Plot.line(data, { x: "Date", y: "Users", tip: true }).plot({
marginLeft: 50,
title: "BetterHelp's user growth has inverted",
caption:
"BetterHelp have seen monthly paying user decreases for four consecutive quarters from Q2 2023.",
y: {
grid: true,
ticks: 5,
tickFormat: "s",
label: "Monthly Paying Users"
}
})
Plot.line(data, { x: "Date", y: "Revenue", tip: true }).plot({
marginLeft: 50,
title: "BetterHelp's revenue growth has inverted",
caption:
"BetterHelp have seen revenue decreases for four consecutive quarters from Q2 2023.",
y: {
grid: true,
ticks: 5,
tickFormat: "$s"
}
})
Plot.rectY(data, {
x: "Date",
y: "EBITDA",
tip: true,
interval: d3.utcMonth.every(3)
}).plot({
marginLeft: 50,
title: "BetterHelp isn't getting more expensive to provide",
caption:
"BetterHelp's EBITDA exhibits a seasonal pattern, but is largely stable. EBITDA is Earnings Before Interest, Taxes, Appreciation, and Amortization, and is a rough measure of the profitability of the service. We would expect it to significantly decrease if the service was getting more expensive to provide.",
y: {
grid: true,
ticks: 5,
tickFormat: "$s"
},
marks: [Plot.ruleY([0])]
})
Plot.rectY(data, {
x: "Date",
y: "Margin",
tip: true,
interval: d3.utcMonth.every(3)
}).plot({
marginLeft: 50,
caption: "BetterHelp's margins, derived by dividing EBITDA by revenue.",
y: {
grid: true,
ticks: 5,
tickFormat: "%"
},
marks: [Plot.ruleY([0])]
})
Plot.lineY(data, {
x: "Date",
y: "Marketing Yield",
tip: true
}).plot({
marginLeft: 50,
title: "Teladoc's return on marketing is decreasing",
caption:
"BetterHelp's new users per million dollars spent on marketing has dramatically decreased, and inverted in Q3 2023.",
y: {
label: "New users per million dollars",
grid: true,
ticks: 5
},
marks: [Plot.ruleY([0])]
})
data = [
{
Date: "2021-12-31",
Users: 351_000,
Revenue: 214_000_000,
EBITDA: 43_000_000,
Marketing: 112_988_000
},
{
Date: "2022-03-31",
Users: 382_000,
Revenue: 230_000_000,
EBITDA: 30_000_000,
Marketing: 133_600_000
},
{
Date: "2022-06-30",
Users: 408_000,
Revenue: 247_000_000,
EBITDA: 20_000_000,
Marketing: 164_574_000
},
{
Date: "2022-09-30",
Users: 437_000,
Revenue: 265_000_000,
EBITDA: 11_000_000,
Marketing: 178_920_000
},
{
Date: "2022-12-31",
Users: 450_000,
Revenue: 277_000_000,
EBITDA: 53_000_000,
Marketing: 146_443_000
},
{
Date: "2023-03-31",
Users: 467_000,
Revenue: 279_000_000,
EBITDA: 18_000_000,
Marketing: 176_790_000
},
{
Date: "2023-06-30",
Users: 476_000,
Revenue: 292_000_000,
EBITDA: 34_000_000,
Marketing: 178_756_000
},
{
Date: "2023-09-30",
Users: 459_000,
Revenue: 285_000_000,
EBITDA: 26_000_000,
Marketing: 186_152_000
},
{
Date: "2023-12-31",
Users: 425_000,
Revenue: 276_000_000,
EBITDA: 58_000_000,
Marketing: 147_156_000
},
{
Date: "2024-03-31",
Users: 415_000,
Revenue: 269_000_000,
EBITDA: 15_000_000,
Marketing: 183_329_000
},
{
Date: "2024-06-30",
Users: 407_000,
Revenue: 265_000_000,
EBITDA: 25_000_000,
Marketing: 170_270_000
}
].map(({ Date: rawDate, Users, Revenue, EBITDA, Marketing }, i, array) => ({
Date: new Date(rawDate),
Users,
Revenue,
EBITDA,
Margin: EBITDA / Revenue,
Marketing,
"Marketing Yield":
i > 0 ? ((Users - array[i - 1].Users) / Marketing) * 1_000_000 : undefined
}))
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