This or That Rating Question

When and Why to Use

Use this to gather nuanced preferences across paired options using a rating scale. Ideal for:

• Capturing degrees of preference between two alternatives
• Visualizing directional lean with intensity
• Behavioral or brand comparison tasks

Supports slider or button input styles with configurable point scales.

Chat Experience

• Each row shows a pair of options with a slider or buttons between them
• The midpoint represents neutrality; endpoints indicate strong preference
• Don't know option appears if configured

Button style	Slider style

Traditional Experience

• Pairs are displayed in tabular layout with rating scale between them
• Works well with remote or keyboard navigation
• Layout adapts to available screen width

Button style	Slider style on mobile

Configuration Options

Option	Type	Required	Default	Description
question	string	yes	-	The prompt shown to the user
row_options	List[List[str]]	yes	-	List of 2-option comparisons per row
row_name	string	no	"scale"	Label for the row dimension in reporting
number_of_points	int	no	5	Number of scale points; slider and button styles support 2-10 points
first_point	int	no	1	Starting value for scale (optional)
style	string	no	"slider"	"slider" or "button" input style
dont_know_option	str	no	""	Optional "Don't know" response per pair; reported with this text and stored as a sentinel value
randomize	bool	no	False	Randomize row order
default	Dict[str, int] | List[Dict[str, int]]	no	random	Test-data defaults keyed by generated endpoint name (e.g., "Apples to Oranges"), or a list of candidate dictionaries — each simulated respondent picks one at random
recodes	Dict[str, str]	no	-	Map exact point strings (e.g., "1", "5") to reported labels; no range or percentage syntax
image	MediaItem	no	-	Optional image above the task
image_size	Tuple[int, int]	no	(600, 600)	Bounding box size for a displayed image
custom_validator	Callable[[Dict[str, int] | int | str], str | None]	no	-	Called with the parsed dictionary in the traditional experience, or with each parsed rating in the chat experience (asked row by row); "Don't know" rows arrive as strings
number_seconds	int	no	0	Seconds to wait before allowing the respondent to continue
tags	s.tag()	no	-	Used in token substitution and reporting
id	str	no	-	Optional stable identifier for this question

Example Code

Basic usage:

s.this_or_that_rating_question( "Which of the following do you prefer?", number_of_points=5, row_options=[ ["Apples", "Oranges"], ["Coke", "Pepsi"], ["Dogs", "Cats"], ["Winter", "Summer"] ] )

With recodes:

s.this_or_that_rating_question( "Rate your preference for each pair", number_of_points=7, row_options=[["Tea", "Coffee"], ["Netflix", "YouTube"]], recodes={ "1": "Strongly Left", "4": "Neutral", "7": "Strongly Right" } )

With custom validation:

s.this_or_that_rating_question( "Indicate which you prefer in each pair", number_of_points=5, row_options=[["Texting", "Calling"], ["Books", "Podcasts"]], custom_validator=lambda d: "Please vary your responses" if len(dict.fromkeys(d.values())) == 1 else None )

Notes

• Returns a DictResponse keyed by the generated endpoint names (e.g., "Apples to Oranges"); each value is the parsed IntResponse rating, or the "Don't know" sentinel
• Use an odd number of points to include a neutral midpoint
• The left option in each pair anchors the low end of the scale
• recodes are useful for bucketing individual scale points (such as "1" or "5") into preference categories
• custom_validator can prevent straight-lining or require balance