Ingest telemetry data and identify UX friction points

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 returns a hybrid object that is backward-compatible as a list of Notice stages while also providing enhanced functionality with tidy tibble access and flags extraction.

Note: This function is designed for Shiny application telemetry. For Quarto dashboards, shiny.telemetry only works when using server: shiny in the Quarto YAML. Static Quarto dashboards and OJS-based dashboards do not support shiny.telemetry. Consider alternative analytics solutions (e.g., Plausible) for static dashboard usage tracking.

Usage

bid_ingest_telemetry(
  source,
  format = NULL,
  events_table = NULL,
  table_name = NULL,
  thresholds = list()
)

Arguments

source: Either a file path to telemetry data (SQLite database or JSON log file), or a DBI connection object to an already-open database. When a connection is provided, it will not be closed by this function.
format: Optional format specification ("sqlite" or "json"). If NULL, auto-detected from file extension (for file paths) or defaults to "sqlite" for DBI connections.
events_table: Optional data.frame specifying custom events table when reading from SQLite. Must have columns: event_id, timestamp, event_type, user_id. If NULL, auto-detects standard table names (event_data, events). Cannot be used with table_name.
table_name: Optional character string specifying the table name to read from the database. If NULL (default), auto-detects standard table names (event_data, events). Cannot be used with events_table.
thresholds: Optional list of threshold parameters: - unused_input_threshold: percentage of sessions below which input is considered unused (default: 0.05) - delay_threshold_secs: 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 hybrid object of class c("bid_issues", "list") containing bid_stage objects for each identified issue in the "Notice" stage. The object includes:

Legacy list: Named list of bid_stage objects (e.g., "unused_input_region", "delayed_interaction")
issues_tbl: Attached tidy tibble with issue metadata
flags: Global telemetry flags as named list
created_at: Timestamp when object was created

    Use as_tibble() to access the tidy issues data, bid_flags() to extract flags,
    and legacy list access for backward compatibility.

Examples

if (FALSE) { # \dontrun{
# Analyze SQLite telemetry database from file path
issues <- bid_ingest_telemetry("telemetry.sqlite")

# Use sensitivity presets for easier configuration
strict_issues <- bid_ingest_telemetry(
  "telemetry.sqlite",
  thresholds = bid_telemetry_presets("strict")
)

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

# Use a DBI connection object directly
con <- DBI::dbConnect(RSQLite::SQLite(), "telemetry.sqlite")
issues <- bid_ingest_telemetry(con)
# Connection remains open for further use
DBI::dbDisconnect(con)

# Specify custom table name
issues <- bid_ingest_telemetry(
  "telemetry.sqlite",
  table_name = "my_custom_events"
)

# 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?"
  )
}
} # }