bid_ingest_telemetry: Ingest telemetry data and identify UX friction points

In bidux: Behavior Insight Design: A Toolkit for Integrating Behavioral Science in UI/UX Design

Ingest telemetry data and identify UX friction points

Description

This function ingests telemetry data from shiny.telemetry output (SQLite or JSON) and automatically identifies potential UX issues, translating them into BID framework Notice stages. It analyzes user behavior patterns to detect friction points such as unused inputs, delayed interactions, frequent errors, and navigation drop-offs.

Usage

bid_ingest_telemetry(path, format = NULL, thresholds = list())

Arguments

path	File path to telemetry data (SQLite database or JSON log file)
format	Optional format specification ("sqlite" or "json"). If NULL, auto-detected from file extension.
thresholds	Optional list of threshold parameters: - unused_input_threshold: percentage of sessions below which input is considered unused (default: 0.05) - delay_threshold_seconds: seconds of delay considered problematic (default: 30) - error_rate_threshold: percentage of sessions with errors considered problematic (default: 0.1) - navigation_threshold: percentage of sessions visiting a page below which it's considered underused (default: 0.2) - rapid_change_window: seconds within which multiple changes indicate confusion (default: 10) - rapid_change_count: number of changes within window to flag as confusion (default: 5)

Value

A list containing bid_stage objects for each identified issue in the "Notice" stage. Each element is named by issue type (e.g., "unused_input_region", "delayed_interaction", etc.)

Examples

## Not run: 
# Analyze SQLite telemetry database
issues <- bid_ingest_telemetry("telemetry.sqlite")

# Analyze JSON log with custom thresholds
issues <- bid_ingest_telemetry(
  "telemetry.log",
  format = "json",
  thresholds = list(
    unused_input_threshold = 0.1,
    delay_threshold_seconds = 60
  )
)

# Use results in BID workflow
if (length(issues) > 0) {
  # Take first issue and continue with BID process
  interpret_result <- bid_interpret(
    previous_stage = issues[[1]],
    central_question = "How can we improve user engagement?"
  )
}

## End(Not run)

bidux documentation built on Aug. 30, 2025, 1:12 a.m.