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Which of the following metrics would most strongly suggest a poorly performing landing page?

a. Bounce Rate > 90%
b. % New Visits > 90%
c. Session Duration > 5 minutes
d. Bounce Rate < 90%
e. None of these answers

User Tergiver
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1 Answer

7 votes

Final answer:

A Bounce Rate > 90% most strongly suggests a poorly performing landing page because it indicates that visitors are leaving quickly without engaging. In contrast, a high percentage of new visits and a longer session duration are generally positive indicators of performance.

Step-by-step explanation:

The metric that would most strongly suggest a poorly performing landing page is a. Bounce Rate > 90%. A high bounce rate indicates that a significant portion of visitors are leaving the page without engaging with the content or navigating to other parts of the website. This is generally seen as a negative signal, as it could imply that the page content is not relevant or compelling enough to retain visitors. On the other hand, a high percentage of new visits can be a positive indicator of a growing audience, and a long session duration suggests visitors are engaging with the content on the page. A lower bounce rate is typically desired, showing that visitors are interacting more with the website.

For the problem of website traffic with an exponential distribution:

  1. Finding the probability that the duration between two successive visits to the website is more than 10 minutes involves using the rate of visits per hour (12 visits per hour) to calculate the lambda (λ) for the exponential distribution and then calculating the survival function for 10 minutes.
  2. The top 25 percent of durations are determined by finding the value at the 75th percentile of the exponential distribution.
  3. Calculating the probability of the next visit occurring within the next five minutes after a 20-minute gap utilizes the memoryless property of the exponential distribution and its probability density function.
  4. To find the probability that fewer than seven visits occur within a one-hour period, one would use the Poisson distribution with the rate parameter based on the average visits per hour.

User Luca Schimweg
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