Monitor when a user changes their email address in your R application

LogSnag is a powerful event tracking tool that makes it easy to track events across your R application. LogSnag makes it easy to monitor when user activity in your application.

Most of the time, when building a R application that is served to users, you will need to store the user's email address in your database. There are multiple reasons for this, such as sending the user a welcome email when they sign up for your application, sending the user a password reset email when they request a password reset, or sending the user a notification when they have been mentioned in a comment. In addition, it is commonly used for user authentication and authorization.

In most cases, some users may want to change their email addresses for various reasons while using your application. For example, they may have mistyped their email address when they signed up for your application or changed their email address for personal reasons. In any case, it is essential to track when a user changes their email address in your R application to ensure that you are always aware of the change and can update your database accordingly.

Fortunately, here at LogSnag, we have created a powerful solution for this problem. At its core, logSnag is a powerful, real-time event tracking tool that works seamlessly with any R application. LogSnag makes it easy to track any important event in your R application and monitor things such as user activity, user journeys, and more.

One common use case for LogSnag is to set up event tracking for when users change their email addresses in your R application in real-time. You may also optionally set up rules to notify you and your team when a user changes their email address in your R application.

In addition, LogSnag allows you to track user journeys and create a timeline of their actions to monitor the users' email address history and any other activity they have done in your application. This way, you can always track the activity of a specific user, such as when they change their email address and any other activity they have done in your application.


Setting up LogSnag

  1. Sign up for a free LogSnag account.
  2. Create your first project from the dashboard.
  3. Head to settings and copy your API token.

R code snippets

Use the following code snippet to track when a user changes their email address in your R application. All you need to do is to replace the YOUR_API_TOKEN with your LogSnag API token and update the project name to your project name.

Using R with httr
library(httr)

headers = c(
  'Content-Type' = 'application/json',
  'Authorization' = 'Bearer YOUR_API_TOKEN'
)

body = '{
  "project": "my-saas",
  "channel": "profile",
  "event": "Updated Email Address",
  "description": "User updated their email address to john@example.com",
  "icon": "📭",
  "notify": true
}';

res <- VERB("POST", url = "https://api.logsnag.com/v1/log", body = body, add_headers(headers))

cat(content(res, 'text'))
Using R with RCurl
library(RCurl)
headers = c(
  "Content-Type" = "application/json",
  "Authorization" = "Bearer YOUR_API_TOKEN"
)
params = "{
  \"project\": \"my-saas\",
  \"channel\": \"profile\",
  \"event\": \"Updated Email Address\",
  \"description\": \"User updated their email address to john@example.com\",
  \"icon\": \"📭\",
  \"notify\": true
}"
res <- postForm("https://api.logsnag.com/v1/log", .opts=list(postfields = params, httpheader = headers, followlocation = TRUE), style = "httppost")
cat(res)

R integration details

LogSnag provides a set of powerful features such as cross-platform push notifications, event filtering, user and product journeys, charts, insights, and more. In addition, LogSnag is flexible and easy to use, making it a great companion for your R applications.

LogSnag provides a generous free plan to get you started with event tracking. You can also check out our pricing page to see our paid plans. So don't hesitate to give us a try and let us know what you think!

Other use-cases for LogSnag

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  6. Get a notification when your R code is done executing

  7. Monitor when a user exceeds the usage limit for your R service

  8. Monitor when a new feature is used in your R application

  9. Monitor suspicious activity in your R application

  10. Monitor when a user is being rate limited in your R application

  11. Monitor when database goes down in your R application

  12. Monitor your CPU usage in your R application

  13. Monitor memory usage in your R application

  14. Monitor high disk usage in your R application

  15. Track when a file is uploaded to your R application

  16. Track when a form is submitted to your R application

  17. Track canceled subscriptions in your R application

  18. Monitor failed payments for your R application

  19. Monitor your CI/CD build status for your R application

  20. Monitor Redis downtime in your R application

    View all common use-cases with R