The Product POD team from a retail industry is planning to launch a new product and wants to test different variations of the product's landing page. However, they're concerned about the potential…

Question

Options

• APause the test if there is a significant drop in conversion rates
• BTest the variations on a different website before implementing them on the main site
• CImplement the variations only during off-peak hours
• DOnly show the new variations to a small subset of visitors

• A
  2% (1)
• B
  9% (5)
• C
  6% (3)
• D
  83% (44)

Explanation

Showing new landing page variations to only a small subset of visitors (D) is the standard A/B testing best practice for risk mitigation - it limits exposure of potentially underperforming variations to a fraction of users, so any negative UX impact affects the fewest people while still generating statistically useful data.

Why the distractors fail:

• A is reactive, not preventive - pausing after a significant conversion drop means damage has already occurred at scale.
• B introduces a different audience/context, making results unreliable for the main site; results from a different website don't generalize.
• C artificially skews your sample toward off-peak user behavior, which may not represent your typical audience, corrupting the test's validity.

Memory tip: Think "small sample, safe test" - controlled exposure is the cornerstone of A/B testing. The word subset in option D maps directly to the core principle of traffic splitting in experimentation frameworks.

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