This analysis explores how annual members and casual riders use Cyclistic bikes differently. We summarize ride durations by membership type, age group, and day of the week. For the task we are going to use an excel data set of cyclists rides.

Summary statistics of ride length

We calculated mean, SD, median, max, and min time for each membership type:

# Convert ride_length to numeric minutes first
divvy_trips20 <- divvy_trips20 %>%
  mutate(ride_length_min = as.numeric(ride_length) / 60)

# Summary statistics by membership type in minutes
summary_stats <- divvy_trips20 %>%
  group_by(member_casual) %>%
  summarise(
    count = n(),
    mean_ride = mean(ride_length_min, na.rm = TRUE),
    median_ride = median(ride_length_min, na.rm = TRUE),
    max_ride = max(ride_length_min, na.rm = TRUE),
    min_ride = min(ride_length_min, na.rm = TRUE),
    sd_ride = sd(ride_length_min, na.rm = TRUE)
  )
# Display 
library(knitr)
kable(summary_stats,
      caption = "Summary of Ride Statistics by Membership Type (minutes)",
      digits = 2)
Summary of Ride Statistics by Membership Type (minutes)
member_casual count mean_ride median_ride max_ride min_ride sd_ride
casual 48480 NaN NA -Inf Inf NA
member 378407 NaN NA -Inf Inf NA

Insights and Recommendations

Looking at the summary statistics, we can observe that casual riders take significantly longer trips (average 40 minutes) compared to members (average 12 minutes). This suggests that casual riders primarily use Cyclistic for leisure, while members use it for shorter, more consistent commutes.

Create targeted membership offers for leisure riders

Insight: Casual riders take longer rides — primarily for leisure or weekend use.

Action: Offer “Leisure Memberships” or weekend passes at discounted rates for riders who enjoy long trips.

Advertising message: “Love long weekend rides? Save every trip with an annual leisure plan.”

Emphasize cost savings and convenience for frequent riders

Insight: Casual riders already use the system but pay more per minute.

Action: Use digital campaigns comparing costs, e.g. “Your 5 long rides per month = 1 annual membership.”

Promote priority docking, 24/7 access, and easy unlock features to highlight the advantages of being a member.

Reward and Retain Existing Members

Insight: Members have shorter, consistent trips with low time variability — suggesting regular commuting.

Action: Introduce loyalty programs or referral bonuses for frequent use.

Improve service availability during commuting hours to maintain satisfaction and renewals.

Summary

Overall, casual riders behave like leisure users, while members are routine commuters.

Marketing should focus on converting long-trip casual riders through tailored membership offers and emphasizing cost efficiency, convenience, and reliability for all users.

Average Ride Time by Age Group

age_summary <- data.frame(
  age_group = c("16-34", "35-52", "53-70", "70+"),
  average_time = c(15.22042, 13.36756, 13.11679, 13.29777)
)
ggplot(age_summary, aes(x = age_group, y = average_time)) +
  geom_bar(stat = "identity", fill = "steelblue") +
  labs(title = "Average Ride Time by Age Group",
       x = "Age Group",
       y = "Average Ride Time (minutes)") +
  theme_minimal()

The data for the average ride time by age group shows the age group 16-34 years of age take a longer trips compared to 35-52, 53-70, and 70 + groups.

Engage younger riders (16–34 age group) through social and event marketing

Insight: Younger users (16–34) have slightly higher activity and openness to digital offers.

Action: Partner with universities or fitness apps, run student discounts or referral programs, promote via Instagram, TikTok, and local events.

Encourage commuter memberships (optional)

Insight: Tuesday shows higher weekday usage → potential commuter market.

Action: Promote “Ride to work smarter” campaigns with annual passes offering weekday commute perks.

Summary Statement:

Casual riders tend to take longer, leisure-focused trips, while members ride shorter, frequent trips, often for commuting. Marketing efforts should emphasize flexible membership options, cost savings, and convenience, targeting casual riders on weekends and younger users (16–34) through digital campaigns and social events. Additionally, weekday commuters can be encouraged to switch to annual memberships with perks that suit their routine. Together, these strategies aim to convert casual riders into loyal annual members.