Document User Interpretation Stage in BID Framework

This function documents the interpretation of user needs, capturing the central question and the data storytelling narrative. It represents stage 1 in the BID framework.

Usage

bid_interpret(
  previous_stage = NULL,
  central_question,
  data_story = NULL,
  user_personas = NULL,
  quiet = NULL
)

Arguments

previous_stage: Optional tibble or list output from an earlier BID stage function. Since Interpret is the first stage in the BID framework, this is typically NULL but can accept previous stage output in some iteration scenarios.
central_question: Required. A character string representing the main question to be answered. If NULL, will be suggested based on previous stage information.
data_story: A list containing elements such as hook, context, tension, resolution, and optionally audience, metrics, and visual_approach. If NULL, elements will be suggested based on previous stage.
user_personas: Optional list of user personas to consider in the design.
quiet: Logical indicating whether to suppress informational messages. If NULL, uses getOption("bidux.quiet", FALSE).

Value

A tibble containing the documented information for the "Interpret" stage.

Examples

# Basic usage
interpret_result <- bid_interpret(
  central_question = "What drives the decline in user engagement?",
  data_story = list(
    hook = "Declining trend in engagement",
    context = "Previous high engagement levels",
    tension = "Unexpected drop",
    resolution = "Investigate new UI changes"
  )
)
#> Stage 1 (Interpret) completed.
#>   - Central question: What drives the decline in user engagement?
#>   - Your data story has all key elements. Focus on making each component compelling and relevant.
#>   - Your central question is appropriately scoped.
#>   - No user personas defined 

# With user personas
interpret_personas <- bid_interpret(
  central_question = "How can we improve data discovery?",
  data_story = list(
    hook = "Users are missing key insights",
    context = "Critical data is available but overlooked",
    tension = "Time-sensitive decisions are delayed",
    resolution = "Highlight key metrics more effectively"
  ),
  user_personas = list(
    list(
      name = "Sara, Data Analyst",
      goals = "Needs to quickly find patterns in data",
      pain_points = "Gets overwhelmed by too many visualizations",
      technical_level = "Advanced"
    ),
    list(
      name = "Marcus, Executive",
      goals = "Wants high-level insights at a glance",
      pain_points = "Limited time to analyze detailed reports",
      technical_level = "Basic"
    )
  )
)
#> Stage 1 (Interpret) completed.
#>   - Central question: How can we improve data discovery?
#>   - Your data story has all key elements. Focus on making each component compelling and relevant.
#>   - Your central question is appropriately scoped.
#>   - User personas: 2 defined 

summary(interpret_personas)
#> === BID Framework: Interpret Stage Summary ===
#> 
#> Metadata:
#>    stage_number : 1 
#>    total_stages : 5 
#>    validation_status : completed 
#>    has_central_question : Yes 
#>    story_completeness : 1 
#>    personas_count : 2 
#>    auto_generated_question : No 
#>    auto_generated_story : No 
#> 
#> Stage Data:
#>    stage : Interpret 
#>    central_question : How can we improve data discovery? 
#>    hook : Users are missing key insights 
#>    context : Critical data is available but overlooked 
#>    tension : Time-sensitive decisions are delayed 
#>    resolution : Highlight key metrics more effectively 
#>    personas : [{"name":["Sara, Data Analyst"],"goals":["Needs to quickly find patterns in d... 
#>    suggestions : Your data story has all key elements. Focus on making each component compelli... 
#> 
#> Generated: 2025-09-23 23:04:51