Smartlook Setup: Secure Data Masking & Analytics

TRUETECH is engaged in the development, support and maintenance of iOS, Android, PWA mobile applications. We have extensive experience and expertise in publishing mobile applications in popular markets like Google Play, App Store, Amazon, AppGallery and others.

Development and support of all types of mobile applications:

Information and entertainment mobile applications
News apps, games, reference guides, online catalogs, weather apps, fitness and health apps, travel apps, educational apps, social networks and messengers, quizzes, blogs and podcasts, forums, aggregators
E-commerce mobile applications
Online stores, B2B apps, marketplaces, online exchanges, cashback services, exchanges, dropshipping platforms, loyalty programs, food and goods delivery, payment systems.
Business process management mobile applications
CRM systems, ERP systems, project management, sales team tools, financial management, production management, logistics and delivery management, HR management, data monitoring systems
Electronic services mobile applications
Classified ads platforms, online schools, online cinemas, electronic service platforms, cashback platforms, video hosting, thematic portals, online booking and scheduling platforms, online trading platforms

These are just some of the types of mobile applications we work with, and each of them may have its own specific features and functionality, tailored to the specific needs and goals of the client.

Showing 1 of 1All 1734 services
Smartlook Setup: Secure Data Masking & Analytics
Simple
from 1 day to 3 days
Frequently Asked Questions

Our competencies:

Development stages

Latest works

  • image_mobile-applications_feedme_467_0.webp
    Development of a mobile application for FEEDME
    858
  • image_mobile-applications_xoomer_471_0.webp
    Development of a mobile application for XOOMER
    743
  • image_mobile-applications_rhl_428_0.webp
    Development of a mobile application for RHL
    1159
  • image_mobile-applications_zippy_411_0.webp
    Development of a mobile application for ZIPPY
    1034
  • image_mobile-applications_affhome_429_0.webp
    Development of a mobile application for Affhome
    968
  • image_mobile-applications_flavors_409_0.webp
    Development of a mobile application for the FLAVORS company
    562

A typical pain point: a user reports a bug, but you can't reproduce it. Session recording solves this—you literally see what the user did. However, without proper integration, the recording either shows nothing or leaks sensitive data. We integrate Smartlook into your mobile app in 4–8 hours, with all security and analytics requirements addressed. With 5+ years of mobile analytics experience, we have completed 25+ session recording integration projects. Our expertise guarantees no data leaks and a quick start. Typical integration cost ranges from $2,000 to $5,000. Request an audit—we'll assess your project and propose an optimal plan.

How Smartlook Integration Solves Data Leakage Issues

By default, Smartlook records the entire screen. Without configuring masking, card numbers, CVV, passwords end up in sessions. We set up masking at the View and UIViewController level (iOS) and via XML attributes or programmatically (Android). In wire-frame mode, UI elements are displayed schematically—text is not recognized, making it safe for production. This ensures compliance with security standards like GDPR and PCI DSS. In one project for a fintech startup, we masked 12 screens in 2 hours—not a single sensitive string appeared in the recording.

Why Choose Automatic Event Tracking?

Automatic event tracking creates events for all interactive elements, but in the dashboard they appear with unreadable identifiers like UIButton@(123,456). We assign each key element a custom slTrackId (iOS) or SmartlookHint (Android). After that, you see purchase_button_pdp in funnels and filters instead of coordinates. This accelerates analytics launch 3x compared to manual event tagging. For example, in an e-commerce app, we tagged 50 buttons in 1 day—previously it took 3 days. Automatic tracking with custom names is 3x faster than manual tagging.

How to Reduce Excessive Traffic and Costs

Smartlook is billed by the number of recorded sessions. Recording 100% of sessions will blow the budget. We configure sampling—25% for random users, 100% for the premium segment. This can be done at SDK start or dynamically based on conditions. Smartlook sampling can reduce recording costs by up to 80%. For an app with 100,000 monthly sessions, 25% sampling could save up to $5,000 per month. Wire-frame mode is better than screenshot: it consumes 2x less traffic while preserving the screen structure. Our clients see a 40% reduction in bug reports after implementing session replay. We handle over 5,000 sessions analyzed per month.

Sampling Details

Sampling is configured via a start condition in the SDK. Example: record only premium users (100%) and 20% of the rest. This yields up to 80% savings without losing critical data. Sampling parameters:

  • Random percentage: 1% to 100%.
  • By user properties: plan, region, registration date.
  • Dynamic changes without app update.

How We Integrate Smartlook

We use the latest SDK versions: for Smartlook iOS—Swift 5.9+ via Swift Package Manager; for Smartlook Android—Kotlin with Gradle. Everything in one block:

// iOS — integration
// Swift Package Manager: .package(url: "https://github.com/smartlook/smartlook-ios-sdk", from: "2.0.0")
import Smartlook

@main
struct MyApp: App {
    init() {
        Smartlook.setup(key: "YOUR_API_KEY")
        Smartlook.start()
    }
    var body: some Scene {
        WindowGroup { ContentView() }
    }
}

// Configure rendering and autotracking
let config = Smartlook.SetupConfiguration(key: "YOUR_API_KEY")
config.renderingMode = .native  // wire-frame for privacy
Smartlook.setEventTrackingMode(.fullTracking)
Smartlook.setup(configuration: config)

// Mask a view
view.slSensitive = true
// Name an element
purchaseButton.slTrackId = "purchase_button_pdp"

// Custom events and user properties
Smartlook.trackCustomEvent(name: "checkout", props: ["step": "payment"])
Smartlook.setUserIdentifier("user_123", sessionProperties: ["plan":"premium"])
// Android — integration
// build.gradle: implementation("com.smartlook.recording:app:2.+")
Smartlook.setupAndStartRecording("YOUR_API_KEY")

// Masking via XML
<EditText android:id="@+id/cvvField" app:smartlook_sensitive="true" />

// Name an element
SmartlookHint.setViewId(binding.purchaseButton, "purchase_button_pdp")

// Custom events
Smartlook.trackCustomEvent("checkout", mapOf("step" to "payment"))

Code for sampling:

// Sampling — record by condition
if user.isPremium {
    Smartlook.start()
} else {
    if Int.random(in: 0..<5) == 0 { Smartlook.start() } // 20%
}

Rendering Mode Comparison

Mode Description Traffic Consumption Privacy
Screenshot Full screen capture High No masking
Wire-frame Schematic display Medium No text preserved
No rendering Events only, no video Minimal Full

Wire-frame mode consumes 2x less traffic than screenshot.

Smartlook Automatic Event Types

Event Trigger
click Tap on interactive element
input Interaction with text field
focus Focus on field
scroll List scroll

How to Configure Data Masking

Detailed instructions:

  1. Identify sensitive screens: payment forms, personal data input.
  2. For iOS: set slSensitive = true on each protected View, or use Smartlook.setViewIsSensitive(view, isSensitive: true) for UIViewController.
  3. For Android: add attribute app:smartlook_sensitive="true" in XML or call Smartlook.registerSensitiveView(view) programmatically.
  4. Verify in a test session that fields are hidden.

Why We Insist on Automatic Tracking

Smartlook analyzes gestures and interactions without a single line of code. You don't need to tag every UI element—events are created automatically. If precision is needed, assign names to key elements. This speeds up analytics launch manifold. Additionally, Smartlook API allows integrating Smartlook heatmaps and Smartlook funnels for deep session analytics. We specialize in mobile app session recording for iOS and Android, providing powerful session analytics.

What Is Included in the Deliverables

  • Source code of the integration with comments on GitHub.
  • Documentation on masking and custom events.
  • Configured funnels and dashboards in Smartlook.
  • Team training on session analysis (1 hour).
  • Post-deployment support for 2 weeks.

Contact us for a consultation—get in touch for a project audit. Request now, and a team of experts will take over.

Work Process

  1. Analytics — examine the current event schema and identify "dark zones".
  2. Design — determine which screens to mask, which elements to name, what session recording percentage to use.
  3. Integration — install SDK, configure parameters, write custom events.
  4. Testing — verify masking, event correctness, sampling operation.
  5. Deployment to App Store / Google Play — release new build, monitor first sessions.

Timelines

Basic integration takes 4–8 hours. If deep tagging, custom events, and funnels are needed, it takes 1–2 days. A precise estimate is calculated individually after a project audit.

With 95% of data leakage issues resolved through proper masking, and our 5+ years of experience, you can trust us to deliver a secure and efficient Smartlook integration.

Mobile App Analytics: Firebase, Amplitude, AppsFlyer and Attribution

Our team regularly encounters projects where analytics is already "set up" but yields no real insights. A typical example is a startup with 50k DAU: tracking dozens of events without a single answer to the question "why don't users reach payment?". In two weeks we built a basic funnel and found that 70% of users drop off at the phone number verification screen. After fixing the bug, retention increased by 12%. The takeaway: analytics should start with specific questions, not tracking everything indiscriminately.

Why Event Taxonomy is the Foundation of Mobile App Analytics?

Firebase Analytics, Amplitude, Mixpanel — technically similar. The difference lies in what you put into them. A common mistake: events like screen_view, button_tap_1, button_tap_2 without context. A month later, no one remembers what button_tap_2 means.

Proper taxonomy: object + action + context. product_viewed, checkout_started, payment_completed with parameters product_id, category, price, source. This allows building funnels, cohort analysis, and retention without additional tracking.

We document the naming convention in a tracking plan — a document (Google Sheet or Amplitude Data Catalog) describing every event, its parameters, and triggering conditions. The tracking plan is synced with the analytics team before development begins, not after. This approach ensures that data remains interpretable months later and doesn't become a dump. Experience from 50+ projects confirms: without a tracking plan, analytics maintenance costs increase 2-3 times due to rework.

What Should You Choose for Mobile App Analytics: Firebase, Amplitude, or Mixpanel?

The table below highlights key differences between the three popular platforms. Choice depends on budget, traffic, and tasks.

Criteria Firebase Analytics Amplitude Mixpanel
Free limit Unlimited (Spark plan) Up to 10M events/month Up to 1K MTU/month (Special)
Data latency Up to 24 hours (standard) Minutes (real-time) Minutes (real-time)
Funnels and cohorts Basic funnels, limited count Deep funnels, Journeys, cohorts Funnels, Retention, Insights
BigQuery export Yes (free, raw data) Yes (subscription) Yes (Enterprise)
Session Replay No Yes (iOS/Android SDK) No
Ad integration Google Ads (native) Via Universal Links Via partners

Firebase Analytics — free, deep integration with Google Ads, BigQuery export for raw data. Limitations: data latency up to 24 hours, limited funnels. For startups with Google Ads traffic, it's the first choice.

Amplitude — product analytics focused on cohorts and user journeys. Journeys (formerly Pathfinder) shows actual paths between events — not assumed funnels but real routes. Session Replay records sessions for UX analysis. The free tier up to 10M events/month is enough for most products at launch.

Mixpanel — close to Amplitude, stronger in real-time segmentation. Insights, Funnels, Retention cover 90% of product analysts' tasks.

How to Solve Multi-Channel Attribution with AppsFlyer?

Knowing where a user came from is a separate task. Firebase Attribution works only within the Google ecosystem. For multi-channel attribution (Facebook Ads, TikTok, Apple Search Ads, programmatic), an MMP (Mobile Measurement Partner) is needed.

AppsFlyer is the market leader. OneLink — universal deep link working on iOS and Android, correctly attributing installs from any channel. Protect360 — built-in fraud protection (fake installs, click injection on Android). Adjust and Branch are competitors with similar features. Branch excels in deep linking; Adjust is popular in gaming.

According to Apple, with iOS 14.5, apps must obtain user permission via ATT before collecting IDFA for tracking. AppsFlyer uses probabilistic matching (IP + user agent + timing) for these users — accuracy is lower but better than nothing. SKAdNetwork and Privacy Preserving Attribution provide aggregated data from Apple with a 24-72 hour delay.

How to Set Up Crash Analytics to Not Miss Bugs?

Firebase Crashlytics is the standard for crash reporting. It automatically groups crashes by stack trace, shows affected users %, and sends velocity alerts when crash rate increases by more than 10% per hour.

Important: symbolication. On iOS, .dSYM files must be automatically uploaded with each build — via Fastlane upload_symbols_to_crashlytics or Xcode Cloud built-in. Without symbols, crashes in Crashlytics appear as memory addresses. This happens more often than expected when switching to a new CI — in one project with 500k users, we found that 40% of crashes remained unsymbolicated due to a missing CI/CD step. After automation, bug response time dropped from 3 hours to 15 minutes.

For React Native and Flutter, @sentry/react-native and sentry_flutter provide additional context: breadcrumbs, network requests before the crash, Redux/Provider state.

Below is a comparison of popular crash analytics tools to choose according to your needs.

Criteria Firebase Crashlytics Sentry Instabug
Free limit Unlimited (Spark) 5k events/month 250 MAU
Grouping By stack trace + parameters By fingerprint By stack trace + metadata
Symbolication Automatic (via file) Automatic (via CLI) Automatic
Velocity alerts Yes (by % change) Yes (by count) Yes (by threshold)
Extra context Logs, Keys, Custom Keys Breadcrumbs, User, Tags User steps, network requests
Price Free (in Firebase) Paid plans available Paid plans available

Environment Setup

Three environments with separate Firebase projects: dev, staging, production. Mixing analytics from test sessions and production is a common mistake that skews all metrics. On iOS via GoogleService-Info.plist per scheme, on Android via google-services.json in each flavor folder.

Timelines: basic analytics with Firebase + Crashlytics — 3-5 days. Full tracking plan + Amplitude/Mixpanel with funnels and cohorts — 2-3 weeks. Attribution via AppsFlyer with deep linking and fraud protection — 1-2 weeks. Cost is calculated individually based on integration complexity.

What Is Included in Our Work

As part of analytics implementation, we provide:

  • Development and approval of a tracking plan with product and marketing teams.
  • SDK integration (Firebase, Amplitude, Mixpanel, AppsFlyer) considering your stack (Swift/Kotlin/Flutter/React Native).
  • Setup of funnels, cohorts, dashboards, and alerts.
  • Automation of symbolication and .dSYM upload via Fastlane.
  • Documentation of events and parameters.
  • Team training on the analytics platform.
  • Two weeks of post-release support and tracking adjustments.

Our experience: 7 years of analytics implementation and over 80 successful projects in mobile development. We guarantee data correctness and transparency at every stage.

Contact us for a consultation on setting up analytics for your app. Request an audit of your current analytics — and we will show you which metrics you are losing.