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Create personalized onboarding flow

Analyze your user behavior to deliver targeted emails and in-app experiences.

User onboarding is crucial to long-term user retention. Users who quickly see the value in your product are likely to convert and continue using your product or service.

A great way to achieve this is through personalized onboarding. This can take a variety of forms, but the crucial point is that you tailor a user's first experience of your product and your brand. This helps them achieve success faster and increases the retention rate.

Step 1: Connect your data source

First, you will need to make sure that your customer interaction data is properly sent to Intempt Platform. Go to Sources -> Create a source and set up an Intempt JS tracker on your app.

Step 2: Create events

To create a proper onboarding flow, you will need to create specific activation events. Activations events are the actions or steps users need to take to reach the peak moment and become activated users. Identifying your activation event(s) will help you find your peak moment, and vice versa.

To do that, first, make a list of all the possible actions in your application. For example:

  • update a profile
  • Invited a team member
  • created a post
  • number of posts written
  • sharing articles.

After you list all the events, you will need to create them via the Intempt Event editor.

Step 3: Create conversion metric

To identify activation events, you will need to create a conversion metric first.

Go to “Metrics” -> Create a new metric, define the period you want to analyze, select the format (percentage) and choose the required metric creation options from the dropdown.

Conversion: ([A] Subscription count / [B] Total count of users) * 100%

[A] Total revenue:

Type-> Collection

Source-> your JS or iOS tracked website

Collection-> subscriptions

Field-> amount

Aggregation-> Total

[B]Total count of users:

Type-> [B] Users

Filter-> [B] Total User Count

Concept-> Custom metrics

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Step 4: Compare events via event comparison graph

Use the event comparison graph to analyze which events activated most users.

Go to event editor and select the created events to compare them against the conversion rate metric.

Analyze the generated graph and select events that drive the most conversions.

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Step 5: Set up your onboarding flow

Based on the event comparison insights list the activation events in a sequence that is meaningful to your users. For example:

  • Published post/entry/article/tweet
  • Uploaded logo/profile picture
  • Connected bank account/payment processor/credit card
  • Updated profile x times
  • Added team members/friends
  • Contacted prospect using app
  • Linked social account

Step 6: Create destinations

Now it is time to connect appropriate onboarding emails. You will need to set up email destinations that will be triggered by the selected activation events.

For example, once the user publishes a post (activation event), he will trigger an email destination that will send him a personalized email suggesting to do the next step in the onboarding process.

To set up the destination, go to “Destinations” choose your email connector and action “Send email”. Once you configure destinations for every onboarding event, you have your onboarding flow ready.

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You can also go deeper and add a checklist of all activation events (done vs to do). This way users can see the progress of their onboarding and are incentivized to move through all the suggested steps.

Step 7: Measure success

With Intempt Platform you can calculate the effectiveness of your onboarding flow. There are few metrics that are critical in measuring success:

Adoption rate = [A] number of new active users / [B] total number of users

[A] number of new active users:

Type -> [A] Users

Filter -> [A] Users by segment

Period: 1 month

Segment -> [A] Active users

[B] Total count of users:

Type -> [B] Users

Filter -> [B] Total User Count

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Engagement rate = [A] Active subscribed users over a certain time period/ [B] Total subscribed

[A] number of new active users:

Type -> [A] Users

Filter -> [A] Users by segment

Segment -> [A] Subscribed active users

[B] Total count of users:

Type -> [A] Users

Filter -> [A] Users by segment

Segment -> [A] Subscribed users

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Retention rate = [A] Active users that continue their subscription / [B] Total number of active users at the start of a time period.

[A] number of new active users:

Type -> [A] Users

Filter -> [A] Users by segment

Segment -> [A] Subscribed active users

Period: 1 month

[B] Total count of users:

Type -> [A] Users

Filter -> [A] Users by segment

Segment -> [A] Active users

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