehensive digital campaign with three strategic pillars:

1. Cross-Platform Integration

• • Deployed Google Ads & Search Ads 360 (SA360) for campaign automation, tracking, and optimization.
  • Integrated Firebase and GA4 for end-to-end event tracking of installs, active sessions, and engagement metrics.
  • Configured Floodlight tags to ensure accurate conversion attribution across channels.

1. Targeted Campaign Structure

• • Created brand campaigns to capture high-intent searches and defend brand presence.
  • Built generic keyword campaigns to expand reach and attract new audiences.
  • Applied remarketing & lookalike audiences to re-engage past visitors and find high-value similar users.

1. Optimization Framework

• • Set automated bidding (tCPA) to maximize installs and user quality at scale.
  • Conducted weekly reviews of performance data to refine keywords, ad creatives, and audience segments.
  • Reallocated budget dynamically toward the best-performing ad groups and channels.

Implementation Process

The implementation was both technical and strategic, involving multiple layers of setup:

• • Floodlight Configuration: Separate activities were created for installs, engaged sessions, and custom in-app actions, ensuring precise tracking.
  • Account Setup: Google Ads, SA360, and GA4 were fully linked, creating a seamless flow of data.
  • Custom GA4 Dashboards: Built to measure not only installs but also event-level data like session duration, engagement per user, and revenue-related actions.
  • Creative & Keyword Optimization: Multiple ad variations were tested to identify the highest-performing creatives and messaging.

This multi-layer setup ensured full visibility across the user journey, from impression → click → install → engagement.

Results Achieved

The campaign delivered exceptional growth that far exceeded expectations. Key outcomes included:

• Install Growth: Against an initial KPI of 10,000 installs, the campaign achieved 22,000+ installs, over 120% above target.
• Active Users: Reached 17,443 active users, indicating a strong and engaged user base.
• Engagement Quality:
  • 90.5% engagement rate.
  • 66,301 engaged sessions recorded.
  • 246,547+ key in-app events tracked in GA4.

• Conversion Rate: Overall conversion rate surpassed 80%, making the campaign highly cost-efficient.

The combination of installs and strong engagement validated the strategy of focusing on both acquisition and retention quality.

Business Impact

The campaign not only met but also significantly exceeded the client’s expectations. Beyond hitting growth targets, it had a transformative impact:

• Brand Visibility: X-ID became far more widely recognized within its sector.
• Sustainable Growth Model: The integration of SA360 automation and GA4 analytics created a replicable model for future campaigns.
• Actionable Insights: The client gained a much clearer understanding of user behavior, allowing them to improve both app design and user experience.
• Confidence in Digital Scaling: With this success, the client was motivated to invest more heavily in digital campaigns as a primary growth driver.

Recommendations & Next Steps

Based on the insights, I recommended that the client:

• Expand event tracking to cover more in-app activities such as payments and advanced user actions.
• Invest further in remarketing and lookalike strategies to increase user lifetime value.
• Use GA4 data to optimize app onboarding flow, ensuring new installs convert into active long-term users.
• Test expansion into additional ad formats (e.g., YouTube, Display) to strengthen brand recall.

These recommendations helped the client build a sustainable roadmap for digital growth, moving from short-term performance gains to long-term strategic success.

For the next phase, X-ID should prioritize deeper audience segmentation and event tracking beyond installs to capture true user value. Expanding localized creatives in Khmer, combined with reward-based engagement campaigns, will help sustain retention. Integrating monetization metrics into GA4 dashboards ensures growth strategies align with revenue objectives. By focusing on both acquisition quality and long-term engagement, X-ID can strengthen its role as a leading super-app while building a sustainable foundation for future expansion in the digital ecosystem.

Contact me for more details about this case study: Email Me | Zalo me

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X-ID Deployment Strategy Analysis — Detailed Analysis

A. Multilayer Measurement

Objective: Shift from “counting installs” to “understanding post-install user behavior” in order to optimize user quality (activation, retention, LTV).

1) Core components of multilayer measurement

• Event tracking in the app (GA4 / Firebase): installs, first_open, completed onboarding, account registration, core actions (e.g., send message, purchase bundle, redeem reward), transactions (if any).
• Floodlight / Floodlight tags (SA360 / DV360): attach conversions for paid campaigns (installs, valuable in-app events). Use Floodlight as the primary conversion source for SA360.
• Data source linking: Google Ads ↔ SA360 ↔ GA4/Firebase; if an MMP (Adjust/Appsflyer) is used, ensure correct event mapping and synchronization.
• Server-to-Server (S2S) / Postback: ensure consistency and reduce data loss caused by SDK blocking or iOS privacy restrictions.

2) Events to track (minimum)

• install (install)
• first_open (first open)
• complete_onboarding
• key_action_1 (e.g., send message / search / booking)
• purchase / subscription (revenue events)
• retention flags D1, D7, D30 (user still active after 1/7/30 days)

3) KPIs & reports required

• CPI (Cost Per Install)
• CVR (Click → Install)
• Install → Active rate (percentage of installs that become active users within 7 days)
• Retention D1 / D7 / D30
• Events per user (average events per user)
• LTV (30 / 90 days)
• LTV : CAC (profitability ratio)

4) Risks & mitigations

• Attribution discrepancies between GA4 and Floodlight: caused by differences in attribution windows and models. Mitigation: standardize attribution windows across systems and use server-side deduplication where necessary.
• Missing data (iOS privacy / SKAdNetwork): Mitigation: add MMP + modeling, use conversion modeling and probabilistic matching.
• Click flooding / fraudulent installs: Mitigation: monitor abnormal installs-to-activations ratios and deploy anti-fraud tools.

B. Tiered Campaign Structure

Objective: Both scale market reach and protect the brand while optimizing for quality conversions.

1) The three campaign layers (X-ID model)

• Brand campaigns: brand keywords and awareness ads. Role: protect search intent, ensure users searching the app name find it, typically low cost with high conversion rates.
• Generic / Acquisition campaigns: generic keywords, interest/behavioral targeting, UAC/Display/YouTube for scale. Role: acquire new users at volume.
• Remarketing / Retention campaigns: target users who have interacted (app opened, incomplete onboarding, churn). Role: increase activation, reduce churn, raise LTV.

2) Suggested budget allocation (example, depends on context)

• Generic (scale): 50% — find new users.
• Remarketing (activate/retain): 30% — improve quality.
• Brand (protect search + awareness): 20%.
  (Adjust by performance: shift budget from underperforming channels to better ones.)

3) Targeting & audiences

• Lookalike / Similar audiences built from cohorts of high-quality users (top 10–20% by LTV).
• Behavioral segmentation: users who installed but did not register, users who completed onboarding but haven’t paid, high-LTV users.
• Geo / device / OS segmentation: test costs by region; prioritize scaling in areas with the best ROI.

4) Ad group & creative structure

• Each campaign should contain multiple ad groups / asset groups to test creatives, messaging, and CTAs.
• Map creatives to audiences (e.g., reward-based creatives for highly engaged users, feature-focused creatives for users seeking specific capabilities).

C. Continuous Optimization

Objective: Use automation + data to balance scale and quality (keep CPA low while ensuring high LTV).

1) Bidding strategies

• tCPA (target CPA): suitable when sufficient conversion history exists. Requires >30–50 conversions per week for stability.
• tROAS / value-based bidding: optimize for revenue/LTV instead of just installs if monetary values are assigned.
• Manual bids (testing phase): use initially to gather data, then move to automated bidding.

2) Scaling rules

• Rule of 20/20: increase budget by +20% if CPI is stable below target for 3–7 days; reduce budget by 20% if CPI rises >20% versus baseline.
• Scale winners, pause losers: maintain exploration pool for new creatives but reallocate quickly to winning variants.
• Control learning phase: allow 3–7 days for the algorithm to adapt after structural or bid changes.

3) Creative testing framework

• Test hypothesis: change one variable at a time (headline, visual, CTA).
• Cadence: discovery phase (14 days, many variants), exploit phase (4–6 weeks, scale winners).
• Metrics: CTR → CVR → CPI → D1 retention → D7 retention. Don’t optimize on CPI alone.

4) Quality optimization (activation → retention)

• Onboarding funnel optimization: track drop-offs and A/B test onboarding flows.
• In-app nudges / push campaigns: use remarketing audiences to move users from install → active.
• Cohort analysis: monitor retention by traffic source / creative to identify higher-quality channels.

D. From Metrics to Money

• LTV : CAC is the key metric.
  Example:
  • CAC (CPA) = 50,000 VND.
  • Average LTV (30 days) = 200,000 VND.
  • LTV / CAC = 4 → each unit of cost returns 4 units of revenue within 30 days.
  • Spend 1,000,000 VND → 20 installs → 4,000,000 VND revenue → 3,000,000 VND profit.

Optimization rule: prioritize channels/creatives with LTV/CAC ≥ target (e.g., ≥ 3). If < target, optimize onboarding or reduce bids.

E. Advanced Execution Issues & Technical Considerations

• Standardize conversion definitions: GA4, SA360, Google Ads, MMP must align.
• Deduplicate conversions: prevent double counting via server-side IDs.
• Privacy / iOS (SKAdNetwork): apply conversion modeling, probabilistic attribution, SKAdNetwork value buckets.
• Data quality governance: daily data checks, SDK error monitoring, validation rules.
• Integrate revenue events for tROAS: assign monetary values in Floodlight/GA4 for value-based bidding.

F. Actionable Checklist

• Design event mapping: list event → GA4 event → Floodlight activities → MMP postbacks.
• Implement SDK + server-side postback, validate QA flows.
• Set up cohort dashboards (D1/D7/D30 retention, installs by source, LTV curves).
• Launch test campaign (2 weeks): multiple creatives, small budgets, collect conversion data.
• Select winners → enable tCPA / tROAS, scale with Rule of 20/20.
• Optimize onboarding & remarketing in parallel.
• Weekly: analyze performance, adjust bids, creatives, audiences.
• Monthly: audit measurement & attribution.