▸Example Segment (Twilio) call (the "before")
import com.segment.analytics.kotlin.android.Analytics
val analytics = Analytics("YOUR_WRITE_KEY", context) {
collectDeviceId = true
flushAt = 20
}
analytics.identify(userId, traitsOf("email" to email, "plan" to "pro"))
analytics.track("Paywall Purchase", buildJsonObject {
put("value", price)
put("currency", "USD")
})Most analytics SDKs back the unsent event queue with SQLite or UserDefaults / SharedPreferences — so a phone that's been confiscated, jailbroken, or restored from backup still contains analytics state. Respectlytics's queue is RAM-only, flushed on a 30-second timer; unsent events on force-quit are lost by design, in exchange for zero on-device forensic surface.
☑Remove Segment (Twilio) cleanly
-
1
Remove the Segment Analytics SDK from your build (
Analytics-Swift/analytics-android/@segment/analytics-react-native/segment_analytics_flutter) -
2
Remove
Analytics.client(writeKey: ...)andanalytics.track(...)call sites — replace withRespectlytics.track("event_name") -
3
Critically: review your Segment destinations and decide which destinations you still need data flowing to from Respectlytics (most don't — that's the point)
-
4
Delete the Segment workspace's mobile source once events have stopped flowing
-
5
Audit and remove the downstream destination SDKs that Segment was the only reason to forward to (e.g., Facebook Pixel, Google Ads)
⇋Segment (Twilio) vs Respectlytics — ram-only event queue
| Segment (Twilio) | Respectlytics | |
|---|---|---|
| Event queue persistence | SQLite / UserDefaults / SharedPreferences | In-memory ring buffer |
| Disk usage for analytics | 0.5–10 MB typical | 0 bytes |
| Forensic data on jailbroken / rooted devices | Persistent identifiers + queued events | None |
| Survives force-quit before flush | Yes | No (events lost — by design) |
❓Frequently asked questions
Doesn't this reduce data quality?
Marginally — typical force-quit-before-flush event loss is 0.5–2% depending on platform. For aggregate metrics (funnel rates, feature adoption, release deltas) this is invisible. For per-event reconciliation it would be a problem, but per-event reconciliation isn't a use case Respectlytics supports.
What's the actual flush cadence?
30 seconds by default, plus a flush on applicationDidEnterBackground (iOS) / onPause (Android). Most events reach the network within seconds of being fired.
Is this safe for crash analytics?
Crash analytics is a separate concern — use Sentry, Crashlytics, or Bugsnag (with their own crash-aware queues). Respectlytics is product analytics; crash data has different recoverability requirements and lives in different tools.
Why is this a privacy feature?
Devices that are jailbroken, rooted, restored from backup, or forensically imaged routinely surface analytics artifacts — distinct_ids, queued events, user properties — that survive uninstall in some cases. RAM-only storage moves the dump-recovery surface to zero.