Quick UX Suggestions for R Dashboard Developers — bid_quick

Provides a streamlined, single-step workflow for R dashboard developers who need quick UX suggestions without going through the full 5-stage BID framework. This function internally leverages the BID framework stages but presents results in a simple, actionable format. Works with both Shiny applications and Quarto dashboards.

Unlike the full BID workflow (Interpret -> Notice -> Anticipate -> Structure -> Validate), this function provides immediate suggestions based on a problem description. Use this for rapid prototyping or when you need quick guidance. For comprehensive UX redesign projects, use the full BID workflow.

Usage

bid_quick_suggest(
  problem,
  context = NULL,
  package = NULL,
  limit = 10,
  min_score = 0.7,
  quiet = NULL
)

Arguments

problem: Required. A character string describing the UX problem. Examples: "Users can't find the download button", "Information overload on dashboard", "Mobile interface is hard to navigate".
context: Optional. Additional context about the application or users. This helps refine suggestions to your specific situation.
package: Optional. Filter suggestions to specific package ("bslib", "shiny", "reactable", "DT", "plotly", "leaflet", etc.). If NULL, returns suggestions for all relevant packages. Note: bslib, plotly, DT, reactable, and leaflet components work in both Shiny apps and Quarto dashboards.
limit: Optional. Maximum number of suggestions to return (default: 10). Set to Inf to return all suggestions.
min_score: Optional. Minimum relevance score 0-1 (default: 0.7). Higher values return only the most relevant suggestions.
quiet: Optional. Logical indicating whether to suppress informational messages. If NULL, uses getOption("bidux.quiet", FALSE).

Value

A tibble with columns:

title: Brief actionable description of the suggestion
details: Specific implementation guidance
components: R dashboard component recommendations (character vector). Components prefixed with 'shiny::' require Shiny runtime; bslib, DT, plotly, reactable, and leaflet components work in both Shiny and Quarto dashboards.
concept: UX concept the suggestion is based on
score: Relevance score (0-1, higher is more relevant)
difficulty: Implementation difficulty (easy/moderate/advanced)
rationale: 1-2 sentence explanation of why this helps

Details

How it works:

The function analyzes your problem description using keyword matching and semantic analysis to:

Identify relevant UX concepts (cognitive load, navigation, visual hierarchy, etc.)
Detect appropriate layout patterns (grid, card, breathable, etc.)
Generate ranked suggestions with specific component recommendations
Filter and sort by relevance score

Problem Analysis Keywords:

"overload", "overwhelm", "too many" -> Cognitive Load Theory
"find", "search", "navigate" -> Information Scent
"cluttered", "messy", "disorganized" -> Visual Hierarchy
"mobile", "touch", "responsive" -> Fitts's Law
"confusing", "unclear", "complex" -> Progressive Disclosure

When to use this vs full BID workflow:

Use bid_quick_suggest(): Quick fixes, prototyping, single issues
Use full workflow: Comprehensive redesigns, complex projects, team collaboration

Quarto Dashboard Compatibility: Component suggestions include both Shiny-specific (shiny::) and framework-agnostic components. For static Quarto dashboards or OJS-based interactivity, focus on bslib, DT, plotly, reactable, and leaflet suggestions. Shiny-prefixed components require server: shiny in Quarto dashboards or a traditional Shiny app.

Examples

# Basic usage
suggestions <- bid_quick_suggest(
  problem = "Users can't find the download button"
)
#> ℹ Analyzing your UX problem
#> ℹ Detected 2 relevant UX concepts
#> ℹ Suggested layout pattern: breathable
#> ℹ Generating actionable suggestions
#> Quick suggestions ready
#>   - Found 9 suggestions (avg relevance: 0.89)
#>   - Top concept: Cognitive Load Theory
#>   - Use bid_concept() to learn more about any concept 
print(suggestions)
#> # A tibble: 9 × 7
#>   title                    details components concept score difficulty rationale
#>   <chr>                    <chr>   <list>     <chr>   <dbl> <chr>      <chr>    
#> 1 Limit initial choices    Show o… <chr [3]>  Cognit…  1    moderate   Reduces …
#> 2 Use progressive complex… Start … <chr [3]>  Cognit…  0.96 easy       Prevents…
#> 3 Provide smart defaults   Pre-se… <chr [3]>  Cognit…  0.93 moderate   Leverage…
#> 4 Use descriptive labels … Make n… <chr [3]>  Inform…  0.92 easy       Strong i…
#> 5 Establish clear informa… Use si… <chr [4]>  Visual…  0.9  easy       Helps us…
#> 6 Use collapsible advance… Place … <chr [2]>  Progre…  0.88 moderate   Reveals …
#> 7 Group related content v… Use co… <chr [3]>  Visual…  0.87 moderate   Leverage…
#> 8 Implement drill-down na… Allow … <chr [3]>  Progre…  0.87 easy       Matches …
#> 9 Apply Fitts's Law princ… Consid… <chr [3]>  Fitts'…  0.7  moderate   Systemat…

# With additional context
suggestions <- bid_quick_suggest(
  problem = "Dashboard has too many charts and metrics",
  context = "Financial analysts need quick insights but get overwhelmed",
  limit = 5
)
#> ℹ Analyzing your UX problem
#> ℹ Detected 1 relevant UX concepts
#> ℹ Suggested layout pattern: breathable
#> ℹ Generating actionable suggestions
#> Quick suggestions ready
#>   - Found 5 suggestions (avg relevance: 0.95)
#>   - Top concept: Cognitive Load Theory
#>   - Use bid_concept() to learn more about any concept 

# Filter to specific package
bslib_suggestions <- bid_quick_suggest(
  problem = "Mobile interface is hard to use",
  package = "bslib",
  min_score = 0.8
)
#> ℹ Analyzing your UX problem
#> ℹ Detected 1 relevant UX concepts
#> ℹ Suggested layout pattern: breathable
#> ℹ Generating actionable suggestions
#> Quick suggestions ready
#>   - Found 6 suggestions for package 'bslib' (avg relevance: 0.91)
#>   - Top concept: Cognitive Load Theory
#>   - Use bid_concept() to learn more about any concept 

# Navigation issues
nav_suggestions <- bid_quick_suggest(
  problem = "Users get lost in multi-tab interface",
  context = "Application has 10+ tabs with nested content"
)
#> ℹ Analyzing your UX problem
#> ℹ Detected 1 relevant UX concepts
#> ℹ Suggested layout pattern: tabs
#> ℹ Generating actionable suggestions
#> Quick suggestions ready
#>   - Found 8 suggestions (avg relevance: 0.91)
#>   - Top concept: Cognitive Load Theory
#>   - Use bid_concept() to learn more about any concept 

# Information overload
overload_suggestions <- bid_quick_suggest(
  problem = "Too many filters and options on the sidebar",
  context = "Beginners find the interface overwhelming"
)
#> ℹ Analyzing your UX problem
#> ℹ Detected 4 relevant UX concepts
#> ℹ Suggested layout pattern: breathable
#> ℹ Generating actionable suggestions
#> Quick suggestions ready
#>   - Found 10 suggestions (avg relevance: 0.9)
#>   - Top concept: Cognitive Load Theory
#>   - Use bid_concept() to learn more about any concept