mattm

// Add this below the analytics tracking:
if ( sectionName === 'pricing' ) {
  setCookie( 'viewed_homepage_pricing', 'true' );
}

// Then in your sign up event:
analytics.record( 'Signed Up', {
  viewed_pricing: getCookie( 'viewed_homepage_pricing' ) === 'true'
} );

mattm

+------------+----------+---------+
|    week    |   plan   | signups |
+------------+----------+---------+
| 2017-01-26 | Bronze   |      10 |
| 2017-01-26 | Gold     |      55 |
| 2017-01-26 | Standard |     108 |
| 2017-02-05 | Bronze   |       6 |
| 2017-02-05 | Iron     |       1 |
| 2017-02-05 | Gold     |      37 |
| 2017-02-05 | Standard |     142 |

mattm

library(ggplot2)

data <- read.csv("dummy-data.csv", sep = "\t")

g <- ggplot(data, aes(x = week, y = signups, group = plan, fill = plan)) +
	geom_area()

print(g)

mattm

         week     plan
1  2017-01-26   Bronze
2  2017-02-05   Bronze
3  2017-02-12   Bronze
4  2017-02-19   Bronze
5  2017-02-26   Bronze
6  2017-01-26     Gold
7  2017-02-05     Gold
8  2017-02-12     Gold
9  2017-02-19     Gold

mattm

         week     plan signups
1  2017-01-26   Bronze      10
2  2017-01-26     Gold      55
3  2017-01-26 Standard     108
4  2017-02-05   Bronze       6
5  2017-02-05     Iron       1
6  2017-02-05     Gold      37
7  2017-02-05 Standard     142
8  2017-02-12   Bronze      17
9  2017-02-12     Iron       2

mattm

         week     plan signups
1  2017-01-26   Bronze      10
2  2017-01-26     Gold      55
3  2017-01-26     Iron       0
4  2017-01-26 Platinum       0
5  2017-01-26   Silver       0
6  2017-01-26 Standard     108
7  2017-02-05   Bronze       6
8  2017-02-05     Gold      37
9  2017-02-05     Iron       1

mattm

data <- read.csv("data.csv", sep = "\t")

weeks <- unique(data$week)
plans <- unique(data$plan)
combinations <- expand.grid(week = weeks, plan = plans)

data <- full_join(data, combinations, by = c("week" = "week", "plan" = "plan")) %>%
	mutate(signups = ifelse(is.na(signups), 0, signups)) %>%
	arrange(week, plan)

mattm

data <- read.csv("data.csv", sep = "\t")

data <- data %>%
    tidyr::spread(key = plan, value = signups, fill = 0) %>%
    tidyr::gather(key = plan, value = signups, - week) %>%
    arrange(week, plan)

g <- ggplot(data, aes(x = week, y = signups, group = plan, fill = plan)) +
    geom_area(position = "stack")

mattm

        week Bronze Gold Iron Platinum Silver Standard
1 2017-01-26     10   55    0        0      0      108
2 2017-02-05      6   37    1        0      0      142
3 2017-02-12     17   42    2        0      0      119
4 2017-02-19     11   26    0        1      4       70
5 2017-02-26     13    0    0        0      5       52

mattm

         week     plan signups
1  2017-01-26   Bronze      10
2  2017-01-26     Gold      55
3  2017-01-26     Iron       0
4  2017-01-26 Platinum       0
5  2017-01-26   Silver       0
6  2017-01-26 Standard     108
7  2017-02-05   Bronze       6
8  2017-02-05     Gold      37
9  2017-02-05     Iron       1